plastic plant containers – Nature Ecrogrow

Angular sensors can also be used in some cases to measure linear velocity

In the marketplace, people generally care more about the sensed quantity and how well the sensor performs for their specific application, while academic researchers and sensor designers are also interested in how the sensor measures the quantity. This section is concerned with the latter. The means by which a sensor makes a measurement is called the transduction mechanism. Transduction is the conversion of one source of energy to another, and all sensors utilize some form of energy transformation to make and communicate their measurements. It should be noted that this is not an exhaustive list of transduction mechanisms. This list only covers a small fraction of the many universal laws describing the conversion of one energy form to another. Rather, this list focuses on transduction principles that describe converting one energy type to electrical energy. This is because all electrical sensors must take advantage of at least one of these mechanisms, and often more. What this list does not cover is transduction from any energy type to another type other than electrical. For example, the thermal expansion principle that governs the liquid-in-glass thermometer example at the beginning of this chapter is not described,plastic plant containers because that sensor operates on the principle of converting thermal energy to gravitational energy. This list also does not include modes of biological or nuclear signal transduction mechanisms for the sake of brevity.A potentiometric sensor measures the open-circuit potential across a two-electrode device, such as the one shown in Figure 1.3C. Similar to amperometric sensors, the reference electrode provides ‘electrochemical ground’.

The second electrode is the ion-selective electrode , which is sensitive to the analyte-of-interest. The ISE is connected to a voltage sensor alongside the RE. The voltage sensor must be very sensitive and have a high input impedance, allowing only a very small current to pass. There are four possible mechanisms by which ionophores can interact with ions: dissociated ion exchange, charged carrier exchange, neutral carrier exchange, and reactive carrier exchange. Dissociated ion-exchange ionophores operate by classical ion-exchange over a phase boundary, in which hydrophilic counter-ions are completely dissociated from the ionophore’s lipophilic sites, preserving electroneutrality while allowing sites for the ions in solution to bind to. Charged-carrier ionophores bond with opposite-charged ions to make a neutrally charged molecule, and the ions with which they bond are determined by thermodynamics and the Hofmeister principle. Neutral carrier ionophores are typically macrocyclic, where many organic molecules are chained together to form a large ring-like shape whose gap is close to the molecular radius of the primary ion. Finally, reactive carrier ionophores are mechanistically similar to neutral carrier ISEs, with the only difference being that reactive carriers are based on ion-ionophore covalent bond formation while neutral carriers are based on reversible ion-ionophore electrostatic interaction. Neutral carrier and reactive carrier ion exchange both are dependent on the mobility, partition coefficients, and equilibrium constants of the ions and carriers in the membrane phase. Some examples of the chemical structures of ionophores are shown in Figure 1.4. Positional sensors are some of the most common in the world, and there are likely several within reach of you as you read this. Smartphones and wearable health devices utilize various sensors to track how many steps you take in a day, the intensity of your workouts, and what route to take home from work. Displacement, velocity, and acceleration can sometimes all be found with a single device, as each quantity is the time-derivative of the prior.

In practice, however, it is common to use separate devices for any of these three measurements because the cost of these sensors is relatively cheap, and it is easy to build systematic errors if the timing mechanism is off. The measurements for displacement, velocity, and acceleration must be made with respect to some frame of reference. For example, consider a group of people playing a game of billiards in a moving train car. Observers on the train platform would assign different velocity vectors to the balls during play than observers on the train. Displacement and angle sensors commonly use potentiometers when the value is expected to be suitably small. A potentiometer transduces linear or angular displacement to a change in electrical resistance. For a displacement sensor, a conductive wire is wrapped around a non-conductive rod, and a sliding contact is attached to the object whose displacement is being measured. A known voltage is supplied across the wound wire, and as the object moves, the sliding contact will make contact with the wound wire, shorting that part of the circuit. Then, the output voltage across the wire is measured, which will be proportional to the amount of the wire shorted by the sliding contact, which is proportional to the object’s displacement. The same principles are applied to measure the angle for a potentiometer operating in angular displacement mode. There are other methods for measuring displacement, but these methods can also be used to measure velocity, as described in the following section. Velocity measurements utilize a variety of approaches ranging from radar, laser, and sonic sensor systems. These types of sensors use one of these modulating signals to send a sound or light wave in a direction and measure the time it takes to bounce off of a surface, return to the sensor, and activate a sensing element that is sensitive to that modulating signal. Using this, the device can calculate the distance between the sensor and the reflecting object by dividing lag time by the wave speed. Then, because these devices often operate at a high frequency, the measurement can be made again, and the change in distance divided by the change in the time between measurements yields a linear velocity.In a car, for example, the speedometer is a linear velocity sensor, but it makes its measurement using an angular velocity sensor on the drive shaft and calculates the linear velocity from the assumed tire size.

