June 2023 – Nature Ecrogrow

Ethylene production by the olive inflorescence was lowest four days before FB

High GA-like concentrations in midsummer reduce generative bud development, and the highest GA-like substance in fruits occurred in June and July . These collective results suggest that gibberellins in developing seeds of fruits on one year old growth suppress development of fruit buds on the apical current year’s shoot growth, resulting in alternate bearing. Thus, alternate bearing is due to inhibition of floral induction , and floral induction in the current year is inhibited by fruit load from the previous year. There is a negative relationship between the current year’s flowering intensity and the previous year’s production . In ‘Manzanilla de Sevilla’ cultivar, 58% of the variance in the number of flowers was explained by production in the previous year. The current year’s yield depends on flowering intensity, which depends on the previous year’s production. This relationship was also found in pistachio. The yield of the previous-year harvest is most strongly and negatively correlated with the yield of current year . However, the specific mechanism of suppressing floral bud induction and development is unknown. The role of ethylene in precipitating plant organ abscission, including floral organs, is clearly defined .It increased to a maximum seven days after FB and this peak coincided with massive flower shedding . Inhibition of ethylene results in longer-lived carnation flowers . In the ethylene biosynthesis pathway, methionine is catalyzed to SAM by SAM synthetase, SAM is then converted to 1-aminocyclopropane-1-carboxylic acid by ACC synthase,macetas cuadradas and ACC is further converted to ethylene by ACC oxidase . The ACC synthase is the targeted compound in limiting ethylene synthesis in tomatoes .

The compound aminoethoxyvinylglycine competitively inhibits ACC synthase activity by binding to the substrate’s active site, preventing ethylene synthesis . AVG is now used on multiple fruit crops. AVG applications to apple trees during harvest slowed ripening, effectively extending the harvest period . AVG inhibited ethylene biosynthesis, increasing peach fruit quality . Similarly, AVG decreased ethylene generation and increased fruit firmness in plums post harvest . AVG treatment delayed cocoa flower abscission and decrease ethylene generation in pear flowers, increasing fruit set and yield . Similar results were found in apples . Whole-tree applications of AVG on ‘Regina’ and ‘Kordia’ cherry trees significantly improved fruit set and yield . AVG application in walnuts increased yield because the high ethylene concentrations in female flowers caused of pistillate flower abortion . The effect of AVG on ethylene suppression has been confirmed multiple times. For example, AVG prevented ethylene generation in rapeseed and sunflower plants . AVG applications inhibited fruit ethylene production in ‘Golden Supreme’ apples . The primary role of AVG is inhibition of ethylene biosynthesis . Extensive research of AVG applications in walnut demonstrated that ReTain™ applied to pistillate flowers successfully decreased ethylene production and resulted in reduced flower abortion . Subsequent orchard trials confirmed these findings. The AVG treated walnut trees produced higher yields than control trees because the AVG reduced pistillate flower abortion, improving fruit set . We hypothesized the short longevity of olive pistils is the primary reason for the low fruit set and yield in olives. We further hypothesized that AVG applications, as ReTain™, during bloom can potentially decrease ethylene generation by olive inflorescences, extend the pistil and ovule longevity for a longer effective pollination period, and increase yield.

Therefore, we tested the ability of AVG, as ReTain™, applied at 25 to 50% bloom to decrease ethylene production by olive flowers, extend the pistil viability, EPP, and potential successful fertilization, and increase fruit set and oil yield in Arbequina olives. The experimental site was a 12 year-old Oleae europeae cv. ‘Arbequina’ orchard located at 38.07°N, -121.21°W, farmed commercially by Lodi Farming Inc. The orchard comprises 59 rows oriented on a north-south axis with ~ 220 trees in each row. Trees are spaced at 5 feet inrow x 13 feet between rows, for 670 trees per acre. We designated this orchard as Orchard A. A randomized complete block design was used in the experiment, with six, eight-row blocks containing two, three-row sets within a block, separated by two buffer rows. The ReTain™ treatments were applied once in every block to three contiguous rows . The center row of the three contiguous rows was used to collect samples and yield data.In 2019, after spraying on May 13th, 2019 , sampling of ethylene evolution started and was repeated daily for 13 days, until there was no difference in ethylene generation between control and treatment trees. It rained on 10 of the 13 sampling dates. From each treatment in each block, two trees, each from the north and south ends of the row, were selected for ethylene measurements. From each tree, two uniform shoots, similar in floral load, facing two directions , and at equal position in the canopy were collected daily for 13 days. They were placed on ice and transported to the lab immediately. In the lab, ~ 0.6 g, or three to five inflorescences were cut from each shoot, weighed on a Mettler balance and placed in a 15 cm airtight test tube. The tubes were placed in a controlled temperature room at 20°C to equilibrate for 1 hour. After equilibration, 10 mL of air was withdrawn from each sealed tube with a 10 mL syringe and injected into Series 400, AGCCarle Gas chromatograph for ethylene measurement. Ethylene production was expressed as µL/.In 2019, olive inflorescence samples were collected and preserved in FAA solutions .

They were further dyed with Aniline Blue and observed using a fluorescence microscope. Pictures of olive ovaries were taken, and pollen tube widths were measured using ImageJ. The pollen tube width was used as a measure of pollen tube growth, which reflected the effect of ReTain™. The treated and control rows were individually harvested on November 15th, 2019, by a Vinestar canopy contact parallel bow rod harvester with a single detached fruit bin traveling at a ground speed of 1.5 mph. The weight of the detached fruit bin was determined before harvest. The fruit weight per row was then determined using a digital in-ground scale with the bin tare entered. After weighing, a 5 kg sample was collected and put on ice for transport to the UC Olive Center Laboratory of Dr. Selina Wang at UC Davis for oil quality analyses.The same experiment was not repeated in 2020 due to strong alternate bearing and a lack of flowers. However, a grower trial was performed; selected rows in two orchards were sprayed on with the same ReTain™ treatment and control, and ethylene emission was measured from inflorescences collected from the sprayed and unsprayed rows. The sprayed and control rows in Orchard B and C were harvested and yields compared on November 15th, 2020, in both orchards. The yield from Orchard A of the 2019 experiment was measured for comparison with the yield of 2019. In 2019, the six treated rows in Orchard A produced an average yield of 3320 lb, with a standard deviation of 408, while the 6 control rows produced an average of 2970 lb, with a standard deviation of 98. With a p-value of 0.067, the difference in yield between ReTain™ treatment and control rows was not significant when the alpha level equaled 0.05. However, it was significant when the alpha level equaled to 0.1 . In 2020, the six treated rows in Orchard A produced an average yield of 1160 lb, with a standard deviation of 290,maceta cuadrada plastico while the six control rows had an average of 1185 lb, with a standard deviation of 369. The p-value was 0.9, showing no significant difference in yield between ReTain™-sprayed and unsprayed rows . The yields across the orchards in 2019 and 2020 were also determined . In 2019, the significant difference in ethylene generation between treated and control trees suggested that ReTain™ worked as assumed: it decreased ethylene generation. Day 0 was denoted as the ReTain™ application date. The confidence bands for ethylene generation were very narrow before day 3 and after day 12 . During those days, some ethylene measurements appeared to be zero and were omitted, because it is impossible to have zero ethylene generation . Fewer ethylene measurements before day 3 and after day 12 resulted in narrow confidence bands. The primary finding was not affected: from day 3 to day 12, the ethylene generation from ReTain™-treated trees was significantly lower than that from control trees. We hypothesized that delayed floral senescence was a consequence of decreased ethylene generation; however, the visual inflorescence rating data suggested the opposite. The senescence ratings of treated trees were significantly higher than the control trees, indicating ReTain™ increased the rate of flower senescence. Throughout the experiment, the first-opened flowers senesced first.

