Nature Ecrogrow

For example, Adafruit sells ADCs with resolutions ranging from 8‐ to 16‐bits and includes open‐ source software libraries and hardware design for interfacing them with a Raspberry Pi or other single‐board computer. Some sensing applications, however, such as thermocouple psychrometry and load cell measurement, involve the detection of small changes within a large measurement range. These applications may require higher than 16‐bit resolution, thus necessitating an ADC with higher resolution along with low‐noise and low‐drift electronic components. The DAQ system described here provides high resolution at a significantly lower cost than commercial laboratory DAQ systems with similar specifications. It uses the ADS1262 ADC , which has 32‐bit resolution, very low noise and drift , as well as many built‐in features . The ADS1262 and ADS1263 are identical except that the ADS1263 also includes one additional independently controlled 24‐bit ADC. The ADS1262 was used in the system described here, but the ADS1263 can also be used and will perform the same. These features allow this ADC to be used with many different types of sensors; however, the manufacturer of this ADC does not provide a software library that allows it to be easily interfaced with a Linux computer like the Raspberry Pi. To address this, we describe here the open‐source software libraries we developed to provide this interface, called piadcs, and the electronic system design required to use this ADC with a Raspberry Pi to make ultra‐ high‐resolution measurements.The DAQ system consists of a relatively simple hardware design based around a Raspberry Pi and the ADS1262/3 , 10 plastic plant pots and the piadcs software libraries enable users to easily configure the ADS1262/3 and to collect, convert, and store the output data.

The ADS1262/3 is a good choice for a custom DAQ system because of its extremely high resolution and many features that give it flexibility . Functions to modify these settings are found in both piadcs libraries. There are functions for both reading data continuously or reading on command. Communication between the Raspberry Pi and the ADS1262/3 uses a combination of SPI and GPIO. The Go version of the library uses the Periph library to control the SPI and GPIO interfaces, and the Python version uses Spidev and RPi.GPIO . There are other ADCs on the market that use highly similar programming to the ADS1262/3, and the piadcs libraries are extendable to such ADCs. The libraries also contain documentation and examples that provide a template for programming other ADCs.There are two functionally equivalent versions of the piadcs library: one is written in Python and the other in Go. The two versions offer different advantages and disadvantages due to differences between the two languages. Python is one of the most widely used programming languages, but as an interpreted language, it runs slower and does not have support for concurrency. Go is less commonly used but still among the top 20 most‐used programming languages . Go is a compiled language, which provides performance advantages over Python and is simpler to read than other compiled languages . Both versions of the piadcs library are available on GitHub.Both are installed as packages, and detailed instructions for installation and usage can be found in the README file on GitHub. In brief, the Python library is installed from the command line using the “pip3” command and the Go library is installed using the “go get” command. The “Examples” folders found in the libraries contain code examples showing how to use the different functions in the library to change ADC settings and collect data from the ADC.

These libraries were designed to run on a Raspberry Pi model 4B or 3B+ running Raspberry Pi OS. It may also be possible to run them on other models provided they are running an up‐to‐date version of the same operating system, but we have not tested this. There are many helpful guides available on how to get started with a Raspberry Pi and the Raspberry Pi OS. For an official source, the documentation section of the Raspberry Pi website provides a detailed guide .The DAQ system can be built using the materials listed in Table 1 for about US$100. The wiring diagram shown in Figure 1 illustrates how the components are connected. The ADS1262/3 can be connected to the Raspberry Pi using one SPI bus and three GPIO pins. In our setup , they are connected via the Raspberry Pi’s SPI_0 and GPIO pins 4, 22, and 27, but any of the available SPI interfaces and GPIO pins could be used. These connections must be specified in the code. Several breakout boards are available for connecting the ADS1262/3 to solderless breadboards for prototyping. A breakout board from ProtoCentral was used in the development of these libraries, but an alternative from Olimex would also be suitable . A Raspberry Pi–specific “HAT” for the ADS1263 is available from Waveshare . It is compatible with the piadcs libraries, but it is not suitable for low‐noise measurements in that one cannot electrically isolate the Raspberry Pi and the ADC because they share the same power supply; moreover, this board situates heat‐generating components near the temperature sensor of the ADC. High‐resolution measurements require low system noise. In our DAQ system, low noise is achieved by electrically isolating the ADS1262/3 from the Raspberry Pi. This requires separate power supplies. The Raspberry Pi is powered by a standard USB‐C wall adapter , which is usually sold with the computer, whereas the ADS1262/3 is powered by 9‐V batteries connected to linear voltage regulators. Batteries are preferable to wall supplies because they do not generate any 60 Hz AC noise. The ADS1262/3 draws less than 6.5 mA, and so a battery lasts for several weeks. The digital communication channels between the ADS1262/3 and the Raspberry Pi are also isolated using the ADuM4151 7‐channel SPIsolator .

All the components for this custom DAQ system can be wired onto a solderless breadboard or made into a printed circuit board. A solderless breadboard setup was used for the test measurement shown in Figure 2.It is possible to make very low noise measurements with this DAQ system as long as the aforementioned electrical considerations are addressed. System performance was tested with and without sensors connected. We first measured baseline system noise with no sensors connected and found that, at slower data rates , the system noise is remarkably low and the system has better than 1 ppm precision. As the data rate increases, the noise increases and precision decreases somewhat but is still very good . The ADS1262/3 has 16 different data rates available ranging from 2.5 to 38,400 samples/second, but our DAQ system only performs well at data rates up to 14,400 samples/ second. This is due to a breakdown in serial communication that occurs at higher speeds and could potentially be solved in future releases. Although the ADC used in this system has a nominal resolution of 32‐bits, the actual system precision is lower, especially as the data rate increases. Noise remaining in the system , along with the inherent tradeoff between ADC speed and resolution, causes the effective resolution of an ADC to be lower than its nominal resolution . The noise floor and, therefore, the effective resolution of our system is very close to that specified in the ADS1262 datasheet for the data rates and digital filters tested , plastic pots large and is a major improvement over other existing open‐source DAQ systems for the Raspberry Pi. System performance with a connected sensor was tested by measuring the output of a K‐type thermocouple submerged in an ice bath using our DAQ system. This setup was able to measure the ice bath temperature with a noise level of less than ±0.01°C ; this was achieved using only the analog front end provided on the ADS1262 with the PGA set to the maximum setting of 32 V/V. An external ultra‐low‐noise amplifier set to a higher gain could be used instead of the onboard PGA to further decrease noise for applications requiring very low‐level measurements . Our DAQ system has significantly better noise performance than other Raspberry Pi thermocouple DAQ systems. For example, the MCC 134 Thermocouple DAQ HAT for Raspberry Pi has greater than 0.5°C measurement error with the same type of thermocouple. This is likely due partly to large thermal gradients caused by placing the DAQ board on top of the heat‐generating components of the Raspberry Pi.Two assumptions have guided the study of concept learning ever since Hull . The first is that category learning amounts to learning a common label for sets of objects. This assumption is explicit in the ubiquitous supervised classification task, in which people receive feedback when classifying visually presented stimuli. This paradigm has been used to determine, for example, whether prototype models are superior to exemplar models . Over the years, researchers have taught people to group objects into sets and have examined the resulting representations. A second assumption has been that information about a category learned in one context, should not transfer well to another. Consider the goal of distinguishing roses from raspberry bushes. If the most diagnostic feature is the presence of berries, then people will learn that the berry feature should receive the most attention weight . However, when one later has to distinguish raspberry from cranberry bushes, thorns suddenly become diagnostic, because while both have red berries, only the raspberry bush has thorns.

The problem is that optimizing attention for one category contrast is not always optimal for another . The consequence of ignoring irrelevant dimensions for one set of category contrasts means that the learner has to re-attend those dimensions when familiar categories are contrasted in novel ways. That is, the learner has to relearn about raspberries. In this manner, the heralded powers of selective attention assumed by present theories are predicted to harm performance when previously irrelevant dimensions become relevant. The mechanisms of attention allocation in many computational models of category learning suggest that people learn to attend to only that information needed to distinguish the two categories being acquired. The problem we raise is that after learning one classification in which, say, cue A is most diagnostic, people should have trouble learning a second classification in which B is the good cue, because prior classifications have taught people to ignore it . We ask two questions in this study. First, how rigid are learners’ representations across different learning tasks? Second, can attention provide an explanatory variable for differences in what is learned between tasks? We speculate that flexible category representations are necessary for everyday classification, since particular category contrasts are not always known ahead of time by the categorizer. Previous research points to inference as being a likely candidate for producing flexible representations. To the extent that inference but not classification produces flexible category representations, it may reflect a more ecologically valid task for studying the kinds of concepts that people use everyday.Other tasks, where the goal is not to classify, but to learn about the properties of categories, may yield a flexible representation that can handle novel contrasts. Research that has expanded the array of concept acquisition tasks led us to consider a task that may produce flexible conceptual representations. Whereas classification involves predicting the category label from features, feature inference learning involves predicting a missing feature from other features and the category label. So rather than determining that a plant is a raspberry bush,the inference task asks learners to determine whether a raspberry bush has thorns, or some other property. Comparisons of the feature inference task with supervised classification are of current interest, with evidence that inference produces different representations. It has been found that inference produces: increased sensitivity to within-category correlations of features , increased sensitivity to nondiagnostic, prototypical features , more prototypical-feature inferences, and faster learning of linearly separable categories . Thus, in spite inference and classification tasks being formally identical , it is possible that the resulting flexiblity of category representations can also differ. The above-cited evidence suggests that whereas classification learning may foster attention to the diagnostic dimensions that serve to distinguish between categories, inference learning may focus categorizers on within category information. Our hypothesis is that because the within-category information acquired by inference learners is not tied to any particular set of contrast categories, such knowledge yields a more general and flexible representation. As a consequence, with respect to novel contrasts, inference learners may be at an advantage over classification learners.

The pretrained models of these architectures were fine tuned with our proposed insect dataset so that they can be used for the yellow fly detection application, as fine tuning is also one of the common solutions for data scarcity problem in object detection. Because the models had been trained with COCO dataset, which is a large dataset having over 200,000 labeled images with 1.5 million object instances for 80 object categories, and, hence, contains common features for object detection problem, fine tuning the models with 200 yellow fly images helped the models perform the yellow fly detection task.To solve the real-time object detection in the yellow fly detection problem, variants of Single-Shot Multibox Detector are used. The SSD method was first proposed in [36] by Wei Liu et al. and described as a one stage object detection method that completely omits the region proposal and pixel/feature resampling stages used in region proposal-based techniques such as Faster-RCNN. The SSD network is based on a feed-forward network that uses default bounding boxes with different shapes, ratios, and scales to produce a fixed-size collection of bounding boxes with corresponding shape offsets and confidence scores. In addition, the early layers of the network are based on a standard image classification without classification layers, blueberry container size which is called the base network. In this work, MobileNetV1 and MobileNetV2 are used as base networks for the SSD detection models.

The elimination of region proposal and pixel/feature resampling stages helps to improve the processing speed of the model compared to two-stage techniques such as Faster-RCNN with a small trade-off in the model’s accuracy, which enables the implementation of real-time object detection with high accuracy on embedded system for yellow fly detection problem.The approach was first proposed in [37] by A. Howard et al. and was described as a lightweight deep neural network for mobile and embedded system applications with an efficient trade-off between latency and accuracy. The model is based on depth wise separable convolution including depth wise convolution layer which is used to apply a single filter per input channel, and pointwise convolution layer, which creates a linear combination of the output of the depth wise layer. In addition, to construct the model further less computationally expensive, width multiplier, which is used to thin the network uniformly at each layer, and resolution multiplier, which is applied to input images and the internal representation of each layer, were introduced as a hyperparameter to tune, and choose the size of the model.The MobileNetV2 approach was first presented in by M. Sandler et al. The approach is built based on MobileNetV1; therefore, it also makes use of the depth wise separable convolution architecture which consists of depth wise convolution layer and 1×1 point wise convolution layer. In addition, the approach also utilizes linear bottleneck layers in convolutional blocks to optimize the neural architecture. Moreover, inverted residual design is also used in the model to implement shortcuts between bottlenecks with the purpose of improving the ability of gradient propagation across the multiplier layers. Nevertheless, the implementation of the inverted design also showed better performance and significantly more memory efficiency in the work. The training and evaluation of the SSD with MobileNetV1 and MobileNetV2 base networks is based on the pre-trained models provided in the Object Detection API in TensorFlow Model Garden.

