Processing Tomato Fields Research Articles

Evapotranspiration estimation using high-resolution aerial imagery and pySEBAL for processing tomatoes

AbstractThe use of high-resolution aerial imagery for assessing actual crop evapotranspiration $$ \left({ET}_{a}\right)$$ holds the potential to optimize the use of limited water resources in agriculture. Despite this potential, there is a shortage of information regarding the effectiveness of energy balance algorithms, initially designed for satellite remote sensing in estimating $$ {ET}_{a}$$ using aerial imagery. This study addresses this gap by employing the remote sensing model pySEBAL (Surface Energy Balance Algorithm for Land) in conjunction with high-resolution aerial imagery to estimate $$ {ET}_{a}$$ for processing tomatoes. Throughout the 2021 growing season, an aircraft captured multispectral and thermal imagery over a processing tomato field near Esparto, California, USA. Simultaneously, an eddy covariance flux tower within the field measured high-frequency turbulent fluxes and low-frequency biometeorology variables essential for evaluating the energy balance. The comprehensive assessment of energy balance components, including $$ {ET}_{a}$$, yielded compelling evidence that pySEBAL accurately estimated $$ {ET}_{a}$$ at high spatial resolution. The root mean square error (RMSE) and normalized RMSE for various energy balance components were as follows: 33 W m− 2 (12%) for latent heat flux, 29 W m− 2 (35%) for sensible heat flux, 24 W m− 2 (4%) for net radiation, and 10 W m− 2 (15%) for soil heat flux. Additionally, $$ {ET}_{a}$$ exhibited an RMSE and NRMSE of 0.26 mm d− 1 (6%). Moreover, the spatial mapping of $$ {ET}_{a}$$ across the processing tomato field visually depicted the spatial variability associated with irrigation scheduling, crop development, areas affected by disease, and soil heterogeneity. This research underscores the value of high resolution spatial aerial imagery and pySEBAL algorithm for estimating $$ {ET}_{a}$$ variability in the field, a crucial aspect for guiding precision irrigation management and ensuring the optimal use of limited water resources in agriculture.

Biochar influences soil health but not yield in 3‐year processing tomato field trials

AbstractBiochar can deliver many agronomic benefits, though effects may be greatest in suboptimal agricultural soils. The objective of this study was to investigate biochar in prime agricultural soils in a Mediterranean climate. In 3‐year irrigated processing tomato (Solanum lycopersicum) field trials, in which three biochars were amended to a sandy and silt loam, biochar did not influence yield. Given the global policy focus on biochar for climate change mitigation and adaptation, however, it is essential to measure more than just agronomic parameters. To this end, a soil health assessment was conducted 2.5 years after biochar amendment. In the fertile silt loam and more nutrient‐limited sandy loam, biochars had a variable but positive effect on pH, electrical conductivity, soil potassium, water stable aggregation, and permanganate oxidizable carbon. There was no effect on soil moisture nor potentially mineralizable nitrogen or carbon. In the silt loam, there was no change in microbial biomass or phospholipid fatty acid (PLFA) composition. In the sandy loam, almond shell biochars were associated with a slight increase in total biomass, an increase in the ratio of fungal to bacteria PLFAs, and reductions in multiple PLFA ratios were typically interpreted as indicators of environmental stress. Results of this study demonstrate that biochar may deliver soil health benefits in agricultural soils in a Mediterranean climate. However, increased soil health does not necessarily engender increased agricultural productivity within a 3‐year period. Furthermore, increases in soil health indicators were inconsistent across soil and biochar types, underscoring the need for site‐ and material‐specific investigation.

Unraveling the reasons for failure to control Amaranthus albus: insights into herbicide application at different growth stages, temperature effect, and herbicide resistance on a regional scale.