Acceleration measurements are most commonly made with accelerometers. Accelerometers are most commonly MEMS devices that are extraordinarily cheap, have a low-power requirement, and utilize the capacitance transduction mechanism. The charged electrode of an interdigitated parallel-plate capacitor structure is vibrated at a high mechanical frequency. Then, when acceleration occurs, if it is perpendicular to the gap between the two capacitor plates, the force from the acceleration will cause the moving electrode of the parallel-plate capacitor to deflect towards the other plate, changing the space of the gap between the two, thereby changing the measured capacitance. The operating principle of most pressure sensors is based on the conversion of a pressure exertion on a pressure-sensitive element with a defined surface area. In response, the element is displaced or deformed. Thus, a pressure measurement may be reduced to a measurement of a displacement or a force that results from a displacement. Because of this, many pressure sensors are designed using either the capacitive or the piezoresistive transduction mechanisms. In each, a deformable membrane is suspended over an opening, such that the pressure on one side of the membrane is controlled while the pressure on the other side is the subject of the measurement. As the pressure on the measurement side changes, the membrane will deform proportionally to the difference in pressure. For a piezoresistive transducer, the membrane is designed to maximize stress at the edges, which modulates the resistance proportional to the deformation. For a capacitive transducer, the membrane is made of or modified with a conductive material, while a surface on the pressure-controlled side of the membrane is also conductive, and the pair act as a parallel-plate capacitor. Then, the membrane is designed to maximize deflection at the center of the membrane,blueberry container thereby changing the electrode gap and capacitance.Practically speaking, a sensing element does not function by itself. It is always a part of a larger ‘sensor circuit’: a circuit with other electronics, such as signal conditioning devices, micro-controllers, antennas, power electronics, displays, data storage, and more. Sensor circuits fit within the broader subject of systems engineering, which is a vast field in its own right. Figure 1.5 shows one possible sensor circuit configuration. Depending on the design of the circuit and which components are included in it, the signal that is output by the sensing element might be conditioned to the specifications of a connected micro-controller, saved onto a flash drive, shown on a display, and sent to a phone, saved on a remote server, or many other possibilities. Rather than discuss all possible sensor systems and circuit designs, we have selected the most common – and arguably most essential – components in any given sensor system and summarized them in this section.