The models were also trained on the Google Colab Pro environment to utilize the provided GPUs for the training purpose.The assessments in this research are dedicated to search for the most appropriate object detection method among the current state-of-the-art algorithms which have been implemented for insect and fly recognition under our hardware constraints and problem definition. As we only target one type of fruit flies that particularly causes harm to the citrus fruits, we have replaced the yellow sticky paper with a white disc containing the special attractant as a hard refinement to pick up only the flies we are interested in. The object detection problem is then simplified to only one-class object detection, which eases the need for exhausting feature extraction. However, the general constraints, such as correctness and fastness, for an object detection task on an edge-device still hold since early detection and separation of the infected areas are extremely important to the fruit yield.Ultimately, SSD-MobileNetV1, SSD-MobileNetV2 and YOLOv4-tiny are the best candidates for these requirements because they utilize extracted features from a backbone classification model to automatically propose object-related regions instead of using a region-proposal module to pool the related regions before classifying them as many two stage object detection models, such as Fast-RCNN and Faster-RCNN.Regarding the correctness, YOLOv4-tiny clearly outperforms the two SSD models over all the evaluations on four different types of testset with very high and stable results. This could make YOLOv4-tiny become the most probable candidate, because YOLOv4-tiny demonstrates a robust testing performance towards citrus fruit fly detection although it has been fine-tuned only on a training dataset without augmentation effects. SSD-MobileNetV2 shows appropriate robustness given its small number of trainable parameters by yielding good results in two over four testsets, while SSD-MobileNetV1 only works with the original testset. Nevertheless, SSD-MobileNetv2 fails dramatically with the Blurry testset, which simulates a very frequent event that could happen in a fruit field. YOLOv4-tiny is no doubt the chosen one among the three methods if we would not have taken other aspects into account.

Conventionally, highly accurate object detection methods trade their processing speed for its better performance due to the employment of more parameters in their architecture. While missing a fraction of time could lead to undetectable events in which the flies appear, our second choice, which is the SSD-MobileNetV2 model, should be considered. To realize this choice after extensive performance analysis with four different testsets, SSD-MobileNetV2 must have been fine tuned with more augmented versions of the original training dataset before going to production to leverage its robustness to the level of YOLOv4-tiny while retaining its processing speed. Moreover, TFLITE version of SSD-models are also tested on a cloud TPU Google engine, TPUv2, for the feasibility of edge-device deployment. The overall assessment table for YOLOv4-tiny and SSD-MobileNetV2 is shown in Table 2 in terms of F1-Score and inference time.While San Joaquin Valley vineyards are currently fertilized with boron through the soil and foliage , some growers have expressed interest in applying boron via drip irrigation or “fertigation.” Fertigation is a relatively simple, cost-effective and efficient way to apply nutrients. However, irrigation water with more than 1 part per million boron can lead to vine toxicity, so the safety of boron fertigation is also a concern. Our research evaluates the safety and efficacy of boron fertigation in grapevines using drip irrigation. Boron is unique among the micronutrients due to the narrow range between deficiency and toxicity in soil and plant tissues. For grapevines, this range is 0.15 ppm to 1 ppm in saturated soil extracts, and 30 ppm to 80 ppm in leaf tissue. The goal of boron fertilization of grapevines is to keep tissue levels within this narrow range, since both deficiency and toxicity can have serious negative effects on vine growth and production. Fertilization amounts must be precise to avoid toxicity while providing adequate boron to satisfy grapevine requirements . On the east side of the San Joaquin Valley, boron deficiency of grapevines occurs on soils formed from igneous rocks of the Sierra Nevada. This parent material is low in total boron, growing raspberries in containers which is crystallized in borosilicate minerals that are highly resistant to weathering. Boron deficiency is often associated with sandy soils and vineyard areas with excessive leaching, such as in low spots or near leaky irrigation valves. Vine symptoms of boron deficiency are more widespread and pronounced following high rainfall years, when greater amounts of soluble boron are leached from the root zone. In addition, snowmelt water has very low levels of boron, and vineyards irrigated primarily with this water have a greater risk of deficiency. Boron is required for the germination and growth of pollen during flowering, and vines that are deficient in this micronutrient will have clusters that set numerous shot berries, small berries with a distinctive pumpkin shape. When boron deficiency is severe, vines produce almost no crop. Foliar symptoms appear in the spring: shoots have shortened, swollen internodes and their tips sometimes die, and leaves have irregular, yellowish mottling between the veins. Grapevines are also sensitive to too much boron. Toxicity is common on the west side of the San Joaquin Valley, where most soils are derived from marine sedimentary and metasedimentary parent material that is rich in easily weathered boron minerals. Symptoms of boron toxicity include leaves that are cupped downward in the spring and that develop brown spots adjacent to the leaf margin in middle or late summer, intensifying and leading to necrosis as boron accumulates.

Yields are reduced, the result of diminished vine vigor and canopy development. When foliar boron sprays are applied in excess in the spring, juvenile leaves become cupped within 2 weeks; however, vines quickly recover and yields are usually unaffected. Toxicity also occurs when boron fertilizer is applied in excess, regardless of the soil type, and this can lead to yield loss. Over-fertilization is the sole reason for boron toxicity on the east side of the San Joaquin Valley, so it is critical to establish how much boron fertilizer can be applied safely and effectively. Our research investigated the uptake of boron by grapevines when fertilizer was applied with a drip-irrigation system.Research was conducted from 1998 to 2001 in a mature ‘Thompson Seedless’ raisin vineyard near Woodlake in Tulare County. The vineyard was planted in Cajon sandy loam on a recent alluvial fan associated with the Kaweah River. This soil is derived from granitic parent materials, and the surface soil is highly micaceous with a slight to moderate amount of lime. The underlying soil has a coarse, sandy texture. At the onset of this study, the vineyard’s boron status was in the questionable range for deficiency. The vine’s leaf petioles and blades contained about 30 ppm boron. While the foliage had no symptoms of boron deficiency, in the past the grower had observed sticking caps and pumpkin-shaped shot berries, which are indicative of boron deficiency. During the course of the research, the vineyard was drip-irrigated from April through October. The vineyard canopy covered 60% of the land surface during summer months and about 20 inches of water was applied during the season. Boron treatments consisted of applying fertilizer in varying amounts 3 weeks prior to bloom on May 18, 1998, and then again 3 weeks prior to bloom the following year, on May 3, 1999. Growers who fertigate grapevines with a drip system generally inject material into the irrigation water over a 45-to- 60-minute period at the beginning of an irrigation set. We simulated fertigation by applying Solubor, a soluble boron product , to a shovel-sized hole beneath drippers during the first hour of the irrigation set. By doing this, precise amounts of boron could be applied to each plot and plot size could be reduced. This technique has been used successfully in previous research with other nutrients . The experiment was designed as a randomized complete block with five treatments, five blocks and five vine plots . To evaluate the rate of boron uptake and accumulation in tissue with consecutive years of fertilization, grape tissue samples were collected in 1998 and 1999 at bloom and then again about 6 weeks later during veraison. Veraison is the stage of development where berries begin to soften and/or color. To evaluate carryover, leaf tissue samples were also collected at this Tulare County site at both bloom and veraison in 2001, 2 years after the fertilization was discontinued. In each case, 100 petioles and 50 blades were sampled per plot from the center three vines. Petioles and blades were taken opposite inflorescences during bloom, and recently matured leaves were sampled at veraison. Samples were oven-dried, ground in a Wiley mill and sent to the UC Davis DANR Analytical Laboratory for analysis of total boron. Statistical analysis was by ANOVA using least significance difference to separate treatment means. A second experiment was conducted in 1998 in Fresno County near Selma, in a mature Thompson Seedless raisin vineyard planted on Pollaski sandy loam and drip-irrigated.

We describe a microscopic model, an extended Hubbard model on the diamond lattice that, within a mean field treatment, leads to this phase. The order parameter supports a number of topological defects. In particular, a vortex like line defect occurs, but with a Z2 charge. This line defect in the STI is found to be associated with a pair of gapless fermionic excitations that travel along its length. These modes are topologically stable against moderate perturbations such as impurities and interactions as long as time reversal symmetry is intact. This is the main result of the chapter – an analytical derivation is provided which relies on the properties of the Dirac equation on a two-dimensional curved surface. We now contrast our results with other recent work. In Chapter 2 we have shown similar exotic behavior also occurs in TIs, along crystal defects such as dislocations. Gapless fermionic excitations emerge there when a Z2 parameter formed by the product of the dislocation Burgers vector and three WTI indices is nonzero – which in principle can occur inboth the weak and strong TI. In contrast, in the present chapter, the fermionic modes along the line defect are solely determined by the more elusive strong index. They are absent in the case of the WTI. Thus far, the characterization of the TI phase has relied on the surface behavior. This result provides a route to identifying the strong TMI via a bulk property. Similar modes have been identified propagating along a solenoid of π flux, inserted into a STI. Here, the 2π rotation of the electron spin around the line defect leads to a Berry’s phase, plastic potting pots providing a physical realization of the π flux. Analogous phenomena occur in the context of line defects in superfluid He3-B.

In most solids where electron-electron interactions are important tend to have some degree of SOIs – which will confine the defects. Hence, we propose realizations of this physics in optical lattices of ultracold atoms, utilizing molecules with multipole moments to obtain the proposed extended Hubbard models. Realizing the three-dimensional case is more challenging, however molecules with electric quadrupole moments confined in optical lattice can realize some of the key ingredients required. This chapter is organized as the following: In Section 3.2, we will present the order parameter manifold and the line modes’ Z2 dependence on the winding number; in Section 3.3, we will justify our claim with numerical and analytical results; another texture Shankar monopole will be discussed in Section 3.4; in Section 3.5, we will establish our model Hamiltonian on a diamond lattice and show the mean field stability of TMI phases; we give two possible experimental realizations in cold atom systems in Section 3.6; we conclude the main result of this chapter in the Section 3.7. Hereafter we use σ and τ for the spin and sublattice degree of freedom, respectively. This chapter incorporates materials previously published in Ref. .An experimental realization of the TMI phase must contend with two challenges. First, the system should have weak intrinsic spin-orbit coupling, but strong interactions. Next, the further neighbour repulsion should be substantial compared to the nearest neighbor interactions. We believe these difficulties can be overcome in cold atom system, where intrinsic spin orbit couplings are irrelevant, if particles with electric multipole moments are confined to optical lattice sites. We first discuss a two-dimensional example involving electric dipoles, for which a fairly definite experimental setup can be constructed.

Although the phase realized here is two-dimensional and does not break SRS completely spin rotation remains unbroken, it illustrates how the necessary ingredients can be assembled.Subsequently we discuss ideas for realizing the three-dimensional TMI, the main subject of this chapter, using electric quadrupole moments. Two-dimensional Case: Electric Dipoles on a diamond lattice layer Dipole-dipole interactions between hetero-nuclear polar molecules, such as Rb87 and K40 have already been shown to be stron. Consider a fermionic spin 1/2 molecule, with an electric dipole moment confined to the sites of an optical lattice. We note here that the diamond lattice has a special property that if the dipole-moment is along the directions, then the nearest neighbor interaction V1 vanishes. Thus, the second nearest neighbor interaction V2 becomes dominant. However, the difficulty is that within the twelve second nearest neighbors, only interactions between neighbors within a plane perpendicular to the dipole moment are repulsive. This problem can be solved if we restrict the molecules within a two-dimensional layer of the diamond lattice , as the sites circled in Figure 3.4. Then if the dipole moment is perpendicular to the plane all possible nearest neighbor interactions are repulsive. We solve for the mean field phase diagram of this model, as was done previously for the three-dimensional case. Note, since the lattice is essentially the honeycomb lattice, this is essentially the model studied in Ref. . There exists a two-dimensional TMI phase at the center of the U − V2 phase diagram . Note this phase diagram differs from the same model in Ref. which has an extended two-dimensional TMI phase. This is because we also allow for the second nearest neighbor CDW that the authors neglected. Though frustrated, this order will dominate at large V2.One of the many advantages of Drosophila flies as model organisms for life science research has long been their benign relationship to our own species, allowing strains and transgenic stocks to be widely shared without the fear of jeopardizing either human endeavours or the natural environment.