This study investigates factors contributing Amaranthus albus control failure in processing tomato fields in northern Israel. The study region is characterized by a significant climate gradient from east to west, providing the opportunity to investigate the effect of critical elements of the agricultural environment, e.g., temperature. Eight populations were collected from commercial fields in this region. Post-emergence herbicide efficacy of metribuzin, a photosystem II inhibitor, and rimsulfuron, an acetolactate synthase (ALS) inhibitor, was assessed through dose-response analyses at various growth stages. Temperature effects on control efficacy and resistance mechanisms were also explored. Standard metribuzin dose (X) was ineffective on A. albus plants with more than six true-leaves, whereas 2X dose proved effective. Rimsulfuron at 16X dose was ineffective on plants with more than four true-leaves. We report here the first case of target site resistance to ALS inhibitors in A. albus, due to point mutation in the ALS gene (Pro197 to Leu). Furthermore, our findings suggest potential involvement of CYT P450 enzymes in enhanced metabolizing of rimsulfuron. An overall decrease in dry weight was observed in response to both herbicides at 16/22 °C (P < 0.0001). Rimsulfuron was effective against only one population when applied at 28/34 °C. A possible fitness cost associated with target site-resistant biotypes was observed under low temperature conditions, leading to effective control. This regional-scale study highlights the challenges faced by growers, emphasizes the need for adapting management practices to the local climatic conditions and lays the groundwork for implementing location-specific weed management strategies in commercial fields. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

A Tomato-Free Period Delays and Reduces Begomovirus Disease in Processing Tomato Fields in a Complex Agroecosystem in Central Brazil.

A mandatory tomato-free period (TFP) was implemented in the state of Goiás, Brazil, in 2007 to help manage diseases caused by whitefly-transmitted begomoviruses. The impact of the TFP was examined in five locations across three states in Central Brazil from 2013 to 2016. Surveys revealed significant differences in begomovirus disease incidence among locations, i.e., low in Guaíra-TFP and Patos de Minas-TFP; moderate-high in Itaberaí-TFP and Morrinhos-TFP; and high in the non-TFP (NTFP) control, Cristalina-NTFP. PCR tests and DNA sequencing were used to validate the symptoms and showed that all collected symptomatic plant samples were infected with tomato severe rugose virus (ToSRV), a common indigenous bipartite begomovirus. Early season surveys (20 to 40 days after transplants [DAT]) in Itaberaí-TFP and Morrinhos-TFP revealed significantly less begomovirus disease in fields established sooner after the TFP (0 to 2 months) compared with incidences in (i) equivalent early planted fields in the Cristalina-NTFP control and (ii) fields established longer after the end of the TFP (>2 to 5 months). Whitefly infestation of crops was detected year-round in all locations and years, and all tested adults were classified in the Bemisia tabaci MEAM1 cryptic species. Infestation levels were significantly higher during the summer but did not vary significantly among locations. Results of monthly monitoring of adult whiteflies for general begomovirus and ToSRV were positively correlated and were indicators of disease incidence in the field. Notably, ToSRV was not detected in whiteflies collected from nontomato plants during the TFP, and there was a longer lag period before detection in whiteflies collected from processing tomatoes for Itaberaí-TFP and Morrinhos-TFP compared with Cristalina-NTFP. Taken together with the low levels of ToSRV infection detected in potential nontomato reservoir hosts at all locations, our results revealed low levels of primary inoculum during the TFP. Thus, even in a complex agroecosystem with year-round whitefly infestation of crops, the TFP was beneficial due to delayed and reduced begomovirus disease pressure during a critical stage of plant development (first month) and for favoring low levels of primary inoculum. Thus, we concluded that the TFP should be part of a regional integrated pest management (IPM) program targeting ToSRV in Brazil.

Unusual outbreaks of curly top disease in processing tomato fields in northern California in 2021 and 2022 were caused by a rare strain of beet curly top virus and facilitated by extreme weather events

In the western United States, curly top disease (CTD) is caused by beet curly top virus (BCTV). In California, CTD causes economic loss to processing tomato production in central and southern areas but, historically, not in the north. Here, we document unusual CTD outbreaks in processing tomato fields in the northern production area in 2021 and 2022, and show that these were caused by the rare spinach curly top strain (BCTV-SpCT). These outbreaks were associated with proximity of fields to foothills and unusually hot, dry, and windy spring weather conditions, possibly by altering migrations of the beet leafhopper (BLH) vector from locations with BCTV-SpCT reservoirs. Support for this hypothesis came from the failure to observe CTD outbreaks and BLH migrations in 2023, when spring weather conditions were cool and wet. Our results show the climate-induced emergence of a rare plant virus strain to cause an economically important disease in a new crop and location.