The blocks on the edge of the orchard senesced earlier than blocks in the center of the orchard, east sides of the rows than the west, and the south end of the rows earlier than the north. The flowers in the row on the edge of the orchard and the ones on the south end of the rows also bloomed first. This could be potentially explained by that those flowers were at locations to receive the most heat. The visual evaluation of inflorescence senescence was based on petal color change and petal drop. It might not indicate the ovule viability throughout the experiment. Therefore, it is possible that the petal drop was not correlated with the effective pollination period and ovule viability. Aniline blue fluorescence was argued to be an accurate method to measure ovule senescence in olives The findings on pollen tube growth supports this possibility. There was no significant difference between treated and control flowers in pollen tube width. This suggested both treated and control flowers were pollinated equally, even though the treated flowers senesced more rapidly than the control flowers. The non-significant difference in pollen tube width suggested that pollination an ovule viability were not affected by ReTain™. It is possible that pollen tube width is not a good indicator of pollination. The pollen tube width is primarily a measurement of the amount of pollen deposited on the stigma that germinated and produced a pollen tube. We selected this measurement reasoning that a longer effective pollination period provides more time for pollen grains to land on the stigmas. Determining whether the pollen tube has reached the ovary might be a better indicator of successful pollination . However, after reaching the ovary, the pollen tube was unrecognizable . The tissue in the ovary was too thick to observe under a fluorescence microscope. In Arabidopsis, both ethylene-dependent and ethylene-independent pathways are required to initiate and progress through floral senescence . It is possible that the floral senescence in olives is not regulated primarily by ethylene. Pollination induces a series of post-pollination developmental events, including petal senescence . Pollination-triggered senescence has multiple advantages. Once sufficient pollen has been set on the stigma, additional pollen deposition is wasteful, and excess pollen tubes may compete for nutrients. In addition, maintenance of floral structures is costly . In 2020, the ReTain™ treatment was applied to two different orchards at the same concentration. However, no ethylene was detected from either treated or control flowers, which may be due to reduced number of flowers in an “off” year. In 2019, heavy rain during bloom could have prolonged the flowering time. The heavy rain and low temperature combined with the spray of ReTain™, while the control rows were not sprayed, could potentially explain the earlier senescence of the treated rows. The lowest temperature during the bloom reached 8°C, while the optimal temperature for olive pollen germination and pollen tube growth is 20 to 25°C . The low temperature during the bloom may have negatively impacted pollination in both ReTain™-treated and control trees. In 2019, the difference in yield between ReTain™-treated and control rows was not significant at 0.05 but was significant at 0.1. However, yield fluctuated greatly in treated rows, while the yield among control rows was stable. ReTain™ strongly improved yield in five out of six rows, but the increase was not consistent and the effect of ReTain™ was not uniform among rows .

This is a two-fold improvement when compared to previous transcriptomic studies

The class II DNA transposons content is 34.0% . This high percentage of class II DNA transposons appear to be present in three lineages of rust fungi, the Melampsoraceae , Pucciniaceae and Phakopsoraceae . The recently assembled large genome of the rust fungus Austropuccinia psidii in the family Sphaerophragmiaceae, however seems to mainly have expanded in retrotransposons. This illustrates that TEs exhibit different evolutionary tracjectories in different rust taxonomical families. Over 80% of the P. pachyrhizi genome is comprised of only two superfamilies of TEs: long terminal repeat and terminal inverted repeat . The largest single family of TE are the Gypsy retrotransposons comprising 43% of the entire genome . To understand the evolutionary dynamics of the different TE families present in the P. pachyrhizi genome, we compared the sequence similarities of TEs with their consensus sequences in the three genomes, which ranges from 65 to 100% sequence identity . Based on the concept of burst and decay evolution of TEs, the extent of sequence similarity between each TE copy to its cognate consensus is proportional to the divergence time of copies. This approach allows us to compare within-genome relative insertion ages of TE insertions using consensus of TE families, a proxy for the ancestral sequence. TEs were categorised as conserved TEs , intermediate TEs and divergent TEs. The average TE composition of the three isolates is 13.2−18.3% conserved, 29.4–29.9% intermediate and represent 51.7−57.3% divergent . The average Gypsy retrotransposon composition of the three isolates is 16.5–20.7% conserved, 30.4–31.03% intermediate, and 48.8–52.5% divergent . Similarly, average TIR composition of the three isolates is 12.2–18.4% conserved, 29.0–29.7 % intermediate and 51.8–57.8% divergent . This suggests that i) multiple waves of TE proliferation have occurred during the history of the species, ii) the invasion of the two major TE families into the P. pachyrhizi genome is not a recent event, and iii) the presence of conserved TEs indicates ongoing bursts of expansion of TEs in the P. pachyrhizi genome.