The potential for conflict with humans was highlighted, however, following the 2008 identification of Drosphila suzukii in California. In sharp contrast to the vast majority of Drosophila species, which feed on rotting fruit and other decaying vegetation, D. suzukii, a species that is native to east Asia and had not previously been identified on the US mainland, is capable of puncturing the skin of intact, ripening fruit to lay its eggs. Over the past 5 years, D. suzukii has spread widely across North America and Europe, causing extensive agricultural damage. Today, it ranks with the lionfish infestation of the western Atlantic as one of the more severe ongoing biological invasions of the Western Hemisphere. While there has been a proliferation of recent studies on the ecology and pest management of D. suzukii , this work has often been divorced from the broader context of Drosophila evolution. The ability of D. suzukii to lay its eggs in ripening fruit has been attributed to the unusual appearance of its ovipositor, but little research has been carried out on either the morphology or evolutionary origin of this structure. The evolutionary context, however, is critical from the perspective of both basic and applied science. From the vantage point of evolutionary theory, the derived ovipositor is an example of a putative key innovation, conferring an adaptive advantage by allowing D. suzukii to exploit a new ecological niche: young, undamaged fruit that is inaccessible to the larvae of other Drosophila species. From the applied science perspective, it is critical to know the extent to which other relatives of D. suzukii could behave as pests in a similar manner, raspberry container growing in the hope of preventing their spread before they are established. Indeed, popular guides have referred to D. suzukii as ‘spotted wing Drosophila’ but this description applies to a number of flies in this species group and it is not clear how many of them are potentially harmful to agriculture. We carried out a comparative study of fruit susceptibility to D. suzukii and three of its closest relatives, and combined this work with a morphological analysis of their ovipositors. In our experiments, only D. suzukii and D. subpulchrella , the two species with ovipositors that carry enlarged bristles, punctured the intact skin of raspberries and cherries. However, while the number and morphology of enlarged bristles does not differ between these species, only D. suzukii punctured the tough skin of grapes. The shape of the D. suzukii ovipositor differs from the three other species, suggesting that changes in ovipositor shape evolved after the evolution of enlarged bristles. Our results show that D. subpulchrella could be a significant threat to the raspberry and cherry industries, while suggesting that other closely related species, including one with a spotted wing , are unlikely to be harmful.The susceptibility of four varieties of fruit to flies of four species was assayed. All flies were cultured on standard laboratory media. Bottles of flies containing pupae ready to eclose were emptied of all adults. Five to 7 days later, any adults that had emerged from the pupae were transferred to separate bottles and were aged for another 6–7 days. This process ensured that all flies were between 6 and 14 days old prior to the start of the experiment. For each experiment, three female flies of each of the four species were placed in separate plastic bottles with foam plugs, with each bottle containing one raspberry, cherry, red grape or Thompson grape. 

Only fresh fruits were used. After 24 h of exposure to the fruit, flies were removed and each fruit was analysed under dissecting microscopes by two raters. In some cases, particularly for D. mimetica, we observed that flies had died during the 24 h period. Eggs in the exposed region of the fruit were counted separately from eggs found in the intact region of the skin, inserted through punctures generated by the fly . The identification of eggs was facilitated by the presence of protruding filaments . Punctures without eggs were counted in a separate tally. In cases where the raters failed to reach a consensus, the mean value of the two counts was used. Ten to 11 simultaneous replicates of each experiment were carried out. Only D. suzukii flies laid eggs in the intact region of Thompson grapes , and these were very rare. Therefore, in order to have enough punctures with eggs to make meaningful comparisons with the punctures without eggs , we carried out a separate experiment where we placed 6–10 D. suzukii female flies per bottle. We measured the area of a total of 18 randomly selected punctures with egg filaments and compared the results to 14 punctures without filaments from the same experiment.Two strains of each of the four species were used for the morphological analysis . Ten ovipositor plates from each strain, each from a separate fly, were analysed, and the total number of bristles on each plate was determined . Some of the ovipositor bristles on D. subpulchrella and D. suzukii are modified, being enlarged and heavily pigmented. These modified bristles were counted and the location of each bristle was recorded . Outlines of the ovipositor plates were generated manually from photographs. In a manner analogous to a study of the posterior lobe of the male genitalia, a horizontalline was drawn at the base of the ovipositor plate where the pigmentation fades and the structure merges with the abdomen . The area and length to width ratio of each plate outline were calculated using the program IMAGEJ. The same program was also used to calculate puncture area and wing area . Although the flies we studied are all closely related, the ovipositors do not contain easily identifiable landmarks that are invariant across species, making it difficult to employ standard landmark-based morphometric techniques. We decided, therefore, to use elliptical Fourier analysis, which does not require the identification of landmarks. The technique uses a series of contours, described by Fourier harmonics, to approximate a shape. Each harmonic is specified by four Fourier coefficients. Following the example of previous studies, we decided to use 25 harmonics. We conducted the EFA on the distal half of the ovipositorplates , because this is the portion that comes into contact with the fruit. As it is difficult to compare outlines on a large number of Fourier coefficients , principal component analysis is typically used to reduce the data to an orthogonal set of variables ordered according to the proportion of variation explained. As the interpretation of the principal components , however, is not immediately clear, we reconstructed the outlines explained by each PC using the inverse Fourier transform . The software package SHAPE was used for the EFA and PCA.All statistical analyses were carried out using the programming language R. The fruit experiments were designed specifically to compare the susceptibility of the exposed and intact region of each type of fruit across the four species. We therefore tested the following model: number of eggs ¼ f, considering each fruit and skin condition separately.

A direct approach for identifying predators is visual identification of prey remains in predators’ guts or feces . While visual identification of prey gut contents can sometimes yield the necessary taxonomic resolution to identify insect pests, the necessary inspection labor is considerable and sampling techniques often result in high mortality rates among study subjects. Molecular identification techniques, however, offer great potential to yield insight into predator–prey interactions . These techniques often rely on targeting and sequencing a standardized DNA region across species to facilitate identifications . Applications of this approach are diverse; for example, detecting diet shifts in ancient humans , characterizing biological communities in hydrothermal vents , identifying illegal trade in endangered species , and surveying rare mammals with DNA from leeches . Similarly, molecular identification in feces,regurgitate, and stomach contents from carnivores, insectivores, and herbivores of diverse taxa has been used to infer diet . While the application of molecular diet analysis is becoming widespread, the technique is not without limitations. First, predators vary in gut retention times and digestion processes, which may affect detection rates and complicate comparisons among species . Second, DNA assays can misattribute diet in the presence of intraguild predation— that is, if the DNA of the prey of an intermediate predator is found in the fecal samples of a top predator . Finally, digestion degrades prey DNA, making fecal analysis more sensitive than other PCR procedures to DNA quantity . Despite these shortcomings, large pots plastic several studies have used molecular techniques to identify suites of pest predators, largely through DNA analysis of arthropod predators’ gut contents .

Less work has focused on vertebrate insectivores, despite their great potential to control pest infestations . Those that have studied vertebrate predators of insect pests tend to analyze single predator species rather than communities . Further, analyses have neglected the biologically diverse, tropical countries that may stand to benefit most from conservation-minded pest-management plans . We used molecular fecal analysis to identify bird predators of coffee’s most damaging insect pest— the coffee berry borer beetle . Coffee is cultivated across the tropics, with a total export value over US$20 billion and twenty million households involved in its production . The borer has invaded almost every coffee-producing country in recent years. In fact, the borer invaded Costa Rica in 2000 and our study sites in 2005. It spends the majority of its life cycle within coffee berries, overwintering in unharvested berries and undergoing a major dispersal event several months after the first rains . Previous exclusion experiments have shown that birds consume the borer, likely during the primary dispersal event or secondary movements to adjacent berries throughout the year . The borer’s small size makes directly witnessing predation unlikely . Our work builds on Karp et al. , which used exclosures to quantify bird-mediated borer control. Here, we sought to characterize more completely which species are borer predators, supplementing their analysis with an additional 961 fecal samples and 33 bird species . In addition, we verified this approach through feeding trials with three insectivorous bird species. Finally, we compiled a database of bird conservation and functional traits to make a preliminary determination of the traits associated with borer consumption and to assess whether species that important for controlling damaging insect pests are also conservation targets.

We assessed whether confirmed borer predators shared functional traits through compiling a trait database for birds in our study area, focusing on resource and acquisition traits that may affect pest-control provision . We used measurements from birds we captured, and a bird population dynamics dataset collected at 18 nearby sites . Wing chord length and mass were obtained from the population dynamics dataset. We also calculated the total number of captures for each species. We collected bill width , bill length , and tarsus length from species that we trapped during fecal sample collection. Body lengths were obtained from literature . We gathered behavioral traits from literature . We translated foraging stratum into an ordinal scale , and calculated the average foraging stratum for each species. We quantified diet breadth as the number of food categories consumed . From literature and conversations with local ornithologists , we also identified species that consumed insects and the subset that specialized strictly on insects.Ecosystem-service management necessitates identifying service providers, especially in the many agricultural systems that are rapidly expanding and intensifying . Our analysis of ~1500 fecal samples documented that six Costa Rican bird species consume coffee’s most damaging insect pest. Still, detection rates were very low: only 0.7% of analyzed samples contained borer DNA. We offer several explanations for low detection. First, we sampled the entire bird community, including frugivores which do not likely consume the borer. Second, borer abundance is low in our study system. Only 2.5% of berries across plantations are currently infested with borers, whereas infestation has soared above 90% in other countries . Third, detection windows may be narrow. We detected borer DNA in only one sample defecated within 30 min of feeding. Insect DNA could be detected in Carrion Crow feces 30 minutes to 4 hours after consumption .

Borers disperse most often and hence are most vulnerable to predation in the afternoon . Because tropical weather constraints precluded afternoon sampling, a mismatch in sampling and consumption could have depressed detections. Finally, feeding trials demonstrated that false negatives are regular. Models predicted that a positive detection was ~20 times more likely when birds were fed 8 borers and defecated 0.1 g versus 2 borers and 0.01 g. In addition to DNA degradation in the gut, our extraction and PCR procedures may be prone to false negatives. First, PCR inhibitors can persist through extraction and impede DNA amplification from fecal pellets . Second, unlike the primers developed by Jaramillo et al. , the primers that we developed were not specific to the berry borer, meaning the primers could have amplified DNA from any one of the many species of insects that a bird had recently consumed. Moreover, iterant non-specific PCR binding of either primer set could generate chimeric sequences of multiple species. Accordingly, only 10 of the 57 samples that yielded PCR products of the expected size range were identified as borer DNA after sequencing. Future work could utilize a post-PCR sorting method such as next generation sequencing or cloning to help reduce the frequency of false negatives . Low detection rates suggest that there are other species that consume the borer that we did not identify. The species we did identify, however, shared traits that may be characteristic of these other predators. All identified borer predators except the nectarivorous White-tailed Emerald were strict insectivores. Unsurprising given the borer’s size , borer predators had narrow bills. Additionally, these species had short wings, ideal for navigating the dense coffee understory . It is possible that functional traits would change with a larger sample of predators; however, confirmed borer predators in Jamaican coffee plantations shared many of these traits , supporting our hypothesis that they may help predict other predators . A key difference between our studies, however, is that only one of the species that we identified as a borer predator is migratory . We collected our fecal samples during the period of maximum borer dispersal , a time when most migratory species are absent from Costa Rica. Because migratory species could consume borers during their secondary dispersals that occur throughout the year, square planter pots future work should temporally expand sampling effort to ensure that migratory species are well represented. Our work yielded the critical management insight that managing the predators of crop pests may require looking beyond traditional conservation targets. The six documented borer predators were not rare, endemic, or listed on the IUCN red list. Traditional conservation efforts for threatened species often center on delineating large protected areas. Focusing conservation explicitly in agricultural landscapes could benefit species involved in providing critical ecosystem services to farmers . By confirming that birds consume pests, our work could thus help change attitudes towards biodiversity in human-dominated landscapes by fostering greater recognition of its role in supporting human well being. Species interactions play a pivotal role in many ecologically and economically important ecosystem processes. Uncovering the basic relationships between animals and their food is critical for managing pest control, pollination, seed dispersal, and sanitation . Molecular methods can provide us with a window into these interactions, in some instances for the very first time. Our results demonstrate how identifying just a few key interactions between predators and their prey can yield potential insights for management. Indeed, managing nature to enhance both biodiversity and human wellbeing requires diverse approaches.