Detecting soil water redistribution in subsurface drip irrigated processing tomatoes using electrical resistivity tomography, proximal sensing and hydrological modelling

In this study, multiple soil-plant-atmosphere continuum (SPAC) monitoring methodologies, including electrical resistivity tomography (ERT), proximal thermal sensing techniques, and micrometeorological data, were combined with two-dimensional (2-D) soil hydrological modelling using HYDRUS 2-D to explore the soil water redistribution, and infer the relative crop water status in a subsurface drip irrigated (SDI) processing tomato field located in California (Yolo County, USA). Specifically, time-lapse ERT surveys were performed at two transects distributed parallel and perpendicular, respectively, to the SDI line, during an irrigation event. The ERT results were compared to HYDRUS 2-D outputs and the relative differences were explained in the form of local heterogeneities in electrical resistivity (ER) changes, as a proxy for soil water content (SWC) variations. Concurrent simultaneous soil wetting and root water uptake during the last irrigation event of the season caused negligible changes in ER in the active root zone. Slight differences in ER were observed in the top 20 cm along the dripline, confirming that the emitter spacing is small enough to create a wetted strip along the processing tomato bed. These changes were also compared to SWC values measured with time domain reflectometry soil moisture sensors. A comparison between HYDRUS 2-D and ERT confirmed negligible changes in ER during irrigation due to simultaneous wetting and root water uptake processes. In addition, a good correlation was observed between the proximal sensed and the ERT results. Finally, the findings of this study underscore the necessity of using multiple methods for improving our knowledge of the SPAC system under real field conditions.

Nitrogen mineralization following fall‐applied compost to subsurface drip‐irrigated processing tomatoes in California

AbstractOrganic wastes diverted from landfills can reduce greenhouse gas emissions and are used as supplemental nutrient sources for agricultural crops after they are composted. In California, compost should be applied in the fall to processing tomatoes (Solanum lycopersicum L.) to avoid delaying field preparation and transplanting in the spring. The objective of this study was to determine soil nitrogen (N) mineralization following fall application of greenwaste compost (GWC) based on the change of mineral N during a 4 month in‐field buried bag soil incubation in 2 prospective subsurface drip‐irrigated processing tomato fields (PTF1 and PTF2). GWC rates of 0, 11, 22, and 34 Mg ha−1 were evaluated in PTF1 and PTF2 in October 2019. Very dry surface soil conditions in fall 2019 and the disruptive procedure used to prepare soil for in‐field incubation using the buried bag method led us to calculate net N mineralization after adjusting for the initial mineral N concentration of the unamended (0 Mg ha−1) control. The adjusted net N mineralization was significantly less in PTF1 (8.6 mg N kg−1) than PTF2 (16.4 mg N kg−1) and the estimated net N mineralization rate of the surface 0–15 cm soil depth following GWC application to PTF1 was less than PTF2 (1.6–1.9 vs. 2.3–3.1 kg N ha−1 week−1). In‐field incubation requires soil disturbance that likely affected N mineralization and additional research should consider the feasibility of using pretreatments or pre‐incubations to account for disruption to antecedent soil conditions.

A regional-scale study of the contribution of local, management and climate factors to the infestation of processing tomato fields with Amaranthus species

Determining the various factors affecting weed infestation in arable fields is complicated by the considerable spatiotemporal variability of agricultural systems. A possible solution lies in regional-scale studies of weeds in commercial fields to provide insights into the influence of field properties, climate, and weed management practices on the efficacy of weed management. The current study focused on Amaranthus species – noxious weeds infesting many crops worldwide – in processing tomato fields in Northern Israel, a geographical region characterized by a significant climate gradient. This gradient provides an ideal opportunity to study the effect of climate on weed infestation and management. The objective of this study was to investigate the associations between Amaranthus infestations and local (field properties), climate, and management factors in processing tomato fields. A survey of 103 commercial tomato fields was carried out in 2018 and 2019 throughout the four major tomato-growing areas in Northern Israel. The spatiotemporal change in infestation for fields surveyed both pre- and post-weed control was evaluated relative to management and climate variables. A bootstrapped model selection for beta regression models with varying dispersion was performed to determine factors associated with weed infestation before and after weed management. The analysis showed that the application of sulfosulfuron pre-planting, could potentially reduce Amaranthus infestation depending on environmental and local conditions of the field; management comprising of more intense control measures reduced infestation; and precipitation led to an increase in mean infestation when occurring before planting, but a decrease when occurring after weed management. In addition, the onset timing of weed control was found to be negatively correlated with precipitation occurring post-treatment. Our findings show that management actions are key factors in controlling Amaranthus infestation but that these actions are affected by the local climate conditions. Therefore, this work indicates the need for a regional-scale perspective when making weed management decisions.

