Scholarly Works, Virginia Agricultural Experiment Station

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VAES faculty are located at 11 Agricultural Research and Extension Centers in Virginia and three colleges at Virginia Tech (CALS, CNRE, and VMRCVM).

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Copper-induced stress mechanisms in Erwinia amylovora: a comparative phenotypic and transcriptomic study using copper-sensitive and -tolerant strains
Santander, Ricardo Delgado; Aćimović, Srđan G. (American Society for Microbiology, 2025-10-22)
Erwinia amylovora causes fire blight of apple and pear. Among the management strategies, copper-based treatments are widely used to control the disease. However, the impact of copper on the pathogen is not uniform, and different strains show different tolerance levels to the heavy metal. Upon identifying E. amylovora strains with unusually high (EaR2 and Ea17) and intermediate (Ea19) copper sensitivity, we conducted phenotypic and transcriptomic analyses to understand the basis of these differences. The highly copper-sensitive strains EaR2 and Ea17 grew slower, showed increased sensitivity to paraquat and cadmium, and developed a characteristic copper-dependent overproduction of amylovoran and levan, with patterns not observed in strain Ea273, with regular copper tolerance. Copper sensitivity was also associated with higher copper-shock death rates after copper pre-exposure during growth. Transcriptomic analysis via RNA-Seq revealed similar responses to copper shock in EaR2 and Ea273 but very different transcriptomic responses during copper adaptation (prolonged growth with copper). EaR2 responded to copper adaptation with earlier activation of stress responses, exopolysaccharide biosynthesis pathways, and protein quality control systems, while reducing the expression of genes linked to iron uptake. Ea273 mostly displayed an activation of copper homeostasis-related genes, with a characteristic downregulation of histidine catabolism.
The dark side of avocados: a review of anthracnose and stem-end rot in postharvest fruit
Bernal, Valentina Valencia; Boeckman, Nathanial J.; Aćimović, Srđan G.; Khodadadi, Fatemeh (Frontiers, 2025-10-10)
Avocados are a key global fruit crop with rising international demand. However, postharvest diseases like anthracnose and stem-end rot (SER) can lead to significant economic losses, with incidence rates surpassing 30% in some regions. The latent nature of these infections complicates detection and management, affecting fruit quality and marketability. This review examines the pathogens behind these diseases, highlights advancements in detection technologies such as the use of biochemical and non-destructive methods and explores host-pathogen interactions through emerging omics approaches. We also evaluate the impact of preharvest practices on disease outcomes and current management strategies, including the growing potential of biological control agents, systemic resistance inducers, and natural product-based formulations as sustainable tools that complement synthetic fungicides. Finally, we highlight implications for fruit quality and consumer perception, along with critical research gaps, particularly the imbalance between anthracnose and SER studies in avocados, and outline future directions for improving postharvest disease control in avocados.
Enhancing Reproductive Performance by Boars Used for Pasture Mating
Estienne, Mark J. (Virginia Cooperative Extension, 2025-08-19)
Swine Production in Virginia: A Summary Using Data from the 2022 Census of Agriculture
Estienne, Mark J. (Virginia Cooperative Extension, 2025-07-09)
Using Artificial Insemination for Mating Sows to Heritage Breed Boars to Produce Crossbred Hogs Suitable for Niche Market Pork: A Demonstration Study
Estienne, Mark J. (Virginia Cooperative Extension, 2025-07-30)
Growth performance, hematology, and blood chemistry in weanling pigs consuming water recycled from a manure lagoon and then treated with a water and nitrogen management system
Estienne, Mark J.; Niblett, Tyler; Cumbie, William; Willinger, Rachel (Elsevier, 2025-12)
Decreasing availability of good quality water challenges sustainable pork production. One potential approach to mitigate this problem is treating wastewater recycled from manure so that it can be used for drinking. Such a system, however, requires that consumption not adversely affect pig health or economically important growth traits. The objective was to assess health and growth performance in pigs consuming water recycled from manure storage and then treated with a novel water and nitrogen management system before disinfection. Based on body weight, 72 weanling pigs were placed in 8 blocks of three pens each (three pigs/pen). Within block, pens were randomly assigned to one of three treatments: well water (control), 100 % water recycled from a manure lagoon and treated, or a 50/50 mixture of control and treated water (8 pens/treatment). Compared to pigs consuming 100 %-treated water, control pigs had greater (P < 0.05) red blood cell and hemoglobin concentrations, and hematocrit. During week 1 post-weaning, average daily gain (P < 0.05) and gain: feed (P < 0.05) were greater for pigs consuming the 100 %-treated water than the other groups. For the overall trial (Day 0–28), gain: feed was also greater (P < 0.05) for pigs consuming the 100 %-treated water compared to control pigs. Although hematological measures revealed evidence of elevated nitrate/nitrite in recycled wastewater, growth during the 28-day trial was not negatively impacted.