Techniques and practices have already been borrowed from fields as diverse as agronomy, economics, hydrology, psychology, and sociology. Our results indicate that molecular biology offers ecologists the ability to expand their toolkit in key dimensions and, in turn, advance ecosystem service management.California is the leading producer of table grapes. In 2019 table grapes accounted for 130,000 acres of the 918,000 acres of grapes grown in the state, with 6,588 acres grown with the variety Redglobe . The cultivar Redglobe is a variety popular for export markets, including China and Mexico, because of its flavor and long shelf life . Brown spot can cause major post harvest fruit loss in Redglobe and other late-harvest cultivars such as Crimson Seedless and Autumn King . No reliable control of brown spot has been found. A study by Swett et al. showed 100% of Redglobe clusters collected from a commercial field in Delano, in the San Joaquin Valley, had latent infections of Cladosporium species responsible for brown spot disease. Redglobe clusters may be stored for 2 to 3 months before they are shipped to Asia. When symptomless berries are in cold storage conditions for long periods, brown spot disease begins to emerge and spread . While initial infections occurin the field, once in post-harvest, infection can also easily spread from berry to berry through epidermis contact with no wounding necessary and in temperatures as low as −2°C . Attempts to manage brown spot have relied on strategies developed for the control of gray mold, a severe post harvest disease caused by the fungus Botrytis cinerea . Gray mold and brown spot have similar biology, such as infection timing, occurrence of a latency period and timing of symptoms expression . However, the common practice of using 100 to 200 parts per million per hour sulfur dioxide treatments used to control gray mold during cold storage and during transport has not been effective for the control of brown spot . Brown spot has been attributed to several species of the Cladosporium herbarum species complex and C. cladosporioides . As described by Swett et al. , typically a fluffy, light green to white mycelial mat will form where infection has taken place on the berry epidermis. A mycelial callus can form under the epidermis as a result of an internal infection, creating a scab and a brown spot on the underside of the epidermis. As the infection progresses, the scab will encompass the seed of the grape, forming a fungal fruiting body that eventually replaces the grape seed placenta, and prolific sporulation will occur on the seed . In the last 20 years, a total utilization technique for fumigant applications of SO2 during cold storage has been established for table grapes; it increases efficiency, reduces environmental pollution and protects operators . An important step of the technique is to apply the first SO2 treatment during the initial forced-air cooling of the grapes after harvest, which is then followed by weekly applications during cold storage with homogenous air distribution . The total utilization technique system uses ~ 10 times less SO2 than the previous standard fumigation system, but it requires uniform room air distribution for the treatment to be effective . The total utilization technique was based on laboratory studies that revealed that at least 100 ppm-h SO2 was necessary to kill B. cinerea conidia and inactivate exposed mycelia at 0°C . Even less than 100 ppm-h was effective at warm temperatures to cause the death of conidia and mycelium of B. cinerea on grape . These latter studies confirmed that SO2 applied at 200 ppm-30 min, 400 ppm-15 min, 50 ppm-2 h or 25 ppm-4 h was as effective as the 100 ppm-h treatment .

The wines made from control and sort treatments are more closely associated with each of the significant attributes; this trend generally matches the results from the chemical analyses. Both the wines made from control and sort treatments were higher in ethanol content, which can explain their greater association with “alcohol hotness” when compared to reject treatment wines. It is possible that the higher ethyl ester concentration in the control and sort treatment wines could explain why they are rated significantly higher in the “apple” aroma. Most ethyl esters have fruity aromas which the judges could have rated as “apple”. Curiously, the control and sort treatment wines are rated significantly higher in “sweet” as well despite the residual sugar content of all wines being less than 1 g/L , which is below the sensory threshold . All three significant attributes for the CS panel were rated similarly between control and sort treatment wines. This suggests that these wines made from these treatments had similar sensory properties.Analysis of wine color revealed that there were perceivable differences among treatments for all three varieties . For BA the reject treatments were rated lighter in color compared to the control and sort treatments, whereas a similar trend was observed in the CS treatments. This was expected because berries with less color were removed by the optical sorter and included in the reject fermentations. This agrees with results from Table 6; the rejected treatments were significantly lower in anthocyanin content for BA and CS, plastic gutter which can explain the difference in color perception. For GN wines, the control treatment was perceived to be slightly darker than the sort and reject treatments.

Although fermentations were prepared to have similar solid-to-juice ratios in the must among treatments, it is possible that variations between replicates may have resulted in the control treatments being slightly more concentrated, which could provide an explanation for this result. Color perception from the panelists matches well with the wine color determined in the CIELAB color space . It can be concluded that optical sorting was generally successful in removing berries with less color; however, this did not lead to a large difference in the final color of the wines between the sort and control treatments.Multiple Factor Analysis was performed for each variety using all sensory attributes and only volatile compounds that differed significantly among treatments . This was done to observe the association, if any, of the significant volatile compounds and sensory attributes. For GN wines, the only significant attribute was “SO2”. From Figure 7, isobutanol, which can impart a solventlike aroma in wine, is grouped closely with “SO2”. It is possible that wines with a higher isobutanol concentration were perceived to be higher in “SO2” aroma. For BA wines, there does not appear to be a trend among sensory attributes and volatile compounds . For CS wines, “apple” is grouped closely with ethyl esters , which provides evidence that this may have caused the increased perception of this attribute in the control and sort treatments .Overall, optical sorting had minimal impact on the sensory properties of the three varieties tested. It is possible that the chemical differences noted earlier were too small to result in consistent differences by descriptive analysis.

Even though the wines made from reject material contained significantly higher concentrations of higher alcohols, it did not result in a difference in sensory perception. Higher alcohols have a relatively high sensory threshold . It is possible that the concentration of these compounds in the reject wines was below the sensory threshold.The purpose of this study was to determine what effects, if any, optical berry sorting had on wine made from different red grape varieties, and to investigate the potential to use optical sorters to sort for different ripeness levels using color as a main criterion. Given the observed differences in Brix and final ethanol content, optical sorting seemed to be successful in removing underripe berries for CS and possibly for BA; however, this did not result in a significant difference in the final ethanol content between the sort and control treatments. The removal of underripe berries was also evident by the difference in color among treatments. For BA, the rejected treatments were significantly lighter in color; however, the color of the sort and control treatments was very similar, whereas a similar trend was observed in the CS treatments. Wines made from GN generally did not follow these trends; possibly because sorting parameters were too aggressive for this cultivar, resulting in a high percent rejection of optimal berries. This may have minimized potential differences between reject wine with the other treatments. Another possibility is that color differences in the GN fruit did not correspond to differences in sugar content. From these results, it may be concluded that, when using color as a criterion, optical sorting based on ripeness level was successful but may be dependent on variety and fruit variability. Additionally, the impact on the resulting wine is likely dependent on the initial variability in grape ripeness.

The optical sorter was successful in removing MOG. Thisresult was reflected in the phenolic analyses; reject treatments were generally higher in total phenolics and tannin, most likely due to the greater proportion of MOG included in the must. The decrease in anthocyanins is likely due to the higher percentage of green, underripe berries in the reject treatment musts. A study that made wine with the addition of MOG found that this addition significantly increased the phenolic and tannin content in the resulting wines. Despite the differences observed in the phenolic composition of the reject wines, the control and sort treatments were very similar for all three varieties. This is in contrast with some previous studies that have found wine made from optical sorted fruit had significantly different levels of phenolics. One study found that optical sorting led to wines with higher levels of total phenolics. It should be mentioned that the researchers here did whole cluster pressing for their control wines , whereas the sorted wines were destemmed. It is possible that higher levels of phenolics were extracted due to the damage caused by the destemming process on the seeds and skins. Another study found that wine made from optically sorted grapes that were machine harvested generally had lower levels of phenolics; levels that were similar to the same wines made from a handpick treatment. Given that the rejects were, in general, significantly higher in total phenolics and tannin than the control and sort treatments, it can be suggested that optical sorting has the potential to decrease the phenolic content in wine; however, there was not enough MOG to show a large impact in the current study. Optical sorting likely has a greater impact on mechanically harvest fruit due to generally higher levels of MOG observed from this harvest method. Some differences were found among treatments in the aroma profiles of the wines. Few compounds differed significantly between sort and control treatment and, in general, the reject treatments had greater concentrations of higher alcohols and control and sort treatments had greater concentrations of ethyl esters. The higher ethanol content of the sort and control treatments as well as their lower pH can lead to a higher production of esters. In general, blueberry container reject treatments contained significantly more suspended solids then the control and sort treatments for all varieties studied. Research has shown that high levels of suspended solids during fermentation can lead to greater production of higher alcohols. Descriptive analysis indicated only one significantly different attribute among GN treatments and only two significantly different attributes among BA treatments. BA control and sort wines were associated with the “alcohol” descriptor which correlated with the higher ethanol levels in these treatments compared to the reject treatment. Similarly, there were only three significant attributes among the CS treatments. “Alcohol hotness” related to ethanol content as previously described. The control and sort treatments were also rated significantly higher in “apple” and “sweet” aromas compared to the reject treatment. Some studies have shown that higher levels of ethanol can increase the perception of sweetness in a wine. However, as King et al. noted, there is disagreement in this regard, as other studies have shown that ethanol content can either decrease or have no effect on the perception of sweetness. Thus, this may not be a sufficient explanation as to why the control and sort wines were rated significantly higher in sweetness. Perhaps the higher concentration of total phenolics and tannin in reject wines could explain the difference given that phenolics in wine contribute to bitterness and astringency. From the PCA in Figure 6, it can be noted that “bitter” and “drying” are more associated with reject wines. Although these attributes are not significantly different among the treatments there appears to be a trend which could impact the perception of sweetness. One study found that increasing bitterness in coffee decreased the perception of sweetness. It is possible that reject wines were rated lower in “sweet” due to the higher concentration of phenolic compounds thus decreasing the perception of sweetness. The higher perception of sweetness in the control and sort wines may also be attributed to the higher intensity of the “apple” aroma, which the judges could have associated with a sweet taste.

One study found that retronasal aromaperception of fruity compounds increased with an increasing level of sweetness in a model wine solution. The authors also noted several other studies which found that aroma compounds can enhance the perception of sweetness in different foods and beverages. Another study found that samples described as “fruity” were also often associated with a “sweet” aroma. This provides further evidence that the judges in the current study may have associated these attributes together. The overall sensory differences were minimal, and the wines were determined to be similar. The results from this study largely agree with results from previous studies investigating the effects of optical sorters. It is possible that there was not enough variation in the starting material of the current study for optical sorting to have a large impact. Optical sorters may be used to greater effect during vintages with inconsistent ripening, issues with raisining, or large amounts of berry damage, possibly caused by either birds and/or fungal infections. Future research should investigate the impact of optical sorters in these scenarios.Grapevine has indeterminate growth habits compared to other perennial fruit crops. Latent growth of the dormant grapevine bud may be induced by favorable conditions with little to no dormancy period required . Therefore, semi-tropical regions may raise two crops a year, and in fact, it is not uncommon for the latent bud to produce some fruit when correlative inhibition is removed in temperate regions. Furthermore, the grape berry does not have the same fruit abscission mechanism as apple or peach revealed under carbon starvation. It is therefore possible for grapevine canopy size and crop level manipulations leading to a wider range of source or sink limiting conditions within a growing season. The number and size of the flower primordia is associated with number of clusters and berries per cluster through the formation flowers and fruit set . However, fruit set is largely variable among years, weather, location, and cultivars . Poor fruit set may be a limitation to crop yield, although weather is often considered to be the leading cause. However, the mechanism of poor fruit set is not fully understood. Carbon supply or mineral nutrition are related to the amount of fruit set , which is an acclimation mechanism to unfavorable conditions. Ultimately, yield of grapevine is affected by berry size, and within the berry, pulp enlargement is the largest contributor to yield gain rather than skin or seed biomass . Conversely, vegetative growth is far less influenced by latent bud formation, as competition amongst growing buds tends to buffer the impact of growing shoot tips on its length and total leaf area . This is likely due to the great limiting effect of nitrogen among other nutrients or hydraulic pressure . The ratio between leaf area and fruit mass is closely related to the amount of carbohydrates accumulated in the must . Thus, an excessive crop level or less than ideal canopy size may result in over cropping and may lead to delayed ripening .

The four others were an autophagy gene and constitutively activated cell death 1 , which function in autophagy, lytic pore formation, and HRs , Kinesin-like 5C , which encodes a microtubule motor protein , and an ARF-GAP encoding ADP-ribosylation factor GTPase-activating protein domain 15, which helps efficiently load vesicles and remodel the actin cytoskeleton . Several additional general functional categories were present among the 32 genes that exhibited conserved responses to GLRaVs . Genes encoding phenylalanine ammonia-lyase and cinnamate 4-hydroxylase , which catalyse the first two steps of the phenylpropanoid pathway, two genes encoding UDP glucosyltransferases , which conjugate sugars, and SWEET17, encoding a sugar transporter, were upregulated, as was a gene encoding 3-isopropylmalate dehydratase, an enzyme in the leucine biosynthetic pathway. Two genes, encoding an LRR receptor-like kinase called ERECTA and nicotianamine synthase , were downregulated. ERECTA participates in organ development and resistance to bacterial and fungal pathogens . NAS expression increases Fe and Zn abundance in rice . Generally, these genes and their changes in expression suggest that a common response to GLRaVs in Cabernet Franc berries during ripening includes the modulation of pathogen-detecting genes, an increase in ABA transport and signalling, a decrease in ROS-related signalling, and an enhancement of cytoskeleton remodelling, vesicle trafficking, phenylpropanoid metabolism, sugar transport and conjugation, and leucine biosynthesis.The same berry samples used for RNA-Seq were used to measure the levels of three hormones associated with ripening and/or stress, including SA, JA, and ABA, and additional metabolites, square plastic plant pot including xanthoxin, a precursor to ABA, and ABA glucose ester , a conjugate of ABA implicated in its long-distance transport .