In some form or another, all sensor circuits require power to operate. The components of a sensor circuit that generate, attenuate, or store energy to power the other circuit components are called power electronics. This may include batteries, energy harvesters, and various power conditioning devices. A sensor circuit can be made passive, where there is no energy storage within the circuit. The concept is similar to passive sensing elements described in section 1.2: passive sensor circuits use the naturally available energy to operate. This can be done if the quantity that is being measured can also be harnessed to power the device, such as light powering a photovoltaic sensing element. If there is no passive power generation, power electronics are vital for a sensing circuit’s function. This could be as simple as a coin-cell battery connected to the micro controller’s power I/O pins or as complex as a circuit with multiple energy harvesting and energy storage modalities. A sensor is not a sensor if it does not communicate its measured signal to another person or device. Communication electronics are what fulfill this function. Communication electronics can be wired or wireless. When communicating data to a person, wired communications electronics could be displays or speakers that communicate the data through images or audio. When communicating data to another computer, wired communication electronics come in the form of a ‘bus’, a catch-all term for all the hardware, wires, software, and communication protocols used between devices. At the time of this writing, wireless communications must be between the sensor circuit and another electronic device, though perhaps in future years, technology will develop a way for people to directly interface with wireless data transfer. In the meantime, wireless communications generally incorporate an antenna that attenuates an electrical signal into a directional RF frequency following one of many wireless communication protocols such as WiFi, Bluetooth, or RFID.In science and engineering, ‘error’ does not mean a mistake or blunder. Rather, it is a quantitative measurement of the inevitable uncertainty that comes with all measurements. This means errors are not mistakes; they cannot be eliminated merely by being careful. All sensors have some inherent error in their measurement. The best that one can hope for is to ensure that the errors are minimized where possible and to have a reasonable estimate of the magnitude of the error. One of the best ways to assess the reliability of a measurement is to perform it several times and consider the different values obtained. Experience has shown that no measurement – no matter how carefully it is made – will obtain the same values. Error analysis is the study and evaluation of uncertainty in a measurement. Uncertainties can be classified into two groups: random errors and systematic errors. Figure 1.8 highlights these two types of error using a dartboard example. Systematic errors always push the measured results in a single direction, while random errors are equally likely to push the results in any direction. Consider trying to time an event with a stopwatch: one source of error will be the reaction time of the user starting and stopping the watch. The user may delay more in starting the stopwatch, thereby underestimating the duration of the event, but they are equally likely to delay more in stopping the stopwatch, resulting in an overestimate of the event. This is an example of random uncertainty. Consider if the stopwatch consistently runs slow – in this case, all events will be underestimated. This is an example of systematic uncertainty. Systematic errors are hard to evaluate and sometimes even difficult to detect. However, the use of statistics gives a reliable estimate of random error. In the kingdom of electronics, silicon reigns.

Quercetin galactoside did not significantly differ among the treatments

The effective concentration of GA can vary markedly according to sensitivity of the variety to the hormone. For example, ‘Thompson Seedless’ requires multiple applications and large cumulative amounts of GA exceeding 100 ppm, while a single application of 10 ppm of GA can triple the size of ‘Black Finger’ berries. GA is also known to potentially delay maturity, increase pedicel thickness, and increase berry abscission depending on the application time. If applied on the whole vine on sensitive varieties, GA can also harm reproductive meristems and reduce subsequent yield. The molecular aspects of the synthesis, signal perception, and transduction of GA in grapes have been reported. The study of the effects of cytokinins on grape development focused largely on forchlorfenuron -N′-phenylurea, a synthetic cytokinin known as CPPU, that has been tested and applied to regulate fruitset, size, and shape in several fruit crops. In grapes, CPPU was also reported to delay maturation and reduce berry skin color, increase berry pedicel thickness and rigidity, increase cuticle content, and reduce weight loss of the rachis. CPPU is commercially applied at levels of 5 ppm or lower due to its potential adverse effects on maturation and post harvest quality. The time frame for application of CPPU is usually similar to that of GA and often in combination with GA at reduced concentrations. Other cytokinins such as benzyl adenine had similar effects but a concentration of 500–1000 ppm was required to increase berry size. Phenylpropanoids are a large class of plant secondary metabolites derived from aromatic amino acids, phenylalanine in most plants or tyrosine in some monocots.

The main branches of the phenylpropanoid pathway include lignans and lignins, stilbenes, coumarins, isoflavonoids, flavonoids, and PAs. The biosynthesis of PAs, anthocyanins,hydroponic pots and flavonols share common steps in the flavonoid pathway. In grape berries, the first committed steps in PA biosynthesis are catalyzed by leucoanthocyanidin reductase and anthocyanidin reductase by converting anthocyanidins to flavan-3-ols such as -catechin and -epicatechin , respectively. The resulting -epicatechin and -catechin derivatives can be oxidized to quinones, which are polymerized. However, it is not clear whether this polymerization of the soluble precursors proceeds enzymatically by laccases or non-enzymatically. The subunits of PA are derived from 2,3-cis-flflavan-3-ols -epicatechin and -epigallocatechin , as well as from 2,3-trans-flflavan-3-ols -catechin and -gallocatechin and are most commonly linked via 4 β → 8C−C bonds. The PAs are oligomeric and polymeric flflavan-3-ols that can range in size from 2 to 30 or more subunits. The regulation of the phenylpropanoid pathway was studied extensively in grapes with respect to anthocyanins, PAs, and other branches of the pathway with emphasis on the role of R2R3-MYB, bHLH, and WD40 transcription factors and their target genes. Our previous study demonstrated that CPPU causes a marked increase in tannin content of Thompson Seedless. Thompson Seedless is a major variety but it does not produce anthocyanins and is very low in volatile content. In the current study we presented the following questions: how do CPPU and GA affect tannin accumulation in a variety that is rich in anthocyanins and volatile compounds; and how are biological processes at ripening affected by the treatments. These questions were addressed at the phenological level, by the analysis of relevant metabolites from the phenylpropanoid pathway, by volatile composition, and by transcriptome analysis.Experiments were carried out on Vitis vinifera cv. Sugrasixteen that will be referred as ‘Sable’. Vines of ‘Sable’ were grafted on Richter root stock that was 7 year old and grown in Israel in the Lachish area . All viticulture practices were performed as describepreviously.