Development of a Multi-Scale Tomato Yield Prediction Model in Azerbaijan Using Spectral Indices from Sentinel-2 Imagery

This paper presents the development and update of a multi-scale yield prediction model for processing tomatoes. The study was carried out under the EU-funded programme “Support to Development of a Rural Business Information System (RBIS)”, and the performance of the updated crop-specific yield prediction models and their generated predictions at regional and national levels are presented. The model was built using Sentinel-2 satellite imagery to obtain cumulative values of six (6) selected vegetation indices (VIs). The data were collected on five (5) different dates for processing tomato fields in the Khachmaz region of Azerbaijan during summer 2021 (June to August) at 10- to 13-day intervals. In addition, a targeted field sampling campaign was conducted on selected Khachmaz pilot fields towards the end of the growing season to assess the potential of Sentinel-2 data to determine yield variability in tomato fields. Finally, actual recorded yields were collected at the field level to build the yield prediction regression model and evaluate its performance at different spatial scales, ranging from single field to national level, as well as under different data availability scenarios (number of consecutive Sentinel-2 images used). The results showed a high degree of correlation between all implemented VIs and processing tomato yield, with a coefficient of determination of up to 0.89 for the NDVI, providing valuable information for future estimates of tomato production across multiple spatial scales. The developed prediction model could also be used in the agri-food sector for national yield estimates to support policy and regulatory decisions at the national level.

Modeling water and nitrogen dynamics from processing tomatoes under different management scenarios in the San Joaquin Valley of California

Study regionThe Southern San Joaquin Valley (SSJV), California. Four representative soil types were evaluated. Study focusEvaluation of regional scale hydrology and nitrogen (N) fate and transport requires a robust modeling framework that considers critical local scale environmental conditions and crop root zone physical processes. Two widely used yet conceptually and mechanistically different models, HYDRUS(2D/3D) and SWAT (Soil and Water Assessment Tool), were used to investigate water and N dynamics in processing tomato fields across a range of soil types and management scenarios over a 30-year period in the SSJV. New hydrological insights for the regionThis study implements a framework to evaluate a regional scale model against a field scale model and provides a framework for assessing percolation and N transport results from regional scale simulations in the absence of extensive field observations. Field scale models developed in HYDRUS (2D/3D) produced similar results to a regional-scale SWAT model in four specific soils in terms of responses to percolation and N losses as a function of varying N fertilizer and irrigation management practices. This model-to-model agreement at the local scale provides confidence in region-scale hydrological and N fate and transport findings, particularly in the absence of extensive field observations. Both models suggest that promoting conservation practices targeting the optimization of irrigation and fertilizer-N management would have a large impact in protecting regional groundwater quality.

Impacts of winter cover cropping on soil moisture and evapotranspiration in California's specialty crop fields may be minimal during winter months

As fresh water supplies become more unreliable, variable and expensive, the water-related implications of sustainable agriculture practices such as cover cropping are drawing increasing attention from California's agricultural communities. However, the adoption of winter cover cropping remains limited among specialty crop growers who face uncertainty regarding the water use of this practice. To investigate how winter cover crops affect soil water and evapotranspiration on farm fields, we studied three systems that span climatic and farming conditions in California's Central Valley: processing tomato fields with cover crop, almond orchards with cover crop, and almond orchards with native vegetation. From 2016 to 2019, we collected soil moisture data (3 years of neutron hydroprobe and gravimetric tests at 10 field sites) and evapotranspiration measurements (2 years at two of 10 sites) in winter cover cropped and control (clean-cultivated, bare ground) plots during winter months. Generally, there were not significant differences in soil moisture between cover cropped and control fields throughout or at the end of the winter seasons, while evapo-transpirative losses due to winter cover crops were negligible relative to clean-cultivated soil. Our results suggest that winter cover crops in the Central Valley may break even in terms of actual consumptive water use. California growers of high-value specialty crops can likely adopt winter cover cropping without altering their irrigation plans and management practices.