The mean levels of SA and JA were significantly influenced by year and/or by interactions between year, rootstock, and GLRaV at prevéraison , but no significant differences were observed between individual groups . In contrast, year alone had a significant impact on the levels of ABA and related metabolites measured at each developmental stage, but largely did not interact with rootstock or GLRaV infection type to affect the abundance of ABA and related metabolites . In addition, the effect of GLRaV infection on ABA and ABA-GE content significantly differed based on rootstock . Significant differences in ABA and ABA-GE content were observed between rootstocks in plants with identical infection status and between plants with different GLRaV status grafted to the same rootstock . Such differences were scarcely observed for xanthoxin, a precursor to ABA . Significant differences between rootstock genotypes in the abundance of these metabolites were observed most at prevéraison and in GLRaV , GLRaV-3 , and dual infections . In GLRaV and most single infection conditions, the levels of all three metabolites tended to be higher in berries from plants grafted to MGT 101-14 than in berries from plants grafted to Kober 5BB. The opposite tended to be true when two GLRaVs were present. With one exception, significant changes in the abundance of ABA and ABA-GE in GLRaV versus GLRaV were typicallyto cluster separately from other Kober 5BB-grafted plants. Nonetheless, the effects of GLRaVs differed between rootstocks for many of these genes . One of these, encoding an ABC transporter , is also included in Figure 3; significant increases in its expression were observed in both years, in both rootstock conditions, and for several GLRaV infections. All other significant changes in GLRaV versus GLRaV that were reproduced in both years occurred in only one rootstock or the other.

These changes were sparse. However, significant differences between rootstocks in identical GLRaV were reproduced in both years for 9 out of these 19 genes. Significant differences between rootstocks in at least one year were observed for 16 out of these 19 genes. On average, three genes encoding 9-cis-epoxycarotenoid dioxygenases , both ABA 8′-hydroxylase genes, three ABC transporter genes, one gene encoding PP2C, and PYL/RCAR were upregulated in berries from plants infected with GLRaV in both rootstock conditions. One ABC transporter gene was downregulated in both rootstock conditions. Of the remaining eight genes, most were downregulated across development only in berries from MGT 101-14-grafted plants.Differential expression analysis identified 1,809 genes that were differentially expressed in at least 1 year, that were differentially expressed in only one rootstock condition and more than one GLRaV infection type versus GLRaV , and/or for which the effects of more than one GLRaV infection significantly differed between rootstocks . RNA-Seq, hormone, and metabolite data from ripening Cabernet Franc berries were integrated in a multiple factor analysis to relate these variables and distinguish the effects of GLRaVs given different rootstocks . As input for the MFA, all genes differentially expressed between GLRaV and GLRaV or between rootstocks were used, plus all hormones and metabolites measured. Overall, the rootstocks were distinct at each developmental stage . Some of the GLRaV conditions could be distinguished from others at prevéraison, véraison, and harvest. At prevéraison, GLRaV-1,2 differed overall from GLRaV-1 . At véraison, GLRaV-1,3 differed from every other GLRaV condition except GLRaV-1,2 . At harvest, the two dual infections were different than one another and GLRaV-1,2 differed from GLRaV-1 . Next, we identified which variables were best correlated with each rootstock-differentiating MFA dimension. At eachdevelopmental stage, ABA and/or ABA-related metabolites were correlated with at least one of the first two MFA dimensions .

The rootstock-dependent disparity in ABA levels and ABA-related gene expression is consistent with the observation that ABA and related metabolites tended to be highly correlated with rootstock-differentiating MFA dimensions over time and that ripening initiates earliest in Kober 5BB plants with dual infections in terms of TSS . There were 548 genes that shared high correlation to rootstock-differentiating MFA dimensions with hormones or hormone-related metabolites. Most of these genes had shared positive or negative correlations to the same dimensions as ABA, xanthoxin, and/or ABA-GE . Categories of genes with functionally relevant relationships to each hormone or hormone related metabolite were over-represented among the genes that shared high correlation to rootstock-differentiating MFA dimensions with each hormone. ABA signalling, starch biosynthesis and catabolism, and C2C2-DOF transcription factor-encoding genes were over-represented among the genes correlated to the same dimensions as ABA and xanthoxin. The latter two categories were significantly over-represented among the genes correlated with the same dimensions as ABA-GE. Genes related to heat shock protein -mediated protein folding, chaperone-mediated protein folding, the cation channel-forming HSP-70, channels and pores, the reductive carboxylate cycle, and carbon fixation were over-represented among those correlated with the same MFA dimensions as SA. Similarly, most ripening-related metabolites measured were correlated with the same MFA dimensions as ABA, xanthoxin, and/or ABA-GE . Overall, the effects of GLRaVs differ between rootstocks primarily in terms of ABA and related metabolites. This finding is especially salient because of the role that ABA plays as a ripening promoternear véraison, in root–scion communication, and in plant stress. ABA, metabolites, and genes that were well correlated to rootstock differentiating MFA dimensions and were differentially expressed were scrutinized more closely.There were 548 genes in 85 functional categories that were well correlated with rootstock-differentiating MFA dimensions and differentially expressed between GLRaV grafted to different rootstocks or in GLRaV versus GLRaV in only one rootstock condition . These functional categories were generally related to hormone and other types of signalling, amino acid and other metabolic pathways, transcription factors, transport, and cellular organization and bio-genesis . Most of these genes coincided with ABA and related metabolites along rootstock-differentiating MFA dimensions . The distribution of expression for four transcription factor families differed significantly between rootstocks at all four developmental stages . This included bHLH, C2C2-DOF, FHA, 25 liter sqaure pot and homeobox domain transcription factors. The distribution of expression of 39 hormone signalling related genes differed significantly between rootstocks . This was true at each developmental stage for ABA, gibberellin , and auxin signalling genes and at three developmental stages for JA/SA, cytokinin , and ethylene signalling genes . Genes related to all of these hormone families had similar roles in MFA and were associated with ABA, including the JA/SA signalling genes .

This may reflect interactions between hormone signalling pathways. In addition, the effects of GLRaV infections on histone H1 expression were not equal in plants grafted to both rootstocks . Linker histone H1 contributes to higherorder chromatin structure . There were seven ABA signalling pathway genes that differentiated GLRaV effects in plants grafted to different rootstocks . This included SOS2, KEG, three PP2C genes , and two genes encoding ABA-responsive element -binding proteins . SOS2 is a kinase appreciated for its role in the salt stress response, seed germination, GA signalling , and ABA signal transduction via its interaction with ABI2 and ABI5 . SOS2 was upregulated in both rootstock conditions before and at véraison and downregulated after véraison. KEG is a negative regulator of ABA signalling; it maintains low levels of ABI5 in the absence of stress by ubiquitination and degradation and helps regulate endocytic trafficking and the formation of signalling complexes on vesicles during stress . KEG was downregulated in Kober 5BB and downregulated in MGT 101-14 at véraison and mid-ripening. In the presence of ABA, ABA receptors bind PP2Cs like HAB1 and AHG3 to inhibit their phosphatase activity. As a result, ABA signal transduction is permitted via SnRK2 phosphorylation of ABRE-binding proteins . ABI5 and AREB2 are bZIP transcription factors that bind to ABREs to drive ABA signalling and ABI5 can integrate signals across hormone signalling pathways . The effects of GLRaVs on these genes in Kober 5BB were consistent with an enhancement of ABA signalling during ripening. In Kober 5BB, HAB1, AHG3, AREB2, and ABI5 were upregulated. In MGT 101-14, the PP2Cs were downregulated at two or more developmental stages; AREB2 and ABI5 were upregulated at and after véraison.In addition to analysing hormones and hormone-related metabolites, we analysed metabolites associated with the shikimate, phenylpropanoid, and flavonoid pathways and their biosynthetic and regulatory genes in Cabernet Franc berries during ripening . Significant differences in expression versus GLRaV were detected, as well as significant differences in the effects of GLRaV infection between different rootstock conditions . The effects of GLRaV infection on the genes associated with this pathway were generally consistent with the change in abundance of corresponding metabolites . Overall, these genes tended to be upregulated in GLRaV at véraison . After véraison, the amount of upregulation tended to decrease, or genes were downregulated . The three amino acids examined tended to be less abundant in GLRaV across the developmental stages and the largest decreases were observed at harvest . Mixed effects of GLRaVs were observed on the abundance of hydroxycinnamic acids , t-resveratrol, and anthocyanins. Significant changes versus GLRaV tended to occur in only 1 year. During ripening, these were significantly more abundant in Kober 5BB GLRaV-1,2 , Kober 5BB GLRaV-4 , and/or MGT 101-13 GLRaV-3 . Significant decreases were observed for GLRaV-1 and GLRaV-1,3 . Though nonsignificant, the size of the downward effect of some GLRaV infections on these metabolites tended to increase towards harvest. Finally, flavanols and flavonol glycosides tended to be elevated in GLRaV . The size of this effect tended to be greatest before and at véraison and decreased towards harvest. Significant differences between rootstocks were observed for GLRaV-1,2 in both years and for GLRaV-1 , GLRaV-1,3 , and GLRaV-3 in individual years;the increase in flavonols and flavanols tended to be greater in berries from Kober 5BB GLRaV than in those from MGT 101- 14 GLRaV .GLRaVs affect viticulture on nearly every continent and can a have considerable economic impact on a major crop. The presence and severity of symptoms in GLRaV infected grapevines is influenced by host genotype, rootstock, which GLRaV is present, and environmental conditions. In addition to the assembly and annotation of the Cabernet Franc genome, a valuable resource that might be applied for the larger purpose of understanding grapevine genomic diversity and evolution, the dedicated experimental vineyard used in this study is a tremendous asset for the study of GLRaV infections over time in a common environment. This work identified responses to GLRaVs in grape berries during ripening, including those that are conserved across experimental conditions and responses that differ based on the rootstock present. We propose which hormones and signalling pathways at least partially govern the responses observed and likely influence leafroll disease symptoms. The effects of dual infections, particularly GLRaV-1,2 , were most distinctive.

The same procedure executed for the 2018 cultivar experiment was used to calculate and re-inoculate the pots. Field grafting experiment. Field experiments were performed in a commercially-owned field south of Bakersfield, Kern County, CA. The field has historically been under consistent tomato production and typically experiences southern blight. The soil was a sandy clay loam with a pH of 6.37 and 2.19% organic matter. In 2017, the preliminary field experiment evaluated two cultivars under two graft treatments that were mechanically transplanted on May 15, 2017. Plots were 165 m long with 30.4 cm plant spacing and were arranged in a randomized complete block with 7 replications. Plants were irrigated with a buried drip system at a depth of 26 cm. The field experiment in 2018 and 2019 evaluated the same treatment structure as the 2018 and 2019 greenhouse experiments. The field experiments consisted of treatments arranged in a randomized complete block design with 6 replications with plots that measured 34 m long in 2018 and 30.5 m long in 2019. In both the 2018 and 2019 field trials, the plants were mechanically transplanted at a spacing of 60.9 cm in single row beds. Transplants were established with a towed water tank or sprinklers , then irrigation was switched to drip. Although not located within an active production field, the experiments were maintained by the commercial grower using standard practices for processing tomato in the southern San Joaquin Valley. Data Collection. In both the cultivar and grafting greenhouse experiments, Southern blight severity was rated using the following 0 to 7 ordinal rating scale: 0 = no disease symptoms; 1 = chlorosis of the older leaflets; 2 = wilting of the older chlorotic leaflets; 3 = wilting of the older leaves with a wilted apex; 4 = necrotic older leaflets with a wilted apex, black plastic plant pots and apex leaflets showing chlorosis; 5 = all leaflets are dry; 6 = all leaflets are wilted and dry with a chlorotic stem; and 7 = a dead plant that is completely wilted and dry .