Therefore,berry pots the proportion and distribution of TEs indicate that different categories of TEs differentially shaped the genomic landscape of P. pachyrhizi during different times in its evolutionary history . We set out to date the Gypsy and Copia TEs in P. pachyrhizi, using a TE insertion age estimation. We observe that most retrotransposon insertions were dated less than 100 million years ago . We, therefore, decided to perform a more granulated study taking 1.0 million year intervals over this period. We approximated the start of TEs expansion at around 65 Mya after which the TE content gradually accumulates . We can see a more rapid expansion of TEs in the last 10 Mya, indeed over 40% of the Gypsy and Copia TEs in the genome seem to have arisen between today and 5 Mya . The climatic oscillations during the past 3 Myr are well known as the period of differentiation for multiple species. Therefore, the genome expansion through waves of TE proliferation in P. pachyrhizi correlates with periods in which other species, including their host species the legumes started their main radiation, and differentiation due to external stressors. This suggests that TEs either play an important role in generating the variation needed to adaptation of various stressors and/or proliferation of TEs is triggered by stressful events. Although a clear causal and or mechanistical role of TEs in adaptation, like in many other systems is still lacking, it is clear TEs have had a major impact on the architecture of the P. pachyrhizi genome.To build a high-quality resource that can facilitate future in-depth analyses, within the consortium, we combined several robust, independently generated RNAseq datasets from all three isolates that include major soybean infection-stages and in vitro germination . Altogether, eleven different stages are captured with seven having an overlap of two or more isolates, representing a total of 72 different transcriptome data sets . These data were used to support the prediction of gene models with the de novo annotation pipeline of JGI MycoCosm. Those proteins secreted by the pathogen that impact the outcome of an interaction between host and pathogen are called effectors and are of particular interest We used a variety of complementary methods to identify 2,183, 2,027, and 2,125 secreted proteins encoded within the genome assembly of K8108, MT2006 and UFV02, respectively.In P. pachyrhizi, depending on methodology, 36.73 − 42.30% of these secreted proteins are predicted to be effectors . We identified 437 common secreted proteins that are differentially expressed at least in one time-point in planta, of which 246 are predicted to be effectors providing a robust set of proteins to investigate in follow-up functional studies . We performed expression analysis on the annotated TEs and observed that 6.66−11.65% of TEs are expressed in the three isolates .

We compared the TE expression from different infection stages versus in vitro stages and used the in planta RNAseq data from the isolates K8108 and UFV02. A relatively small subset of TEs are expressed during the early infection stages between 10 to 72 hours post-inoculation . Remarkably, for this subset, we observed a 20 to 70- fold increase in the expression when compared to the spore and germinated-spore stages, with the expression levels reaching a peak at 24 HPI . To estimate the impact of the insertion age of this in planta-induced TE subset, we performed expression analysis on the conserved, intermediate, and divergent TEs. Although there is a slight overrepresentation of the conserved TEs, several intermediate TEs and divergent TEs are also highly expressed during 10–24 HPI . To compare the expression profile of this subset of TEs to the predicted effectors, we used the 246 core effectors and compared these with 25 known and constitutively expressed housekeeping genes across three isolates. We found that both TE and effector expression peaked at 24 HPI . While expression of effectors remained higher than the 25 selected housekeeping genes during infection, expression of TEs started to be repressed after 72 HPI . This observation would corroborate the hypothesis of stress-driven TE derepression observed in other patho-systems. However, it also shows that in P. pachyrhizi only a small percentage of the TEs are highly expressed during early infection stages. In several different phytopathogenic species a distinct genomic organization or compartmentalization can be observed for effector proteins. For example, the bipartite genome architecture of Phytophthora infestans and Leptospheria maculans in which gene sparse, repeat-rich compartments allow rapid adaptive evolution of effector genes. Other fungi display other organizations such as virulence chromosomes or lineage-specific regions. However, when interrogating both genomic location and genomic distribution of the predicted candidate effector genes in P. pachyrhizi, we could not detect an analogous type of organization . In addition, we did not observe evidence of the specific association between TE super families and secreted protein genes , as has been observed in other fungal species. Additional analyses comparing the distance between BUSCO genes and genes encoding secreted proteins also showed no specific association . Therefore, despite the large genome size and high TE content of P. pachyrhizi, its genome appears to be organized in a similar fashion to other rust fungi with smaller genome sizes. The lack of detection of a specific association between TE and genes in P. pachyrhizi may be due to the level of TE invasion with 93% TE observed for this genome.Rust fungi are dikaryotic, therefore variation can exist both between isolates and between the two nuclei present in each cell of a single isolate. Long-term asexual reproduction is predicted to promote divergence between alleles of loci,hydroponic grow system which in principle can increase indefinitely. Some rusts can reproduce both sexually and asexually leading to a mixed clonal/sexual reproduction. In the rust fungus P. striiformis f.sp. tritici, asexual lineages showed a higher degree of heterozygosity between two haploid nuclei when compared to the sexual lineages.

In the case of P. pachyrhizi, there are clear indications that the population is propagating asexually in South America based on early studies using simple-sequence repeats and internal transcribed spacer sequences. Our data utilizing high coverage raw Illumina data corroborate these earlier studies as we observed high levels of heterozygosity; 2.47% for UFV02, 1.61% for K8108 and 1.43% in MT2006, respectively . This was further corroborated by mapping the Illumina reads to the genome assembly. In total, 283.355, 359.939, and 458.719 SNPs were identified from K8108, MT2006 and UFV02, respectively. The average heterozygous SNPs across the genome is 2.97 SNPs per Kb in UFV02 compared to 2.58 and 3.34 SNPs per Kb in K8108 and MT2006, respectively . We subsequently studied the structural variation as well as the haplotype variation between the three isolates. Remarkably, the structural variation between the haplotypes of UFV02 is 163.3 Mb, while the variation between the complete genomes of the three isolates is 8 to 13 Mb . For example, the total number of repeat expansion and contractions is 7 and 16 times higher between the haplotypes than the variation between the isolates . To look at this inter-haplotype variation in more detail, we selected contigs larger than 1 Mb to study large syntenic blocks between isolates and haplotigs. The largest of these contigs, the 1.3 Mb contig 148 from UFV02 has synteny with contig 5809 from K8108, and contigs 220 and 362 from MT2006 , but not with its haplotig genome counterpart within UFV02, which indicates lack of recombination between haplotypes. This corroborates earlier studies that in South America P. pachyrhizi reproduces only asexually. Collection of the monopustule isolates K8108, MT2006, UFV02 is separated in both time and geographical location . To study SNP variation, we mapped the Illumina data of all three isolates to the reference assembly of UFV02. Given the high level of heterozygosity and TE content, we focused our analysis on the now annotated exome space . After removal of SNPs shared between either all three or two of the isolates, we identified only three nonsynonymous mutations unique for K8180, eight non-synonymous mutations for MT2006 and five unique non-synonymous mutations forUFV02. For these 16 predicted genes, we found evidence for expression in our transcriptome analyses for ten genes. This total number of non-synonymous mutations within exons between the isolates may appear counterintuitive given the time and space differences between collection of these isolates. Nonetheless, it is likely that other single pustule isolates identified from another field would yield a similar number of mutations. Approximately 6 million spores may be produced per plant in a single day resulting in 3 × 1012 spores per hectare per day. Therefore, the ability to generate variation through mutation cannot be underestimated. We observed an enrichment of mutations in the upstream and downstream regions of protein-coding genes , similar to other rust fungi. In contrast to the low number of mutated exons, the number of uniquely expressed genes between the three isolates is relatively high when compared to the core set of differentially expressed genes . This may reflect a mechanism in which transcriptional variation is generated via modification of promotor regions which would have the advantage that coding sequences that are not beneficial in a particular situation can be “shelved” for later use. This would result in a set of differentially transcribed genes for different isolates, and a core set of genes that are transcribed in each isolate.We subsequently set out to identify expanding and contracting gene families within P. pachyrhizi. To this end, a phylogenetic tree of 17 selected fungal species was built using 408 conserved orthologous markers. We estimated that P. pachyrhizi diverged from its most recent common ancestor 123.2−145.3 million years ago , a time frame that coincides with the evolution of the Pucciniales. We derived gene families including orthologues and paralogues from a diverse set of plant-interacting fungi and identified gene gains and losses using computational analysis of gene family evolution. Genomes of rust fungi including P. pachyrhizi underwent more extensive gene losses than gains, as would be anticipated for obligate biotrophic parasites . In total, we identified 2,366 contracted families and 833 expanding families within UFV02, including 792 and 669 families with PFAM domains, respectively. The most striking and significant contraction in the P. pachyrhizi genome is related to DEAH helicase which is involved in many cellular processes, e.g., RNA metabolism and ribosome biogenesis . In contrast, significant expansions in 12 gene families were found, including genes encoding glutamate synthase, GMC oxidoreductase and CHROMO domain-containing proteins .