The experimental plot comprised of four replications of three vines each, arranged in a randomized block design. Clusters were manually sprayed to full wetness with the growth regulators gibberellic acid and forchlorfenuron in a concentration of 20 and 5 ppm, respectively, with 0.025% Triton-X100 as a wetting agent. A combination of GA and CPPU was also sprayed on the berry at the same concentrations. ‘Sable’ was treated on 14 May 2018 at the berry diameter of 6.0 ± 0.08 mm. Phenological data for ‘Sable’ was collected at the time of treatment , and 7, 34, 51, and 70 days post treatment . Sampling for metabolites, volatiles, and gene expression was carried out at 51 and 70 d after treatment, the time points which represent the beginning and end of commercial harvest. Sampling at all time-points was of 90 berries pooled from 20 to 30 clusters randomly collected from the four vineyard replications. For metabolite and RNA-seq analysis, a disk of 14–16 mm was removed along the longitudinal axis of each berry and was frozen in liquid nitrogen. The berry disks were homogenized in three replicates of 30 disks each using an IKA homogenizer with liquid nitrogen and were stored at −80 °C for further analysis. The remaining part of the berries was used for measurement of total soluble solids and titratable acidity .Measurements of TSS and TA in ‘Sable’ berries of GA, CPPU, and GA + CPPU treatments were carried out as previously described. The juice was obtained by using a fruit juicer from 30 berries. TSS was determined by a digital refractometer and denoted as °Brix. TA was measured by means of titration with 0.1 N NaOH to pH 8.2 with a Metrohm automatic titrator and expressed as tartaric acid equivalents. All the above analyses were performed on fresh samples at the harvest date. Informal tasting was done by three expert tasters that scored the samples in hedonic scale of 1–9 .Sample preparation and microscopic examination of ‘Sable’ berries at 33 d after GA, CPPU, and GA + CPPU treatment were performed as described by Tyagi et al.. Briefly, transverse hand sections from ‘Sable’ berries of GA, CPPU, and GA + CPPU treatment were immediately immersed in a solution containing formaldehyde, acetic acid, ethanol, and water in ratios of 10: 5: 50: 35, respectively.