Data was collected weekly after southern blight symptoms began to develop for the greenhouse cultivar experiments in 2018 and 2019. For the grafting greenhouse experiments, disease severity was rated every 2 weeks after southern blight symptoms began to develop for the 2017 and weekly for the greenhouse graft study in 2018 and 2019. For the field trials of objective , in 2017 data was collected weekly beginning six weeks after planting. Strike counts, defined as plants observable as infected or not infected, were collected from four 15.2 m sections per plot in the 2017 field trial. In the 2018 and 2019 trials, data collection began two and five weeks after transplanting after transplanting, respectively, and approximately every one to two weeks thereafter. In these trials, the status of each plant was individually recorded on each rating date. Plants that were wilting, collapsed, and lime-colored were rated as exhibiting southern blight symptoms . Other diseases were also observed in these trials. Plants with crisp leaves that roll or curl upwards with or without appearing stunted were rated as symptomatic of curly top, and plants with crinkled leaves having interveinal yellowing and typically with stunted growth were rated as symptomatic of unknown virus. Plants completely brown and dry were rated as dead. When a dead plant was observed, it was marked with a flag to ensure it would be counted on subsequent rating dates. Yield data was collected from 165 m long plots from the 2017 field trial on September 18, 2017. Yield data was not collected in 2018 due to quick collapse of plants ending in poor fruit quality for harvest. Yield data was not collected in 2019. Data Analysis. For the 2018 and 2019 cultivar and grafting trials in the greenhouse, the influence of experimental factors on southern blight severity was analyzed with generalized linear mixed models with PROC GLIMMIX in SAS 9.4 using the multinomial distribution and the cumulative logit link function.

The cultivar trial was analyzed as a nested model, with inoculum as a main effect and inoculum × cultivar as an interaction effect, because only a small set of the cultivars were evaluated in noninoculated control plots. The grafting trial was analyzed as a factorial. For both trials, rating date was included separately as an additional main effect and not included as an interaction to reduce complexity of attempting to model ordinal data. Block was included as a random effect for both trials. When interactions were significant, the effect of cultivar within inoculum and the effect of graft within cultivar were examined with the slice statement for the cultivar and grafting trials, respectively. Levels of significant main effects or interactions were separated by obtaining odds ratios for all pairwise comparisons with the model statement. Due to the large number of treatments in the cultivar study, odds ratios were summarized with the lsmeans statement in PROC PLM with the Tukey-Kramer adjustment for multiple comparisons. In the cultivar trials, the effect of cultivar among inoculated plants was analyzed using a dataset with noninoculated cultivars removed because odds ratios cannot be determined for interaction terms. Initial analysis of the greenhouse grafting trials did not detect statistical evidence for an effect of inoculum despite a total lack of symptoms in control pots, therefore all non-inoculated pots were removed for analysis. In addition, initial analysis of the 2019 cultivar trial did not find statistical evidence for separation of cultivars despite clear variation in the raw data. Therefore, three cultivars which possessed all 0 ratings on all dates were excluded from analysis. For the 2018 and 2019 field trials, individual plant status data was first subjected to quality control. In some cases, the same plant was rated with more than one disease over the course of each trial. This was generally due to lack of clarity of the symptoms when they are first observed or a secondary disease affecting plants following the first.

Quality control consisted of assigned the true or primary pathogen retroactively to all symptomatic ratings. Then, for dead plants, the cause of death was determined from ratings on previous dates when the plant was symptomatic but alive. Following quality control, ratings were summarized at the plot level. The total number of plants in each plot with a given rating was determined, and southern blight incidence was determined by adding the number of plants exhibiting southern blight symptoms and the number of plants dead due to southern blight. The influence of cultivar, graft, rating date, and all interactions on southern blight incidence in the 2018 and 2019 field trials was analyzed with a generalized linear mixed model in PROC GLIMMIX with the binomial distribution and the logit link function. Block was included as a random effect. The effect of graft within significant cultivar × graft interactions was examined with the slice statement. Means of significant main or sliced effects were separated using the least significant difference test with Tukey-Kramer adjustment for multiple comparisons with the lsmeans statement. For the 2017 field trial, yield and strike count data were analyzed with PROC GLIMMIX procedure in SAS v9.4 using the log normal and binomial distributions, respectively. The 2017 greenhouse experiments were analyzed as relative treatment effects with repeated measures using the nparLD package v2.1 in R v3.3.2 . An analysis of variance -type statistic was used to determine the effect of treatment, black plastic planting pots and means will be separated using 95% confidence intervals calculated from the nparLD package.Cultivar greenhouse experiment. By the end of the experiments, some inoculated plants from almost all cultivars had died from southern blight, but many plants did not develop any symptoms . The raw data showed that cultivars differed primarily in the number that did not develop any symptoms and that most died after exhibiting disease symptoms. One cultivar in 2018 and three in 2019 did not develop any symptoms. No symptoms were observed in any non-inoculated plants. In both trial years, analysis of fixed effects showed that the interaction of cultivar and inoculum had a significant effect on disease severity, and slicing these interactions showed inoculum of 10 sclerotia per 100 cm3 of soil had an effect on disease severity . There were few differences among cultivars in the multiple comparison analyses in both years, and relative differences among cultivars varied between years . In 2018, HZ 4707 had the lowest risk of developing disease, but was not different from SUN 6366, HZ 1428, and N 6428. In 2019, risk of both HZ 4707 and HZ 1428 was relatively low but was similar to several commercial cultivars and Texas A&M breeding lines. In contrast, N 6428 had the highest risk in 2019 but was not significantly different from six other cultivars. Cultivar N 6416 had the highest risk in 2018 and relatively high risk in 2019, but was not different from 9 or 12 other cultivars, respectively. Although Maxifort and Multifort were included as positive controls in 2018, their risk of developing southern blight was similar to all but 1 and 4 of the remaining cultivars,respectively. Of the Texas A&M breeding lines that were not excluded from analysis in 2019, 5635M and 5913M exhibited the least risk, but were not significantly different from the two remaining breeding lines and 8 commercial cultivars.

Grafting greenhouse experiments. The preliminary 2017 study showed under moderate inoculum pressure, disease severity was significantly higher in non-grafted HZ 5608 compared to HZ 5608 grafted to Maxifort, but was similar for H 8504 grafted and non-grafted . Disease severity was low in both 2018 and 2019 experiments. The Type III analysis of fixed effects detected a significant effect of grafting on disease severity in 2018 and 2019 . However, odds ratio estimates and confidence intervals of the pairwise comparisons control-standard and standard-tall were not sensical , and the control-tall comparison suggested that control had significantly greater odds to develop disease in 2018 but significantly lower odds in 2019. HZ 5608 had numerically higher incidence of southern blight compared to HZ 8504 for both replicate trials in inoculated pots across all grafted treatments , however a statistical effect of cultivar was not detected in either experiment. Field grafting experiment. Disease incidence was significantly lower on four of five rating dates in grafted plots compared to non-grafted in 2017 . On the final rating date, southern blight incidence was 52% and 58% lower in grafted compared to non-grafted plots. A significant effect of grafting was observed on yield, in which yield was 30.0% higher in grafted plots compared to non-grafted . In 2018 and 2019, disease severity was moderate to high . The Type III analysis of fixed effects on the 2018 field trial showed a significant interaction of cultivar and grafting on disease incidence, whereas in 2019 only the main effect of grafting was significant . For both cultivars in 2018 and in 2019, disease incidence was significantly lower in grafted plots regardless of height when compared to the non-grafted control. Mean incidence in non-grafted plots was approximately 7.5 and 11.5 times higher in 2018 and 2019, respectively, when averaged over cultivar and height of the graft union. Additionally, for HZ 8504 in 2018, incidence in tall grafted plots was significantly lower than incidence in standard plots . This numeric trend was also observed for HZ 5608 in 2018 and in 2019, but the difference was not significant.This study presents options for the management of southern blight of processing tomato in California. We found that grafting to resistant rootstocks dramatically reduced southern blight in processing tomato. Our finding agrees with previous literature on the benefit of grafting for management of southern blight and other diseases. In addition, our results suggest that raising the height of the graft union may reduce southern blight incidence. Finally, we observed variation in susceptibility to southern blight among commercial cultivars currently planted in California.While our findings in processing tomato agree with previous research in fresh market tomato, the utility of grafting to processing tomato production may be lower due to the relative costs and returns between the two systems. Although we did not perform a comprehensive economic analysis of production using grafted transplants, the current cost of F1 hybrid seed and the grafting operation exceeds returns under reasonable price and yield scenarios.

Maturation of coffee cherries is slow, with immature green cherries taking up to 240 days to develop into red, ripe fruit that is ready for harvest in mid-October through January . After harvest, coffee plants are left to recuperate until flowering is initiated again the following year by the next onset of rain.Following the coffee flowering period and initiation of cherry growth, adult female CBB emerge and disperse via flight in search of new cherries to colonize . Timing of emergence appears to be driven primarily by relative humidity and temperature, with dispersal peaks occurring around the end of the coffee harvest, from December through March . Females begin ovipositing in chambers carved out of the coffee endosperm roughly 120–150 days after coffee flowering, when the dry content of the seed is 20% or higher . It is this dispersal period, and subsequent drilling into the coffee cherry, when CBB are vulnerable to predation by birds, as the remainder of the CBB life cycle occurs within the coffee cherry. There are five main CBB developmental stages: egg, larva, pupa, juvenile, and adult. Females can oviposit daily for up to 40 days, averaging 1–2 eggs per day . After a week, eggs hatch and larva take 17 days to develop into pupa. Following pupation , juveniles emerge and reach sexual maturity after about 4 days . The length of the CBB life cycle can be slowed and accelerated depending on average temperature ; the developmental times used here are based on 25 C rearing conditions . Offspring sex ratio is skewed toward females, ranging from 1:5 to 1:494 . Since males are flightless, mating occurs between siblings within the natal cherry.

Fertilized females then disperse to colonize other cherries, though multi-generational oviposition within the natal cherry is possible. The prolonged maturation of the coffee crop allows continual reproduction, drainage planter pot with 2–8 CBB generations feasible in a single season if environmental conditions and food availability be favorable . With the removal of cherries during harvest, adult CBB will enter diapause in coffee cherries that remain on the plant or fall to the ground .Since birds do not eat coffee cherries, bio-control by birds would only occur during the brief dispersal period when CBB are vulnerable. There is a rich bird community during this period of time as both resident and migratory birds are present . Neotropical migrants are potentially more abundant on coffee farms than resident species that may prefer forest habitat due to higher prey abundances . Many migratory warbler species of the Setophaga genus that frequent coffee farms have been confirmed as CBB predators, as have resident bird species such as the rufous-capped warbler and common tody flycatcher  Overall, insectivorous birds are the most abundant on coffee farms and hold great potential as bio-control of many insect pests . Details on bird densities on Costa Rica coffee farms used in the model are expanded on below .We created a deterministic Leslie matrix for coffee berry borers with one-day time steps using data reported by Mariño et al. for an artificially infested coffee farm. Mariño et al. estimated the amount of time in each life stage , each of which had a narrow window, and calculated transition probabilities between stages. We converted each of the stage transition probabilities into daily transition probabilities as Gi 1 d, where d = the number of days in a life stage.

We assumed that mortality was evenly distributed across days within each life stage. Similarly, fecundity estimated by Mariño et al. for a seven-day period was converted to daily egg laying rate, assuming eggs are produced at a constant rate. To account for the female skewed sex ratio, the new daily Fi was multiplied by 0.9 to model a conservative 10:1 F:M sex ratio. Lab experiments show fecundity decreases when multiple ovipositing females cohabitate . However, it is rare to find a cherry bored by more than one female, likely due to the high abundance of coffee cherries in the field. Therefore, we assumed density-independent growth. Since all developmental stages of CBB occur within the coffee cherry and are assumed to be protected from predation by birds, we added a dispersal life stage to the population growth matrix, and limited bird-related mortality to this life-stage. The dispersal life stage includes the time a gravid adult female emerges from the natal cherry, disperses via flight, and the initial stages of boring into a new cherry to oviposit, while part of its body is still exposed, outside the cherry. Coffee berry borers are weak flyers and boring into the cherry and reaching the endosperm can take 2– 8 h . Consequently, we estimated the disperser life stage to last 1 day.To our knowledge, there is little information about population densities of CBB in coffee plantations at the start of the growing season. The start of CBB reproduction commenced 120 days after coffee flowering and continued until 305 days after flowering, yielding a 185-day CBB breeding season. We confirmed CBB reproduction was possible within this period for Central Valley Costa Rica using degree day calculations from Jaramillo et al. based on CBB thermal tolerance.