Both variables showed a close match between simulated and measured values

The first scenario consisted of applying the same amount of fertilizer spread across all irrigation pulses , except for the last irrigation pulse to enable flushing. The second scenario consisted of continuous irrigation of the same duration and irrigation amount as under pulsed treatments, with fertigation at all times , except for the same period of flushing at the end of irrigation. The fertigation scheme in PF1, PF2, PF3 and continuous scenarios was assumed to start from 17 August 2010. All fertigation simulations were run as for the irrigation experiment, that is for 29 days .The water content distribution in the soil reflects water availability to plants, and plays a crucial role in water movement through and out of the root zone. Volumetric water contents simulated by HYDRUS 2D/3D are compared in Fig. 5 with the measured values obtained using EnviroSCAN probes 15 cm away from the dripper. Simulated values matched measured values well, both spatially and temporally. However, deviations between simulated and measured values were observed at day 19 of simulation, particularly in the upper 50 cm of the soil profile; at later times this difference was not observed. Simulated and observed daily and cumulative drainage are compared in Figs. 6 and 7, respectively. It can be seen that simulated daily drainage remained slightly below observed values , except for the initial higher leaching on day 1. However,vertical hydroponic nft system the total drainage observed in the lysimeter was matched closely by the model.

The high peak on day represents the effect of high rainfall on that day, which also was very well predicted by the model. However, the cumulative drainage remained slightly over predicted during the initial 15 days, after which the simulated and observed values matched well. Model evaluation was performed using a number of model performance parameters calculated using measured and model generated soil water contents . The mean absolute error varied from 0.006 to 0.22 cm3 cm−3 and the root mean square error ranged between 0.007 and 0.028 cm3 cm−3, which indicated small deviations between measured and simulated values. However,the maximum values of MAE and RMSE were observed at day 19, confirming the deviations shown in Fig. 5 at this time. However, the values of paired t-test between measured and simulated water contents showed insignificant differences at 5%level of significance at all times.Values of the coefficient of determination varied between 0.68 and 0.96, indicating a reliable generation of water contents by the model at all days of simulations. Similarly, the Nash and Sutcliffe efficiency coefficient values ranged from 0.17 to 0.96, indicating a good performance of the model for the prediction of water contents in this study.However,the relative efficiency value at day 19 reveals unsatisfactory performance of the model at that point according to the criteria suggested by Moriasi et al. . The values of MAE, RMSE, r2, E, and RE for the drainage flux were 2.87, 4.14, 0.97, 0.94, and 0.78 , respectively, which also showed a robust performance of the model for drainage fluxes from the lysimeter. The close match of both water contents and drainage fluxes indicates that the HYDRUS 2D/3D software can be successfully used to predict water movement and drainage fluxes in a lysimeter planted with a citrus tree. Other studies have also reported good performance of this software for various soil, water, and crop conditions under pressurised irrigation systems . Simulated water balance components over the 29 day experimental period are shown in Table 3. It can be seen that simulated drainage, which is similar to the amount measured in the lysimeter, represents 48.9% of the total water balance.

A much higher seasonal drainage has been reported for a lysimeter planted with an orange tree in a fine sandy soil . High drainage is bound to occur in highly permeable, coarse textured soils, such as the sand/loamy soil used in this study, where water drains easily and quickly from the root zone because gravity dominates over capillarity . However, Sluggett estimated deep drainage in the range of 6.1–37.2% under citrus trees growing in light textured soils in the Sunraysia region of Australia. A major contributor to the high drainage measured in this experiment was the high amount of water applied, mostly as a result of large rainfall events. Simulated plant water uptake was estimated to be 40% of the water application, indicating low irrigation efficiency of the drip system. The daily plant uptake varied from 1.2 to 3.14 mm . However, plant uptake is a very complex process, and depends on a number of parameters describing the root and canopy development. Since the HYDRUS model does not support a dynamic behaviour of the root system and considers only the static root parameters, root uptake was optimised on the basis of a changing transpiration rate over time. Additionally, since in the present study we dealt with a tree, for which the root distribution development over time is not as fast as observed for seasonal crops like cereals, the root development was considered relatively constant for the modelling purpose. Hence, a static root distribution and variable atmospheric conditions produced a good approximation of plant uptake, as has been revealed in a number of earlier studies that used HYDRUS for modelling purposes Simulated distribution of nitrate at selected times after commencement of fertigation is shown in Fig. 8. Concentration of NO3-N was maximum at the centre of the plume below the dripper, with a gradual decrease in N concentration towards the outer boundaries of the plume. Subsequent irrigation and fertigation pulses resulted in enlargement of the plume, with a rapid lateral and vertical movement of NO3-N. It is worth noticing that after 15 days of fertigation all nitrate still remained in the lysimeter, reaching a depth of 70 cm. The maximum nitrate concentration at this time was at 20 cm. The simulated NO3-N uptake accounted only for 25.5% of applied nitrogen .