After fixation, tissue sections were serially diluted by ethanol and subsequently a stepwise exchange of ethanol with Histoclear was carried out. Samples were embedded in paraffin and cut with a microtome into 12 μm thick sections. Sections were stained with Safranin O that stains nuclei, lignified suberized, or cutinized cell wall in red, and with fast green FCF that stains cellulose in green-blue and sections were examined under a light microscope .Gibberellin and cytokinin applied at fruit-set are known to increase berry size, but due to the complexity of agricultural systems, the intensity of the response can vary among seasons. The PGR treatments were performed at a fruitlet size of 6.0 ± 0.08 mm on ‘Sable Seedless’. Fruitlet diameter and weight increased significantly by application of both GA and CPPU measured 7 d after treatment . Interestingly, at 34 d post treatment, berry diameter and weight of CPPU-treated berries was smaller than the control but this trend was reversed at later time points. At 51 and 70 d after the treatments, CPPU increased berry weight and diameter significantly with respect to the control and the GA treatment. The GA treatment increased berry size by 17.5% and 13.4% at 51 and 70 d, respectively, but at a later time point, the difference was not statistically significant from the control. The diameter and weight of berries treated with the combined treatment of GA + CPPU was higher than that of CPPU alone at both 51 and 70 d. Brix of the control grapes was higher at all time-points followed by GA and CPPU . At 34 d,grow pot berries treated with GA + CPPU had higher Brix as compared to CPPU-treated berries, but at later time points there were no differences among the two treatments. CPPU had a major effect on TA that was much higher than the other treatments at 34 d after treatment . At both 34 and 51 d, GA seemed to mitigate the effect of CPPU on TA. With respect to appearance of the berries 34 d after the treatment, there was a clear delay in color development by CPPU and the treatment of GA + CPPU . Transverse sections of the berries showed that the epidermal layer was thicker either in both GA- and CPPU-treated berries or the combined treatment as compared to the untreated control . Informal tasting done by experts indicated excellent taste rated as 8 with multiple aromatic notes for the control and GA treatments, while in berries from the CPPU treatment there was some astringency that reduced the score to 7.5 or 7.0 for the combined treatment.The cytokinin CPPU was shown to increase total tannins in Thompson Seedless that bears green berries. It was therefore of interest to determine what effect CPPU has on black berries and if GA has similar effects. HPLC analysis was carried out for glucosides, acylated and coumaroylated forms of delphinidin, cyanidin, petunidin, peonidin, and malvidin . CPPU and GA + CPPU treatments reduced the levels of the majority of these compounds at both 51 and 70 d as compared to the control. Quantitatively, CPPU reduced the levels of the anthocyanin glucosides by ca. 50% at both time points. The GA + CPPU treatment reduced the levels of the anthocyanin glucosides to ca. 75% and 53% at 51 and 70 d, respectively, as compared to the control.

At 51 d post treatment, GA reduced the inhibitory effect of CPPU but this effect was not maintained at 70 d . Anthocyanin glucosides are the major form present in ‘Sable’ comprising 63–71% of the total anthocyanins and the remaining are acetylated and coumaroylated forms . Interestingly, CPPU reduced the proportion of the glucoside forms at both 51 and 70 d and this decrease was accompanied by an increase in coumaroyl glucosides at both time points and acetylated glucosides at 70 d. GA had an intermediate effect on the proportion of the anthocyanin forms. Flavonols are an important branch of the flavonoid pathway and therefore it was of interest to determine the effect of the treatments on major grape flavonols . Myrcetin glycoside was the major flavonol detected with an average of 81–89% among the compounds tested. While variation among replications was significant, two trends are worth noting. At 51 d, CPPU alone or in combination with GA reduced the levels of flavonols to ca. 60% of the control. At 70 d there was an increase in levels of the flavonols and decrease in the effect of CPPU.Flavan-3-ols are the building blocks of the PA chains that are synthesized in the early stages of berry development. Figure 2c displays the three major flavan-3-ols: -catechin, -epicatechin , and -epigallocatechin . Clearly, CPPU-treated berries contained more flavan-3-ols and their level increased during ripening. At the late sampling, GA + CPPU reduced the level of the flflavan-3-ols as compared to the CPPU treatment alone. The hydroxycinnamic acid derivatives, caffeic acid, caftaric acid, coutaric acid, and ferulic acid changed in different ways: caftaric acid was highest in the early stage in CPPU-treated berries; caffeic acid levels were reduced by CPPU at the early stage and it was absent in the late harvest; coutaric acid levels were induced by CPPU and reduced by the combined treatment relative to the control; the levels of ferulic acid were low but increased with ripening without a distinct pattern .To further investigate the effect of GA, CPPU, and GA + CPPU on PA composition, phloroglucinolysis was performed and differences were monitored using HPLC . Phloroglucinolysis hydrolyzes the polymeric PAs generating terminal units and extension units with phloroglucinol adduct . CPPU increased the levels of C, EC, EC-P, and EGC-P. GA did not affect the levels of the PA monomers while the treatment with GA + CPPU reduced the levels of C, ECG, EC-P, and EGC-P only at 70 d after the treatments . Monomeric PAs did not change with ripening with the exception of ECG that was lower at 70 d compared to the control treatment. The total PA level clearly shows the effect of CPPU and also shows that the combined treatment reduced the level of PAs at 70 d in agreement with the data on the free monomers . The treatments with GA or CPPU had minor effects on the % galloyl units but the combined treatment reduced their level. The mean degree of polymerization was significantly lower in CPPU and GA + CPPU treatments as compared to the control .