We then calculated how much the dispersing adult survival rate would have to be reduced to cause a 50% reduction in adult female borer population size on day 185. To determine how many CBB would need to be consumed by birds to achieve this goal, we found the difference between daily borer population sizes of unsuppressed and suppressed populations and summed the differences across the CBB reproductive season. We used sensitivity analysis to estimate the degree to which changes in each vital rate affects population growth rate . All models were implemented using the popbio package in R . R code for all analyses is provided in the Supporting Information . We also wanted our model to project CBB population growth that represented “low” and “high” infestations observed in the field. To start, we estimated probable CBB densities using data on the number of dispersing females collected in alcohol-lure traps. At peak dispersal, CBB numbers have been recorded as high as 1000–6120 CBB/trap/week to as low as 50–105 CBB/trap/week . Using these trap counts, we calculated potential CBB densities per hectare via reported trap densities and converted weekly capture estimates to the number of daily dispersers to complement our daily population model. We used a density independent model, a standard first step in many population models. However, note that we would need to divide CBB numbers by plant density to evaluate the impacts of CBB population growth on yield. We also would need empirical data on how the demography of CBB populations change with coffee-plant density to implement a revised model, and we are unaware of published data on this. Consequently, this analysis is beyond the scope of this paper . Using data from Aristizabal et al. , we selected a high peak dispersal count from farms with large infestations and a low peak dispersal count from farms with small infestations to represent peak dispersal on Day 185 in our model. We then back calculated the initial population sizes that would yield those ultimate densities. We used our calculated values of 269 and 5 as our “high” and “low” initial population sizes of gravid females at the start of the coffee season and used 100 CBB to represent “medium” initial population size.The mass, in dry weight, of a female adult CBB was determined from the weighted average of CBB using midpoint values for weight ranges from Moore et al. . We estimated the caloric content of a single CBB using the average energy value of Coleoptera species in the adult stage . Using our estimated CBB caloric content, plant pot with drainage we calculated the number of CBB required to make up 5% and 10% of an average bird’s daily diet . We calculated daily energy requirements for birds under field conditions as M =  2.5, where W is the weight of an average insectivorous bird on coffee farms . We calculated the weight of an average insectivorous bird by averaging body masses of 33 insectivorous resident and migrant bird species reported to consume CBB on Jamaican and Costa Rican coffee farms , or predicted to consume CBB based on morphology and diet breadth . Sherry et al. found that CBB made up 5%–10% of the diet of three Neotropical migratory warblers by number of individuals consumed; we used these percentages to estimate how many calories, and therefore how many CBB, birds potentially eat. Avian consumption rate of CBB was constant, with even effort across the coffee season. For avian densities, we used estimates from Karp et al. of 3 to 14 birds per ha, because these densities include known CBB predators on coffee farms in Costa Rica.Parameters for our Leslie matrix for coffee berry borers are broadly consistent with expectations and general knowledge . For example, our conversion of fecundity to a daily value, F1 = 1.341, is consistent with published literature stating that 1–2 eggs are laid per day by CBB .

Model projections showed that across a 185-day CBB breeding period starting at the point of first ovipositing, an initial population size of 100 female dispersers would produce 1.3 million offspring, resulting in a new adult population of 70,245 females . Assuming
99% of colonizing females successfully bore and oviposit in a coffee cherry on Day 0, the first generation of new dispersing females does not appear until day 37. At Day 38, the adult population begins to increase, and continues to do so exponentially.The daily growth rate of this population converged on 1.042. Sensitivity analysis revealed that survival of adult females had the largest impact on overall population growth , followed by daily survival of pupa , juveniles , eggs and larvae and dispersing females . In addition to modeling growth with 100 initial colonists , we projected the population growth of low and high starting populations calculated from observed weekly alcohol-lure trap catches during peak dispersal . Comparing the three population projections, peak number of dispersers at Day 185 varied considerably, with 162, 3259, and 8768 daily dispersers for low, medium, and high colonizing populations, respectively. In the high population projection, the adult population toward the end of the growing season reached over 18,800 individuals. Note that because these are density-independent models, the number of CBB does not depend on plant density. However, the impacts of the CBB population on yield would depend on coffee plant density. To reduce the final adult population by 50%, the daily survival rate of dispersing females would have to be reduced from 0.99602 to 0.83202. This change represents a 16.4% reduction in daily survival when dispersing. The number of CBB that birds need to eat to reduce the adult population at this rate was driven by the initial population size as a straight line, y = 79.23 N0 . At medium starting population , birds need to consume 7628 CBB during the borer breeding season, while at high starting population , about 20,500 dispersing CBB must be consumed by birds. Daily consumption rates by birds would have to increase over time as the CBB population grows and could vary from 15 to 750 CBB being consumed a day, depending on starting population size . Overall, we calculated that for every female CBB in the initial colonization, birds need to consume 79 CBB to reduce the end of season population by half.We estimated that the caloric content of a 195 μg adult CBB to be 1.09 calories per gram dry weight, or 0.00109 kcal. At 5%–10% of a bird’s daily diet based on number of prey items, birds would consume <7 CBB per day. This represents 0.03%–0.05% of daily caloric requirements of our average insectivorous bird. At these feeding rates, our models suggest that by the time of peak dispersal, 4, 88, and 236 birds are required at low, medium, and high starting population sizes, respectively, to reduce CBB populations by 50% on day 185 .Our model suggests that avian predation is likely to be effective at reducing CBB populations by 50% only during small infestations , or during the early stages of larger infestations . Birds appear unable to successfully suppress medium and large infestations because the number of CBB that need to be eaten in a season requires higher bird densities than are reported in the literature.

Therefore, a comparison of the geometric effects reflected by the generalizations of the Berry phase of purified states or thermal vacua is expected to be achievable in future experiments on quantum computers or quantum simulators. For example, one may consider two identical composite quantum systems of Example V.1 of the generalized Berry phase and then apply a partial transposition to one of the composite systems. As a consequence, the composite system with a partial transposition corresponds to a purified state while the one without partial transposition may be viewed as a thermal vacuum. By applying parallel transport that involves the ancilla to both composite systems and extract their generalized Berry phase after a cycle, a π-phase difference is expected between the two composite systems. Given the large phase difference between them after a cycle, the result is robust against small perturbations or noise from the hardware and offers another demonstration of geometrical protection of information. We have presented two generalizations of the Berry phase, the thermal Berry phase and generalized Berry phase, for distinguishing the two state-vector representations of mixed states via the purified state and thermal vacuum. From the geometrical and physical points of view, pots with drainage holes the generalized Berry phase has more desirable properties since the thermal Berry phase is generated by a temperature-dependent thermal Hamiltonian and may carry non-geometrical information.

We caution that while the transformations can be on the system, ancilla, or both in the construction of the generalized Berry phase, an operation on the ancilla is necessary if we want to differentiate the purified state and thermal vacuum.The two state-vector representations of mixed states via purified states or thermal vacua have been developed in different branches of physics, but both have been realized on quantum computers [32, 33]. We have pointed out that their difference lies in a partial transposition of the ancilla, which has its origin in the Hilbert-Schmidt product. Available physical quantities, including previously studied geometric phases, cannot differentiate the two representations. By analogue of the adiabatic process of pure states, the thermal Berry phase has been constructed and shown to differentiate a purified state froma thermal vacuum. However, the thermal Berry phase may include non-geometrical information. The generalized Berry phase is then constructed by generalizing the parallel-transport condition to properly include the system and ancilla, and only geometrical contributions are included. Depending on the protocol and setup, the generalized Berry phase may also differentiate the purified state and thermal vacuum. Future demonstrations of the interplay between geometric effects and partial transposition of state-vector representations of mixed states on quantum computers or simulators will advance our understanding of quantum systems at finite temperatures.Magnesium has great potentials to serve as next-generation bio-resorbable implants for medical applications due to their excellent mechanical properties, biodegradability, and bio-compatibility . Biodegradability of Mg-based implants and interactions with relevant cells have been studied in vitro for orthopedic and urological applications. Most of the in vitro studies on the degradation of Mg-based implants were performed by immersion in physiologically relevant fluids at the body temperature of 37°C to represent the chemical and thermal environment in vivo.

It is desirable to include physiological loading as one of the key contributing factors when studying in vitro degradation of Mgbased metals for medical implant applications, because mechanical stress could increase the corrosion rates of Mg-based alloys and composites. For example, cyclic loading significantly increased the corrosion rates of high purity magnesium , binary Mg-1Ca, and ternary Mg–2Zn–0.2Ca alloys in simulated body fluid. Li et al. reported that the degradation of Mg/Poly wires was accelerated under a dynamic compressive stress of 0.9 MPa at a frequency of 2.5 Hz. Mg-based alloys are known to be susceptible to stress corrosion cracking ; and Mg-based implants may degrade faster and experience sudden fracture under load, especially in a humid environment such as inside the body. Mechanical behaviors of Mg have been investigated using a slow rate test method in modified simulated body fluid, and Mg did show a lower elongation and ultimate tensile strength due to SSC. Thus, it is important to study the degradation behaviors of Mg-based implants under load for a long period of time, preferably weeks to months, to understand the properties of these implants as they degrade. Although in vivo studies in animal models can provide complimentary information about the performance of Mg-based implants under load, the load in small animal models, such as rats, cannot be directly translated to the human study due to the significant differences in musculoskeletal structures between small mammals and human. Before clinical studies, large animal models, such as sheep and dogs, are often recommended for evaluating orthopedic implants because they have similar loading conditions as human. However, long-term studies in large animal models are always costly and involving sacrifice of many animals.

Therefore, the objective of this study was to develop and build a novel loading device to simulate the human-like physiological loading conditions in vitro for studying biodegradable implants in a long period of time from weeks to months. The degradation behaviors of Mg rods under applied loads of 500 N were investigated for up to two weeks using this loading device. Mg rods were cut into 15 mm × 6 mm using a handsaw, and then polished using silicon carbide papers from 600 grit to 1200 grit. The polished samples were degreased and cleaned in acetone for 30 min and in 100% ethanol for 30 min respectively, using an ultrasonic cleaner . Before immersion, all of the Mg samples were weighed using an analytical balance , and the mass of each sample was recorded as the initial mass . The well design of the loading chamber for housing the Mg samples is shown in Figure 3. To prevent the galvanic corrosion between the Mg samples and the piston, the wells and the caps on the pistons were machined out of Teflon to avoid the metal to metal contact. The Mg rod samples were placed into Teflon wells and immersed in 2.5 mL of revised simulated body fluid that has the same ionic composition as human blood plasma. A load of 500 N was applied on each Mg rod at room temperature until the prescribed immersion time point is reached. The Mg rod controls were also placed in the Teflon wells respectively and immersed in 2.5 mL of rSBF but without load. The Mg rod samples were immersed in rSBF for 3 days, 1 week, and 2 weeks. The rSBF was replenished every other day. The immersion degradation experiment was run in triplicate concurrently. After each immersion period, the rSBF was collected from the wells and the Mg rod samples were dried in a vacuum at room temperature. The macroscopic images of the dried Mg rod samples that were tested with or without 500 N of load were taken using a camera . The dried Mg samples were also weighed using an analytical balance to determine the final mass after immersion. The mass change of Mg samples at different time points was then calculated following the equation /Mo, drainage pot where Mf is the final mass and Mo is the initial mass. The pH of the collected rSBF was measured using a pH meter . The Mg2+ ion concentrations were quantified using inductively coupled plasma – optical emission spectrometry . Briefly, the collected solutions from each well were diluted with deionized water by a factor of 1:100 into a total volume of 10 mL. Mg2+ ion concentrations were then quantified based on the calibration curves generated using Mg2+ standards serially diluted to a concentration of 0.5, 1, 2, and 5 mg/L. The characterization process was repeated for each time point.The macroscopic images of the Mg under load and Mg controls without load showed different surface morphologies after 14 days of immersion in rSBF . Generally, all the Mg samples showed deposition of degradation products after 3 days of immersion. The white degradation products increased as the time increased during the immersion. Mg rods under load, however, had a less degradation products on the surface than that of Mg controls, especially at 7 days and 14 days. Figure 4b shows the mass change of the Mg under load and Mg controls after 14 days of immersion in rSBF. Statistically significant difference was found among the Mg-based samples during the 11 days of immersion [F=175.7, p<0.0001]. All the Mg samples had a significant mass decrease after the immersion. At the 3 days of immersion, all the Mg samples had a mass increase due to the deposition of the degradation products. The Mg under load showed a higher mass increase than the Mg controls. Starting at 7 days of immersion, all the Mg samples had a significant mass decrease, where the Mg under load showed a significantly higher mass loss than the Mg controls. At 14 days of immersion, the mass of Mg controls had no significant change in comparison with the previous time point.