The remaining nitrogen was still available in the soil for plant uptake, provided it was not transformed by soil biological processes. No nitrate leaching was predicted by the model within this initial 15 day period. The total seasonal recovery of applied N amounts to 42.1% by the orange tree, while 7.7% of added NO3-N was retained in the soil atthe end of the season. These results agree with the findings of Paramasivam et al. who reported 40–53% nitrogen uptake in afield experiment on citrus. Similarly, Boaretto et al. showed 36% recovery of applied nitrogen by an orange tree in a lysimeter. The seasonal distribution of nitrate in the soil at 30-day intervals after the fertigation commencement is shown in Fig. 9.It can be seen that nitrate rapidly moved downwards and dispersed in the lysimeter, reaching a depth of 95 cm after 30 days. However, the zone of the maximum concentration remained close to the soil surface. Subsequent fertigation pulses further pushed N near to the leaching outlet at 60 days and N dispersed throughout the lysimeter, beyond which regular N leaching was observed with subsequent fertigations. However, the concentration of N remained much higher in the upper soil depth till 180 days of fertigation, enabling its continued uptake by the orange tree. The nitrogen concentration thereafter reduced drastically in the upper zone as a result of the withdrawal of fertigation after 195 days of simulation . At 210 days after commencement of fertigation ,nft hydroponic system the NO3-N concentration in the domain ranged between 0 and 0.4 mg cm−3, and continued to decline until it completely moved out of the upper 40 cm soil depth at 270 days. At the end of the simulation , only a very small amount of nitrate remained in the lysimeter, with higher concentration occurring at the bottom of the lysimeter , indicating higher vulnerability of this N to leaching. Major leaching of NO3-N took place after 90 days of simulation, amounting to 61%of total N leaching between 90 and 180 days , which corresponds to heavy precipitation of 95 mm on day 115 and 68 mm on day 152 of simulation. Paramasivam et al. and Nakamura et al. also reported that unexpectedly prolonged irrigation or high rainfall following fertilizer applications led to higher NO3-N leaching losses.

Total nitrate leaching amounted to 50.2% of the N applied as fertilizer . Nitrate losses of similar magnitude have also been reported by Syvertsen and Sax and Boman and Battikhi in a lysimeter grown orange tree. On the other hand, low NO3-N leaching losses ranging from 2 to 16% of the applied nitrogen have been reported in some studies on citrus . The migration of nitrate to deeper layers is highly dependent on the amount of irrigation and rainfall, as this is the driving force moving nitrate out of the root zone. Lower nitrate leaching estimated in this study may have been a consequence of improved irrigation and fertilizer management through the drip system. Hence improved water efficiency under drip irrigation, by reducing percolation and evaporationlosses, can contribute considerably towards environmentally safer fertilizer applications . In addition to the factors discussed above, a choice of appropriate source, amount, frequency, and timing of fertilizer applications and the rate of N transformation into NO3 are other important factors that determine the amount of NO3-N leaching out of the vadose zone .Temporal distribution of nitrate for different fertigation scenarios is presented in Fig. 11.Although nitrate movement appears to be similar in all scenarios, small differences can be observed in nitrate distribution in the soil for some scenarios. In scenarios PF and PF3, in which fertilizer was applied with all pulses in low concentrations or towards the end of irrigation, the N concentration after 2, 7, and 14 days was slightly higher in the centre of the plume where root activity was at a maximum. However, the nutrient uptake varied within a narrow range under normal irrigation , indicating an insignificant impact of fertigation timing under conditions experienced in our lysimeter study. Contrary to this, Hanson et al. reported 14% higher nitrate uptake when fertilizer was applied at the end of the irrigation event in a HYDRUS simulation that was based on historical irrigation and fertigation data. A similar observation was also made by Paramasivam et al. and Alva et al. in field experiments. Gärdenäs et al. also concluded that fertigation applied towards the end of the irrigation cycle generally reduces the potential for nitrate leaching under micro-irrigation systems, with the exception of clayey soils.A short fertigation pulse used in our study, as compared to the other studies, may have reduced differences among various scenarios. However, these results imply that fertigation in a short pulse towards the end of the irrigation event or low concentration fertigation with all pulses could increase the efficiency of nitrogen fertigation as compared to other options. Nitrate distribution in the domain after 21 and 28 days were similar in all scenarios , and all differences disappeared by 21 days of simulation. It can be shown that while nitrate distribution varied during one application phase, they were similar for all scenarios at the end of each irrigation cycle. Also, nitrate moved to a similar soil depth after 28 days in all scenarios. These scenarios did not produce any NO3-N leaching because of the short simulation period. A comparison of nitrate uptake between pulsed and continuous irrigations revealed that scenarios with pulsed irrigation had almost alike nitrate uptake as fertigation with continuous irrigation. Similar results were obtained in scenarios with different irrigation quantities. A negligible impact of pulsing on moisture distribution pattern and drainage has been reported in earlier studies for different dripper discharge rates and spacings . This observation further confirms that pulsing has little impact on solute distribution in the soil under optimal irrigation applications as compared to continuous irrigation.Modelling simulations were also performed to evaluate the impact of variable irrigation applications on nitrate movement for scenarios discussed above . It can be seen that plant NO3- N uptake gradually reduced as the amount of irrigation increased. The nitrogen uptake efficiency for the 50% irrigation treatment varied from 55.3 to 56.2% for all scenarios of fertilizer applications, which was about 8.5% higher than uptake recorded for the normal irrigation . On the other hand, a higher amount of irrigation than normal reduced nitrate uptake of an orange tree by further 3.4–3.6%. At the same time, the zone of maximum nitrate concentration moved to a depth of 40–60 cm , where root uptake decreased exponentially due to the reduction in root density.

How Often To Run Pump On Nft System

In an NFT hydroponic system, the pump should run continuously to maintain a consistent flow of nutrient solution over the roots of the plants. The continuous flow ensures that the plants receive a constant supply of water and nutrients while allowing for proper oxygenation of the roots.

Running the pump continuously helps prevent the roots from drying out and ensures a consistent nutrient delivery. It also aids in maintaining a stable root zone temperature. The continuous flow of nutrient solution in the NFT channels creates a thin film of liquid that flows over the roots, providing them with the necessary moisture and nutrients.

Therefore, it is recommended to run the pump in an NFT system 24 hours a day, seven days a week. This ensures that the plants receive a consistent supply of nutrient solution and promotes healthy growth. However, it’s important to monitor the nutrient solution levels and the overall health of the plants regularly to ensure optimal conditions and make any necessary adjustments.