Migration Drives the Replacement of Xanthomonas perforans Races in the Absence of Widely Deployed Resistance.

Changes in Xanthomonas race and species composition causing bacterial spot of tomato have occurred throughout the world and are often associated with epidemics. Knowledge of bacterial population structure is key for resistance discovery and deployment. We surveyed Xanthomonas spp. composition from processing tomato fields in the Midwestern United States over a 4-year period between 2017 and 2020, compared these to strains collected previously, and found that X. perforans is currently the most prevalent species. We characterized 564 X. perforans isolates for sequence variation in avrXv3 to distinguish between race T3 and T4 and validated race designation using hypersensitive response (HR) assays for 106 isolates. Race T4 accounted for over 95% of X. perforans isolates collected in the Midwest between 2017 and 2020. Whole genome sequencing, Average Nucleotide Identity (ANI) analysis, core genome alignment and single nucleotide polymorphism (SNP) detection relative to a reference strain, and phylogenomic analysis suggest that the majority of Midwestern X. perforans strains collected between 2017 and 2020 were nearly identical, with greater than 99.99% ANI to X. perforans isolates collected from Collier County, Florida in 2012. These isolates shared a common SNP variant resulting an a premature stop codon in avrXv3. One sequenced isolate was identified with a deletion of avrXv3 and shared 99.99% ANI with a strain collected in Collier Co., Florida in 2006. A population shift to X. perforans T4 occurred in the absence of widely deployed resistance, with only 7% of tomato varieties tested having the resistant allele at the Xv3/Rx-4 locus. The persistence of nearly identical strains over multiple years suggests that migration led to the establishment of an endemic population. Our findings validate a genomics-based framework to track shifts in X. perforans populations due to migration, mutation, drift, or selection based on comparisons to 146 genomes.

Impacts of winter cover cropping on soil moisture and evapotranspiration in California's specialty crop fields may be minimal during winter months

As fresh water supplies become more unreliable, variable and expensive, the water-related implications of sustainable agriculture practices such as cover cropping are drawing increasing attention from California's agricultural communities. However, the adoption of winter cover cropping remains limited among specialty crop growers who face uncertainty regarding the water use of this practice. To investigate how winter cover crops affect soil water and evapotranspiration on farm fields, we studied three systems that span climatic and farming conditions in California's Central Valley: processing tomato fields with cover crop, almond orchards with cover crop, and almond orchards with native vegetation. From 2016 to 2019, we collected soil moisture data (3 years of neutron hydroprobe and gravimetric tests at 10 field sites) and evapotranspiration measurements (2 years at two of 10 sites) in winter cover cropped and control (clean-cultivated, bare ground) plots during winter months. Generally, there were not significant differences in soil moisture between cover cropped and control fields throughout or at the end of the winter seasons, while evapo-transpirative losses due to winter cover crops were negligible relative to clean-cultivated soil. Our results suggest that winter cover crops in the Central Valley may break even in terms of actual consumptive water use. California growers of high-value specialty crops can likely adopt winter cover cropping without altering their irrigation plans and management practices.

A Regional-Scale Study of the Contribution of Local, Management and Climate Factors to the Infestation of Processing Tomato Fields with Amaranthus Species

A Regional-Scale Study of the Contribution of Local, Management and Climate Factors to the Infestation of Processing Tomato Fields with Amaranthus Species

Proximity to subsurface drip irrigation emitters altered soil microbial communities in two commercial processing tomato fields