The mass of Mg under load, however, showed a mass loss which was significantly lower than the Mg controls.Figure 4c displays the pH of the rSBF for the Mg under load and Mg controls after 14 days of immersion. Statistically significant difference was found among the Mg-based samples during the 11 days of immersion [F=10.86, p=0.004]. Generally, the pH of Mg-based samples showed an increasing trend as time increased during the immersion. When comparing the Mg under load and Mg controls without load, the pH of Mg controls was higher than that of Mg under load at 3 days and 7 days of immersion. The pH of Mg controls at 14 days, however, showed a lower pH than the previous time point, possibly because the continuous deposition of degradation products slowed the degradation of Mg samples. At 14 days of immersion, the pH of Mg controls was significantly lower than that of Mg under load. From Figure 4d, the Mg2+ ion concentration of the rSBF for the Mg rods under load and Mg controls showed a significant increase during the 14 days of immersion. Statistically significant difference was found among the Mg-based samples during the 11 days of immersion F=55.82, p<0.0001]. The Mg2+ ion concentrations of Mg-based samples showed an increasing trend as time increased during the immersion. The Mg under load showed a higher Mg2+ ion concentration in average than that of Mg controls at all-time points during the immersion. Statistical difference was found at 3 days of immersion and 14 days of immersion.Engineering the loading device for studying Mg-based bio-materials in vitro involves three major challenges, that is, automating, powering, and down scaling in size. Although the current version of our loading device meets the critical design criteria and functional requirements for studying Mg degradation under load, further improvements in the following aspects are still recommended to make the device more user friendly and more robust for repeated experiments. First, automating operation of the loading device can greatly improve the repeatability of experimental results and benefits the users especially in the long-term studies that span from weeks to months. The current pneumatic pistons are powered through an air compressor, which needs to be manually adjusted by the user due to natural accruing air leaks in the system. To improve this, the pneumatic powered pistons can be replaced with electrically powered pistons, and a feedback or closed loop control system can be added for autonomous regulation. One piston type of interest would be hydraulic pistons as they are small, and able to output large forces that would be required for testing various medical implant material. Using these electrical powered pistons, a feedback loop can be created through various means, such as using electrical components that read the output force of the electrical powered pistons, and with that data the device could self correct itself to the desired load output without the need of a user. To implement this, a self adjusting controller such as a PID controller, would be able to provide the device with both versatility and higher accuracy. Second, the device should simulate the body conditions more closely during the in vitro experiments in addition to applying a load onto the implant material. Specifically, it is beneficial to conduct the experiments under standard cell culture conditions inside an incubator, i.e., a sterile, 37°C, 5% CO2/95% air, humidified environment, because such environment resembles the conditions inside the body.

Compounds were identified based on retention time and spectral comparisons with standards. Information about the linear equations and lower limits of detection and quantitation can be found in Table S1 in the supplementary material. The LLOD was calculated as 3.3 times the standard deviation of the y-intercept of the curve divided the slope, while the LLOQ was calculated as 10 times those values.Several peaks appeared in the HPLC chromatograms that could not be identified using the above parameters. Chromatographic eluents of these peaks were collected individually and dried under vacuum. These extracts were reconstituted with mobile phase A, and 5 µL were injected into the HPLC- QTOF-MS/MS for accurate mass analysis . A Poroshell 120 EC-C18 column was used at 35 °C. Mobile phase A was 1% formic acid in distilled water, and mobile phase B was 1% formic acid in acetonitrile. The gradient used was 0 min 3% B, 30 min 50% B, 31-32 min 95% B, 33-38 min 3% B. The mass spectrometer was used in negative mode, and the mass range for MS was 100 to 1000 m/z while the range for MS/MS was 20-700 m/z. Collision energies at 10, 20, and 40 V were applied. The drying gas was set to a flow of 12 L/min at 250 °C, while the sheath gas was set to 11 L/min at 350 °C. The nebulizer was set to 40 psig, the capillary voltage was 3500 V, the nozzle was set to 500 V, vertical gardening in greenhouse and the fragmentor was set to 100 V. Data was analyzed using Agilent MassHunter Workstation Qualitative Analysis 10.0 .

Tentative identification was achieved by comparing the mass to charge ratio of the precursor and fragment ions to online libraries of compounds as well as using formula generation for the peaks in the spectra.The composition of blue elderberries is presented for the first time, which is key to understanding how this subspecies of Sambucus nigra compares to commercialized elderberry subspecies, S. nigra ssp. nigra and S. nigra ssp. canadensis. These data help to establish the blue elderberry grown in hedgerows in California as a viable source of berries and bio-active compounds. Data for the compositional assays is presented for the 2018 and 2019 harvest years as the average of all shrubs sampled in Table 2. The average moisture for the blue elderberries was 79.5 ± 1.5% in 2018 and 79.5 ± 1.6% in 2019, which is very similar to the levels found in wild elderberries in Spain 95. The average soluble solids found in blue elderberry ranged from 11.94 ± 2.08 to 14.95 ± 1.02 g per 100 g FW in 2018 and from 12.64 ± 1.86 to 17.09 ± 1.60 g per 100 g FW in 2019. These values are slightly higher than the soluble solids found in S. nigra ssp. cerulea grown in Slovenia29 and American elderberries grown in Ohio52. Compared to European and American elderberries evaluated in other studies, blue elderberries have similar levels of soluble solids 8,18,29,49,50,95. In the present study, the overall average content of soluble solids was significantly different between years, as blue elderberries harvested in 2019 had significantly higher average soluble solids than the elderberries harvested in 2018 . The pH in the blue elderberry ranged from 3.44 to 3.86 in 2018 and from 3.46 to 3.79 in 2019, with no significant difference found between harvest years.

These values are slightly lower than the values found in European elderberry, which ranged from 3.9 ± 0.06 to 4.1 ± 0.04 with an average pH of 3.9 ± 0.2, and American elderberry, which ranged from 3.9 ± 0.04 to 4.5 ± 0.03 with an average pH of 4.2 ± 0.2 49 Another evaluation of pH in American elderberries had a range of 4.5 ± 0.08 to 4.9 ±0.12,higher than those found in the blue elderberry.52 The higher sugar and lower pH levels in blue elderberry could potentially impact taste and performance in food and beverages as compared with the European and American species. The average titratable acidity in blue elderberries ranged from 0.45 ± 0.08 to 0.77 ± 0.03 g citric acid per 100 g FW in 2018 and from 0.54 ± 0.06 to 0.77 ± 0.11 g citric acid per 100 g FW in 2019 with no significant difference found between harvest years. These values are lower than the total acids found by Mikulic-Petkovsek et al. 29 in S. nigra ssp. cerulea , but they are similar to the levels found in European elderberry 8,18,49,50 .Anthocyanins are a class of phenolics that contribute red, purple, and blue hues to fruits and vegetables, act as attractants for pollinators, and are potent antioxidants. European and American elderberries are well-known for containing high levels of anthocyanins 8,18,49. The anthocyanin content of elderberries strongly correlates to the antioxidant potential of the fruit, which may confer health-promoting properties 50,89, which is one reason why elderberries are used in supplements and value-added products. Elderberry is also used as a source of natural food colorants due to the levels of anthocyanins35. Understanding the levels of anthocyanins in the blueelderberry grown in hedgerows is critical towards establishing this native fruit as an additional and more sustainable elderberry. TMA was variable between hedgerows in both years of harvest, with relative standard deviation values between 16% and 30%, yet there was not a significant difference in the overall average TMA between 2018 and 2019 . Furthermore, most hedgerows were not significantly different from the other hedgerows harvested that year despite significant differences in TMA values found between farms in both years .

Regarding the age of the elderberry shrub, hedgerows 2 and 14 had two of the three highest concentrations of TMA in 2019 . This suggests that blue elderberries can be harvested from plants as young as two years without a significant loss of TMA concentrations. TMA values for the blue elderberries are lower than those found in other elderberry subspecies. In European elderberries, TMA levels range from 170 ± 12 to 343 ± 11 with an average of 239 ± 94 mg CGE per 100 g FW 49. A study of American elderberry grown in Ohio showed a range from 354 ± 59 to 595 ± 26 mg CGE per 100 g FW. In the present study, bare root prerooted cuttings of American elderberries were planted, along with blue elderberries, on Farm 1 in 2018, and three shrubs were harvested in 2019. These American elderberries had an average TMA value of 263 ± 5.4 mg CGE per 100 g FW, which is more similar to what has been observed in other studies on this subspecies. This suggests it is a subspecies difference contributing to the lower anthocyanin concentration in the blue elderberry and not the difference in growing conditions. Compared to other berries, blue elderberries have similar levels of anthocyanins as raspberries, but lower levels than blueberries and blackberries . The lower concentration of anthocyanins in theblue elderberry may require adjustment of levels used in supplements, food and beverages for optimal performance or health benefit, or as natural coloring agents.In addition to anthocyanins, elderberries contain other phenolic compounds, such as flavonols and phenolic acids, which also contribute to the health promoting properties of elderberry. Phenolic compounds are responsible for organoleptic properties and can help protect foods against lipid oxidation. Therefore, TPC can be useful for making approximate comparisons, for example, greenhouse vertical farming between varieties of the same fruit, between similar fruits or in the evaluation of a processing step . It is important to note that the TPC assay is a non-selective assay and is easily impacted by extraction conditions and interfering substances, such as ascorbic acid and reducing sugars. Although there is no evidence that the beneficial effects of polyphenol-rich foods can be attributed to the TPC of a food, it can be a useful measure for making general comparisons with other studies in the literature which reported these values but should be supported by quantitative HPLC data. Herein, the range of TPC measured in the blue elderberries was from 514 ± 41 to 791 ± 34 mg GAE per 100 g FW in 2018 and from 459 ± 50 to 695 ± 41 mg GAE per 100 g FW in 2019 . TPC in the blue elderberries was significantly higher in 2018 than in 2019 . While there were significant differences found between the farms in both years , most hedgerows were not significantly different than most other hedgerows in the given year when evaluated together . Although the farms in this study were near each other and experience similar climates, there can still be differences in growing conditions for each hedgerow, such as water availability, which has been shown to influence the levels of phenolics in blueberries 101 and strawberries 102 . Hedgerows 2 and 14 were not significantly different from other hedgerows in 2019, indicating that the blue elderberries can be harvested earlyin the plant’s lifetime, which allows farmers to earn an early return on the investment of establishing hedgerows.

These comparisons show that blue elderberries from hedgerows are a rich source of phenolic compounds.Phenolic compounds were identified and quantified in the blue elderberry based upon retention time, absorbance spectra and authentic standards when available. Concentrations for samples from 2018 are presented in Table 4, while samples from 2019 are presented in Table 5. Two peaks with significant area were observed in the HPLC chromatograms at 6.96 min and 11.70 min that did not correlate to standards or library matching. Both compounds eluted between the retention time of gallic acid and protocatechuic acid. The first eluting compound had a maximum absorbance at 300 nm while the second compound had a maximum absorbance at 280 nm. These peaks were collected individually and further evaluated by accurate mass quadrupole time-of-flight tandem mass spectrometry . TOF acquires mass spectral data by pulsing ions entering the flight tube in an orthogonal beam, therefore full spectra are collected. The data captured is accurate enough to determine the elemental composition therefore allowing identification without standards. The two compounds were tentatively identified using high mass accuracy as 5-hydroxypyrogallol hexoside, a tetrahydroxybenzene , and protocatechuic acid dihexoside . Accurate mass was especially helpful since commercial standards for these compounds are not available. 5- HPG hexoside was identified by its fragmentation pattern , showing a precursor ion [MH]- at m/z 303.0723 and product ion [M-hexose-H]- at m/z 141.0186 . This compound was one of the most abundant phenolic compounds in the blue elderberry. While no evidence of5-HPG glycoside was found in the literature, the aglycone has shown to have a high radical scavenging activity compared to other simple phenols.Like other elderberry species, rutin was the predominant flavonol and overall had the highest concentration of any of the flavonols measured, with an average of 57.01 ± 17.42 mg per 100 g FW in 2018 and 51.89 ± 25.53 mg per 100 g FW in 2019. These values fall within the range of what has been found in European elderberry. Other flavonols identified include isoquercetin , kaempferol-3-rutinoside, and isorhamnetin-3-rutinoside, which was also a major phenolic compound in the berry. Isorhamnetin- 3-rutinoside averaged 28.30 ± 14.03 mg per 100 g FW in 2018 and 24.71 ± 14.83 mg per 100 g FW in 2019, which is higher than what has been found in other subspecies. Overall, the blue elderberry analyzed in the present study has much higher levels of total flavonols as compared to European elderberry. In the American elderberry, the main flavonols are rutin followed by isorhamnetin-3-rutinoside whereas in European elderberries, the main flavonols are rutin followed by isoquercetin. In blue elderberry grown in Slovenia, rutin and isoquercetin were the two predominant flavonols, though the total flavonols in found for the subspecies was similar to the levels found in this study 59 . The predominant anthocyanin present in the blue elderberry is cyanidin-3-sambubioside, like the European subspecies. The average concentration in 2018 was 32.70 ± 10.18 mg per 100 g FW and 29.66 ± 16.81 mg per 100 g FW in 2019.