Ways To Grow Hydroponic Cucumbers

Cucumbers can be successfully grown using various hydroponic methods. Here are a few ways to grow hydroponic cucumbers:

Nutrient Film Technique (NFT): Cucumbers thrive in NFT systems. Set up sloped channels or troughs for the plants to sit in, allowing a thin film of nutrient-rich water to flow continuously over the roots. Ensure proper support for the cucumber vines as they grow, as they can become heavy.
Deep Water Culture (DWC): DWC is another suitable method for growing cucumbers hydroponically. Use floating rafts or platforms to support the cucumber plants with their roots submerged in the nutrient solution. Oxygenate the solution adequately to promote healthy root growth.
Drip System: Drip irrigation works well for cucumbers. Place drip emitters near the base of each plant, providing a slow and steady supply of nutrient solution directly to the root zone. This method ensures efficient nutrient delivery while avoiding excessive moisture.
Aeroponics: Although less commonly used for cucumbers, aeroponics can be experimented with. Suspended cucumber roots in air and periodically mist them with a nutrient solution. Ensure that the mist droplets reach the roots for nutrient absorption.
Tower Gardens or Vertical Systems: Cucumbers can be grown in vertical hydroponic systems, utilizing tower gardens or stacked layers. These systems optimize space by growing plants vertically and provide support for the cucumber vines to climb as they grow.
Greenhouse Hydroponics: Hydroponic cucumber production is often done in controlled greenhouse environments. Greenhouses offer ideal conditions, including temperature and humidity control, for cucumbers to thrive. Various hydroponic systems, such as NFT or DWC, can be implemented within a greenhouse setup.

Remember to select cucumber varieties suitable for hydroponic cultivation, maintain proper nutrient balance, monitor pH and EC levels, provide adequate support for the plants, and ensure proper lighting and ventilation for optimal growth.

25 Litre Large Plastic Container Plant Pots

25-litre large plastic container plant pots are ideal for accommodating plants that require more space for root development or have larger root systems. These pots are commonly used for growing trees, shrubs, and other sizable plants. Here are some key features and considerations regarding 25-litre large plastic container plant pots:

Size: With a capacity of 25 litres, these pots provide ample room for plants to establish a healthy root system and grow to a significant size.
Material: The pots are typically made of durable plastic, such as polypropylene or high-density polyethylene (HDPE), that is resistant to cracking, breaking, and UV degradation. This ensures their longevity and suitability for outdoor use.
Drainage: Adequate drainage is crucial for plant health. Look for pots with sufficient drainage holes at the bottom to prevent waterlogging and promote healthy root growth.
Stability: Larger pots tend to be heavier, providing increased stability and resistance to tipping over in windy conditions. However, keep in mind that once filled with soil and plants, these containers can be challenging to move.
Portability: While these pots may be heavier and less portable than smaller options, they can still be moved with some effort. Consider placing them on plant caddies or using pot trolleys to facilitate transportation when necessary.
Reusability: Plastic containers are reusable and can be used for multiple planting seasons. Proper cleaning and disinfection between uses are recommended to prevent the spread of diseases or pests.
Maintenance: Plastic pots are relatively low-maintenance. They are easy to clean and maintain, and they resist fungal growth. However, over time, they may show signs of wear and tear, and if they become damaged, replacement may be necessary.

When purchasing 25-litre large plastic container plant pots, you can find them at garden centers, nurseries, or online gardening stores. Consider the specific needs of the plants you intend to grow and ensure that the pot size aligns with their growth requirements.

How Much Land is Required for a Profitable Blueberry Farm

The amount of land required for a profitable blueberry farm can vary depending on several factors, including the blueberry variety, planting density, management practices, market demand,25 liter plant pot and the scale of your operation. Here are a few considerations to help you estimate the land requirement:

Planting Density: Blueberries can be planted at different densities, ranging from 1,000 to 3,000 plants per acre (2,500 to 7,400 plants per hectare) or even higher for some high-density systems. The planting density you choose will depend on factors like the variety, management system (conventional or high-density), and intended yield.
Yield per Plant: The yield per blueberry plant can also vary based on various factors, such as age, variety, pruning, fertilization, and overall management. It’s essential to consider the potential yield per plant to estimate the overall yield and profitability of your farm.
Market Demand: Assess the local market demand for blueberries. Consider factors such as consumer preferences, competition, and potential market outlets (wholesale, direct-to-consumer, value-added products). Understanding the market demand will help determine the quantity of blueberries you need to produce and the scale of your operation.
Profitability Analysis: Conduct a comprehensive profitability analysis to estimate the revenue and expenses associated with blueberry farming. Consider costs related to land acquisition or lease, plants, labor, equipment, irrigation, fertilizers, pest management, marketing, and other operational expenses. This analysis will help you determine the scale of the operation required to achieve profitability and the corresponding land area.
Crop Rotation and Diversity: Blueberries benefit from crop rotation to manage soil health and reduce disease pressure. Plan for crop rotation and consider the land area required for this purpose.
Expansion Potential: Consider your long-term goals and the potential for expanding your blueberry farm. If you plan to expand in the future, it’s advisable to secure land that can accommodate your future growth.

It’s challenging to provide an exact land requirement as it varies depending on several factors. However, as a rough estimate,square plant pots a small-scale blueberry farm with around 1-2 acres (0.4-0.8 hectares) can be a starting point for a profitable operation. Larger commercial blueberry farms can span tens or hundreds of acres (hectares) or more.

It’s crucial to conduct thorough market research, feasibility studies, and consult with local agricultural extension services or experienced blueberry growers in your area to get more precise estimates based on your specific circumstances and goals.

How Tall Does Lettuce Grow In Nft System

In an NFT (Nutrient Film Technique) hydroponic system, the height that lettuce can grow largely depends on the specific variety of lettuce and the conditions provided within the system. However, lettuce generally doesn’t grow to great heights compared to other plants.

Most lettuce varieties are considered leafy greens and have a compact growth habit. Under optimal conditions, lettuce typically reaches a height of 8 to 12 inches (20 to 30 centimeters). However, there are some varieties, such as romaine lettuce, that can grow slightly taller, reaching around 18 inches (45 centimeters) or more.

It’s important to note that in an NFT system, the focus is primarily on the growth and development of the leafy parts of the plant, rather than its overall height. Lettuce is typically harvested when the leaves have reached a desired size and before they start to bolt (produce flowers and go to seed). Regular harvesting of outer leaves promotes continuous growth and allows the plant to produce new leaves.

Maintaining proper nutrient levels, light intensity, and temperature within the NFT system is crucial to ensure optimal growth and prevent any potential issues that may limit lettuce height. Monitoring and adjusting these parameters based on the specific variety and environmental conditions will help you achieve the best results.