Subsurface drip irrigation (SDI) systems that deliver on-farm water savings can alter soil physico-chemical properties and reduce yields of processing tomatoes (Lycopersicon esculentum Mill). We hypothesized that soil microbial communities will also be modified with proximity to SDI emitters. Bacterial and fungal alpha and beta diversity were analysed using soil samples near to (within 15 cm) and distant from (45 cm laterally) SDI emitters in two adjacent fields used for commercial processing tomato production. One field had an established SDI system and four seasons of cropping under irrigation while the second field had a recently installed SDI system and one season of cropping. Bacterial diversity was significantly reduced near the emitter only in the recent SDI field. Bacterial community structure was also determined by proximity to the emitter in both fields. Several bacterial genera contributed to the dissimilarity of communities near and distant from the emitter including Acidobacteria subgroups 3 and 6, Gaiella, Gemmatimonas and Flavobacterium. Fungal alpha diversity was not significantly affected by emitter proximity in the two fields though it was lower overall in the established SDI field. Fungal community structure was also significantly different based on emitter proximity in both fields. Several fungal genera that contributed to the dissimilarity of communities near and distant from the emitter including Glomus, Preussia, Embellisia, Podospora, Gibberella and Plectosphaerella. Redundancy analysis identified pH, available phosphorus (Colwell P), potassium and magnesium as predictors of bacterial and fungal community structure in the two fields. This study has identified that SDI emitter proximity modifies the abundance of specific bacterial and fungal genera implicated in plant and soil health, thereby providing new information to improve the management of SDI systems for sustained yields of processing tomatoes.

Sown Wildflowers Enhance Habitats of Pollinators and Beneficial Arthropods in a Tomato Field Margin.

We evaluated the capacity of selected plants, sown along a processing tomato field margin in central Greece and natural vegetation, to attract beneficial and Hymenoptera pollinating insects and questioned whether they can distract pollinators from crop flowers. Measurements of flower cover and attracted pollinators and beneficial arthropods were recorded from early-May to mid-July, during the cultivation period of the crop. Flower cover was higher in the sown mixtures compared to natural vegetation and was positively correlated with the number of attracted pollinators. The sown Glebionis coronaria, Coriandrum sativum, Anethum graveolens, and Fagopyrum esculentum attracted mainly wild bees, which were the most abundant pollinating insects. In the natural vegetation, Rapistrum rugosum attracted mainly honeybees, while Asteraceae, Convolvulaceae, and Apiaceae species attracted wild bees. Beneficial arthropod abundance and diversity were higher in the sown mixture. Tomato flowers were visited by a small number of wild bees. Their number was not affected by the distance from the field margin, indicating no distraction effect from the sown or natural vegetation flowering plants. Our results suggest that selected flowering plants can improve the field margin habitats for pollinating insects and beneficial arthropods, but more work is needed to elucidate the effect on crop pollination.

Helicoverpa armigera Harm 1 Haplotype Predominates in the Heliothinae (Lepidoptera: Noctuidae) Complex Infesting Tomato Crops in Brazil.

Tomato (Solanum lycopersicum L.) is a natural host for the Helicoverpa-Chloridea (Lepidoptera: Noctuidae: Heliothinae) pest complex. The species Helicoverpa armigera (Hübner) was responsible for significant yield losses in several crops after its detection in Brazil. The morphology of its larval stage resembles common Heliothinae species, making pest control decisions difficult. The overall lack of studies on the Heliothinae associated with tomatoes in Brazil and the establishment of H. armigera in the country plus their recent outbreaks supported our investigation about the relative importance of the insects from the Helicoverpa-Chloridea complex in this vegetable crop. A nationwide survey was carried out across fresh-market and processing tomato fields. Molecular analyses targeting a segment of the mitochondrial cytochrome oxidase subunit I (mtCOI) gene and their sequence analyses indicated the presence of a pest complex, comprising the introduced species H. armigera and the indigenous species, Helicoverpa zea (Boddie), and Chloridea virescens (Fabricius). The Harm 1 haplotype of H. armigera was identified as the predominant Heliothinae pest infesting fresh-market tomatoes. The New World species Chloridea subflexa (Guenée) as well as the exotic Solanaceae-specific species Helicoverpa assulta (Guenée) were not found in our survey. Additional larvae surveys in processing tomato fields during 2013/2014 in Central Brazil also indicated H. armigera as the most abundant Heliothinae species (95%) together with H. zea (4.75%) and C. virescens (0.25%). The occurrence of distinct Helicoverpa species (which are potentially capable of interbreeding) indicates that novel crop management strategies will be necessary in order to minimize damages caused by this pest complex in tomatoes.