Build Your Own Nft Hydroponic System

Building your own NFT (Nutrient Film Technique) hydroponic system for growing plants is an exciting project. NFT systems are efficient and effective for growing a variety of plants, including herbs, leafy greens, and even strawberries. Here’s a general guide to help you build your own NFT hydroponic system:

Materials you’ll need:
- NFT channels or gutters: These are typically made of PVC or plastic and provide a channel for nutrient-rich water to flow through.
- Water reservoir: A container to hold the nutrient solution that will be circulated through the NFT system.
- Submersible water pump: This will pump the nutrient solution from the reservoir to the NFT channels.
- Tubing and fittings: Connect the pump to the NFT channels and allow the water to circulate properly.
- Growing pots or net cups: These will hold the plants in place and allow the roots to access the flowing nutrient solution.
- Growing medium: Choose a medium that is suitable for NFT systems, such as rockwool cubes or grow plugs.
- Nutrient solution: A balanced mix of hydroponic nutrients suitable for the plants you intend to grow.
- Timer: Use a timer to control the pump’s schedule, ensuring regular cycles of nutrient flow.
Setup:
- Determine the size and layout of your NFT system based on the available space and the number of plants you want to grow.
- Install the NFT channels or gutters at a slight angle, allowing the nutrient solution to flow and create a thin film along the bottom of the channel.
- Connect the water pump to the water reservoir using tubing and fittings. Ensure the pump is submerged in the nutrient solution.
- Position the pump in a way that allows it to push the solution up to the highest point of the NFT channels, and let it flow down by gravity.
- Place the growing pots or net cups in the NFT channels, ensuring the roots will hang down into the flowing nutrient solution.
- Fill the pots or net cups with the chosen growing medium, such as rockwool cubes or grow plugs.
- Set up the timer to turn on the pump for a specific duration and frequency, allowing the nutrient solution to flow through the NFT channels and then drain back into the reservoir.
Nutrient solution and maintenance:
- Mix the appropriate hydroponic nutrient solution according to the instructions on the nutrient product.
- Monitor the pH level and adjust it to the optimal range for your plants. Most plants prefer a pH range between 5.5 and 6.5.
- Regularly check the nutrient solution levels in the reservoir and maintain the appropriate concentration by adding fresh solution or adjusting as needed.
- Inspect the system regularly to ensure there are no clogs or leaks, and make any necessary adjustments.
- Prune and maintain your plants as they grow, removing any dead leaves or overcrowded growth.

Remember that building and maintaining a hydroponic system requires attention to detail and ongoing monitoring. It’s essential to research the specific requirements of the plants you intend to grow, as different plants have varying nutritional needs and growth habits. Consulting resources and guides on NFT hydroponic systems can provide you with more detailed instructions and troubleshooting tips to maximize your success.

We are currently evaluating the effectiveness of five entomopathogenic fungus strains

The resolution of the present study is relatively low compared to the 70% resolution reported by Fazekas et al. or other plant groups . Factors specific to the evolution of the Pulsatilla and/or the sampling strategy of this study may affect the ability to discriminate between species. Such factors include incomplete lineage sorting and hybridization, the rapid radiation of Pulsatilla species, the variation present at the barcode loci, and the sampling density used in this study. Unlike animal species, many plant species have paraphyletic or polyphyletic origins due to the higher frequency of reticulate evolution, which is facilitated by hybridization and polyploidization . Given that this is the case, barcoding based solely on plastid markers may not reliably distinguish species. For example, in our study, some species are resolved to paraphyletic groups, such as P. patens. In these cases, the use of nuclear DNA sequences may improve the resolution among plant species because nuclear loci have higher overall synonymous substitution rates, thus making nuclear markers such as ITS more sensitive. In our study, P. patens samples, and formed a monophyletic group with sample P. latifolia. However, these samples were not clustered together by chloroplast marker data .Manipulating the innate immune system of insects as a means of inhibiting vector acquisition of pathogens is currently being explored in many insect vectors of human pathogens. To apply these techniques to hemipteran vectors of plant pathogens, the immune systems of these insects must first be understood. The two hemipterans that have been investigated, the pea aphid and brown plant hopper,square pot have differing immune capabilities; with the brown plant hopper having a robust immune system similar to other insects; while the pea aphid has a drastically reduced immune system.

To identify if immune manipulation could be a technique used to inhibit the Asian citrus psyllid transmission of Candidatus Liberibacter asiaticus , we annotated the immune genes of ACP and exposed ACP to different classes of bacteria. Genome annotation revealed a substantially reduced immune system in ACP with an absence of recognition proteins in the classes PGRP and GNBP, the majority of the IMD pathway, and few genes for antimicrobial effectors. These results suggest that ACP have a particularly reduced immune response against gram-negative bacteria. When ACP were exposed to either gram-negative bacteria or grampositive bacteria through oral infections or cuticular punctures, significantly increased mortality was observed in response to gramnegative bacteria. Taken together, the genetic data and the controlled infection results indicate that ACP are not able to detect or eliminate gram-negative bacteria such as CLas. Although innate immune manipulation may have limited utility for inhibiting CLas acquisition by ACP based on these findings, microbial insecticides may prove to be an effective control technique for ACP. Currently, HLB is associated with Candidatus Liberibacter spp., although several phytoplasmas have been found in citrus showing HLBlike symptoms. The aim of this study was to determine if, in addition to Ca. L. asiaticus , phytoplasma species are also associated with HLB in citrus of Mexico. Citrus plants showing HLB-like symptoms were collected in the Mexican States of Nayarit, Colima, and Sinaloa between August 2011 and September 2012. Samples were evaluated for CP and CLas by nested-PCR and conventional PCR, respectively. For actual RFLP, phytoplasma fragments were digested with restriction endonucleases and fractionated using a QIAxcel system . Virtual RFLP analysis was performed on the 16SrDNA sequences using the virtual gel plotting program pDRAW32 . Phylogenetic trees were constructed with the NeighborJoining method, using the MEGA program . A total of 86 HLB-symptomatic samples of Mexican lime , Persian lime , and Valencia sweet orange Osbeck were analyzed. Diffuse chlorosis, blotchy mottle and vein yellowing were symptoms observed, even though we were unable to clearly identify symptoms specifically associated with either bacterium alone or together. Fifty-four out of 86 citrus plants were positive for CLas, 20 were positive for CP, seven were found in mixed infections with both pathogens, and 19 samples were negative for CLas and phytoplasmas.

Actual and virtual RFLP analyses of the 16S rDNA sequences enabled us to classify two HLB phytoplasma strains as members of the aster yellows group Candidatus Phytoplasma asteris , the subgroup B from Nayarit and subgroup S from Colima and Sinaloa, which was confirmed by phylogenetic analysis. In addition, the partial CLas sequences were identical to the strains isolated from several countries affected by HLB. These results confirm the association of CPa with HLB in citrus in Mexico. Huanglongbing , presumably caused by Candidatus Liberibacter asiaticus , is a devastating citrus disease associated with of flavor in orange juice. Relative CLas titer was determined by analyzing the 16S rDNA gene and the LJ primer targeting the CLas prophage in fresh or processed/pasteurized orange juice using qPCR. A method was developed that yielded large quantities of highly purified DNA, using only a small quantity of juice, which was then compared to the sensory characteristics of the juice using linear regression. To this end, orange juice was centrifuged and the pellet was used for qPCR analysis. After lysing the cells in an alkaline and non-ionic detergent Tris-based buffer, the initial DNA precipitation step was accomplished using hexdecetyl trimethyl ammonium bromide and sodium chloride at low concentration to remove polysaccharides like pectin. A trained sensory panel analyzed the same juice for various descriptors for flavor, aroma, mouthfeel, and aftertaste and the chemical components of the juice were also evaluated. By using multiple dilutions of a known amount of standard DNA, a standard curve was generated for log concentration of sensory descriptors against Ct. The amount of nucleic acids in an unknown sample can then be calculated from its Ct value. For the Li primers, Ct values between 35 and 30 indicated a minor decrease in juice flavor quality, but below 30 indicated a more significant flavor decline. Values below 30 indicated flavor decline for the LJ primer in relation to sweet taste or overall orange flavor and conversely to typical HLB flavor scores . This technology also worked for off-flavor causing microorganisms and human pathogens, for example Alicyclobacillus acidoterrestris or Escherichia coli, respectively, in orange juice or apple cider.An opportunity to analyze spatial patterns to determine the underlying biological process has developed from the widespread sampling and testing of Asian citrus psyllids in Texas and California to locate early infections of Huanglongbing disease. The real-time polymerase chain reaction diagnostic methods used to detect the casual agents of HLB, Candidatus Liberibacter asiaticus, are set to run for 40 cycles. The reaction must surpass a set threshold prior to the completion of the run to be considered positive for the presence of CLas.

When diagnostic testing of ACP initially started in Texas and California, the threshold had to be reached at <32 cycles and then later was raised to <37 cycles. Currently,black plastic pots for plants reactions that surpass the threshold at 37 or more cycles have proven impossible to acquire confirmatory conventional PCR bands and DNA sequence data. Thus, these samples are classified as inconclusive. The question we are trying to answer is whether information in the Ct-values between 37 and 40 is also useful for predicting locations with HLBinfected citrus plants. Analysis of 2013 data from California indicates that psyllid samples with high Ct-values tend to be clustered at close ranges and then dispersed at larger scales. Clustering of samples with Ct-values in the 38-39 range is within 1 km of samples with Ct-values below 37. In both Texas and California, spatial clustering of psyllid samples with inconclusive Ct-values have been shown to cluster around known positive HLB-infected trees. One of the main obstacles in advancing the search for antimicrobials against ‘Candidatus Liberibacter asiaticus’ is the inability to culture this pathogen to perform classical growth inhibition tests. Consequently, we centered our research in the identification of chemicals that inactivate critical physiological pathways operating in this bacterium. To achieve our goal, the experimental design used in our laboratories consisted of a deep in silico multifactorial genomic analysis, followed by a conventional biophysical screening of selected targets. Using this approach, we identified new chemicals that targeted a transcriptional regulator belonging to the MarR-family in CLas. The DNA binding sequence of LdtR was identified via DNase I footprinting. In silico analyses using this binding site indicated that LdtR modulates the expression of several genes involved in cell division and cell wall biosynthesis. A gene of particular interest within the regulon is ldtP, which is predicted to encode for an L,D-transpeptidase. This enzyme is involved in the modification of the bacterial cell wall using an alternative pathway and it is resistant to the activity of b-lactam antibiotics. A recombinant LdtP enzyme has been purified and used as a target to identify potential enzymatic inhibitors. Herein, we present the impact of the identified new antimicrobials on the regulatory activity of LdtR and on the enzymatic activity of LdtP. The compounds identified represent an important advance in the identification of chemicals to be used as bactericidal in planta. The results herein described provide important insights to understand CLas regulatory networks and molecular foundations for the design of therapeutics for the treatment of this devastating disease. Since HLB was first reported in Brazil , the EEAOC implemented and strengthened different lines of work in four strategic areas. Provision of sanitized and certified vegetal material: EEAOC is the only sanitation center in northwestern Argentina and is in charge of providing sanitized and certified material to citrus nurseries. Observation and monitoring: a molecular diagnosis laboratory was set up for Candidatus Liberibacter spp. detection for both vegetal and insect samples.

We visually inspected citrus trees from 44 places located in Northwest Argentina and collected leaf samples, displaying HLB-similar symptoms, and insect samples. From 2005 to present, 12,500 samples were analyzed by qPCR TaqMan, 50% corresponded to citrus leaf, 46% to insect, and the remaining 4% to ornamental plants. All samples were negative. To date, there is no evidence that Candidatus Liberibacter spp. are in the NOA; although, 3,000 sticky traps for Diaphorina citri were set across the citrus area in Tucumán province and checked periodically. Furthermore, citrus plantation and alternative hosts in the urban area were monitored too. This monitoring was conducted on a weekly basis, but was intensified in spring and summer. In April 2011, the abovementioned activities resulted in the detection of 11 D. citri specimens on Murraya paniculata plants from the urban area. This case has remained under effective control by the national and provincial phytosanitary authorities and has not led to any subsequent reports. As for the citrus area, over 600,000 shoots and approximately 25,000 colored sticky traps have been checked without detecting the insect vector. These results prove that Tucumán province is free from D. citri. In the north of NOA , where the insect is present, the efficiency of 17 active ingredients was evaluated along with their correspondent fresh fruit residue analysis.One of the principal challenges in managing rapidly spreading epidemics is to identify optimal control strategies. How, when, where, and which control methods should be used to manage disease effectively. Epidemiological modelling can help by providing a means to integrate the current status of knowledge and to provide a set of tools to compare the effectiveness of different control scenarios. The epidemiological approach is also well-suited, taking account of uncertainties in order to inform a risk‐based management of disease. Drawing upon experience gained from modelling a range of emerging pests and pathogens including Huanglongbing and Asian Citrus Psyllid , I propose to show how an ‘epidemiological toolbox’ can be used to predict disease and vector spread, to analyse the effectiveness of control and to compare ‘what‐if’ scenarios for disease management. Successful control of disease requires us to match the scale of control with the inherent spatial and temporal scales of the epidemic. Identification and characterisation of the epidemic scales involve the formulation of mathematical models that capture the essential biological features of disease spread. The spatial distribution of hosts in the landscape is also important along with the effects of environmental variables and anthropomorphic activity, and the degree of stakeholder compliance. Using data for the spread of disease in Southern Gardens and data from psyllid traps in California, I propose to show how it is possible to extract signatures in the form of epidemiological parameters such as transmission rates and dispersal kernels for epidemic and vector spread.