Agricultural managed aquifer recharge — water quality factors to consider

The resilience and productivity of California's agriculture is threatened by groundwater overdraft, reduction in aquifer water quality, increased land subsidence damage to infrastructure and an irreversible reduction in groundwater storage capacity. Intentionally flooding agricultural fields during winter — a practice referred to as agricultural managed aquifer recharge (AgMAR) — can help counteract overdraft. However, the potential for AgMAR to exacerbate nitrate/salt leaching and contamination of at-risk aquifers remains a critical concern. To quantify the risk of groundwater contamination with AgMAR, we took 30-foot-long soil cores in 12 almond orchards, processing tomato fields and wine grape vineyards on low- and high-permeability soils, measured nitrate and total dissolved solids concentrations and calculated stored nitrate-N. Wine grape vineyards on permeable soils had the least nitrate leaching risk observed. However, almond orchards and tomato fields could be leveraged for AgMAR if dedicated recharge sites were established and clean surface water used for recharge. Historical land use, current nitrogen management and soil permeability class are the main factors to consider before implementing AgMAR.

Development of an IPM Strategy for Thrips and Tomato spotted wilt virus in Processing Tomatoes in the Central Valley of California.

Tomato spotted wilt virus (TSWV; species Tomato spotted wilt orthotospovirus; genus Orthotospovirus; family Tospoviridae) is a thrips-transmitted virus that can cause substantial economic losses to many crops, including tomato (Solanum lycopersicum). Since 2005, TSWV emerged as an economically important virus of processing tomatoes in the Central Valley of California, in part due to increased populations of the primary thrips vector, western flower thrips (WFT; Frankliniella occidentalis). To develop an understanding of the epidemiology of TSWV in this region, population densities of WFT and incidence of TSWV were monitored in California’s processing tomato transplant-producing greenhouses and associated open fields from 2007 to 2013. Thrips were monitored with yellow sticky cards and in tomato flowers, whereas TSWV incidence was assessed with indicator plants and field surveys for virus symptoms. All thrips identified from processing tomato fields were WFT, and females were three-fold more abundant on sticky cards than males. Symptoms of TSWV infection were observed in all monitored processing tomato fields. Incidences of TSWV ranged from 1 to 20%, with highest incidence found in late-planted fields. There was no single primary inoculum source, and inoculum sources for thrips/TSWV varied depending on the production region. These results allowed us to develop a model for TSWV infection of processing tomatoes in the Central Valley of California. The model predicts that low levels of primary TSWV inoculum are amplified in early-planted tomatoes and other susceptible crops leading to highest levels of infection in later-planted fields, especially those with high thrips populations. Based upon these findings, an integrated pest management (IPM) strategy for TSWV in processing tomatoes in California was devised. This IPM strategy focuses on strategic field placement (identification of high-risk situations), planting TSWV- and thrips-free transplants, planting resistant varieties, monitoring for TSWV symptoms and thrips, roguing infected plants, thrips management targeting early generations, extensive sanitation after harvest, and strategic cropping to avoid overlap with winter bridge crops.

RTD-SEPs: Real-time detection of stem emerging points and classification of crop-weed for robotic weed control in producing tomato

A novel technique for enabling robotic weed control in a commercial processing tomato field having densely populated weeds is described. It is necessary to accurately locate the stem emerging points (SEPs) of crop plants for the successful application of a mechanical weeding actuator to remove weeds during automated weeding. However, it is a difficult and challenging task to locate the SEPs in complex natural scenarios such as when the main stem is occluded by weeds or crop foliage, the crop plants are lying on the soil surface, there are non-uniform planting bed conditions, or there is leaf damage due to insects etc. To overcome these challenges a novel crop signalling concept has been proposed to mark the crop plants at planting to make them machine-readable. Plants lacking this crop signal were classified as weeds and removed by the robotic weed knife actuator. A machine-vision algorithm was developed to analyse the seven views of the crop plants taken by camera with help of a specially designed imaging chamber and locate the SEPs of tomato plants, which was passed to the robotic weed knife control algorithm to remove weeds. The algorithm was successfully detected and located the main stems of tomato plants in outdoor environment with success rate of 99.19% while traveling at a speed of 3.2 km h−1 with a processing time for all views of 30 ms f−1.