The regulatory cost burden on Atlantic Coast shellfish farms
Clark, Charles; van Senten, Jonathan; Engle, Carole (Oxford University Press, 2026)
Objective: The objective of this study was to measure the economic effects of regulations on Atlantic Coast shellfish farms, specifically to: a) measure the total regulatory cost burden on Atlantic Coast shellfish farms; b) measure the value of lost revenue resulting from regulatory action; and c) compare economic effects of the regulatory framework across Atlantic Coast states and farm sizes. Methods: A survey was conducted of shellfish producers in Atlantic Coast states (Connecticut, Delaware, Florida, Georgia, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, North Carolina, Rhode Island, South Carolina, and Virginia) in 2019-2022 that elicited detailed farm information on the farm-level regulatory compliance burden, production and marketing costs, sales, and revenue lost from regulations. Results: The aggregated regulatory costs on Atlantic Coast shellfish farms were $7.5M (2023 values), 7% of total farm costs and 4% of total farm sales, and averaged $28,849 per farm. Total lost revenue (from lost production and markets and thwarted expansion attempts) was $9.4M (2023 values) of which 89% was from thwarted expansion attempts. Small-scale farms had disproportionately greater negative economic effects than larger-scale farms largely because the majority of regulatory costs were fixed costs that increased the magnitude of economies of scale on Atlantic Coast shellfish farms. Regulations were ranked as the greatest challenge on Atlantic Coast shellfish farms, of which shellfish sanitation and legal costs associated with permitting and lease approval were the greatest costs. Conclusions: The regulatory framework for shellfish producers on the Atlantic Coast has increased costs of production, restricted access to markets, and prevented producers from expanding production to meet market demand. Streamlining the permit and leasing application processes to reduce redundancy, develop more efficient reporting systems that reduce duplication, and addressing user conflicts more effectively in coastal areas would likely improve the economic sustainability of Atlantic Coast shellfish farms.
The National Regulatory Cost Burden on US aquaculture farms
Engle, Carole R.; van Senten, Jonathan; Hegde, Shraddha; Kumar, Ganesh; Clark, Charles; Boldt, Noah; Fornshell, Gary; Hudson, Bobbi; Cassiano, Eric J.; DiMaggio, Matthew A. (Wiley, 2025-04)
Many government regulations have improved environmental and social quality of life in the United States, but others have resulted in negative consequences that exceed their benefits to society. This study estimated the total annual cost of regulatory compliance and lost revenue for US aquaculture. The total annual regulatory cost was $196 million (in 2023 USD), which accounted for 9%–30% of total annual costs, one of the top five costs of aquaculture production. Regulatory costs result in disproportionately greater per-unit costs of production on smaller-scale farms. Total annual lost revenue was $807 million (36% of total sales value), which resulted from lost sales and thwarted expansion opportunities from regulatory actions that either closed access to existing markets, forced reduced scales of production, or prevented attempts to expand production to meet existing demand for the farm's products. Accounting for multiplier effects, lost economic contributions were $1.4 billion annually, with >8000 jobs lost nationally from farms alone, not including associated supply chain partners. Well-designed regulations made use of best available science, participatory approaches to rule-making, sunset clauses for removal of outdated regulations, and market-based approaches. Pathways identified to improve regulatory efficiency included: (1) sunset clauses for each rule; (2) reward incentives (i.e., reduced testing frequency for farms with records of compliance) (3) standardized fish health testing requirements of sample size, farm-wide rather than lot testing, testing the most susceptible species/life stages; (4) non-lethal, multi-pathogen testing methods; (5) farm compensation for reverse externalities of avian predation; (6) appropriate risk management by experts to manage aquatic invasive species and pathogens; (7) training in aquaculture science, current farm practices, and appropriate, consistent, regulatory actions; (8) engagement with independent experts and producers throughout rule-making; (9) establishment of transparent appeals processes for farmers; (10) concurrent, not sequential review of permit requests by agencies; (11) long-term aquaculture literacy programs; and (12) an efficient, streamlined permitting and regulatory framework for mariculture.
Performance of ‘Honeycrisp’ Apple Trees on Several Size-Controlling Rootstocks in the 2014 NC-140 Rootstock Trial after Ten Years
Cline, J. A.; Autio, W.; Clements, J.; Cowgill, W.; Crassweller, R.; Einhorn, T.; Francescatto, P.; Gonzalez Nieto, L.; Hoover, E.; Lang, G.; Lordan, J.; Moran, R.; Muehlbauer, M.; Musacchi, S.; Parra Quezada, R.; Schupp, J.; Serra, S.; Sherif, Sherif; Robinson, T.; Wiepz, R.; Zandstra, J. (2025-09-17)
In 2014, a multi-year orchard experiment of apple Malus x domestica (Borkh) was established at 13 locations in Canada, Mexico, and the United States using ‘Honeycrisp’ as the scion. Seventeen dwarf and semi-dwarf rootstock genotypes were tested, specifically: Budagovsky.10 (B.10), the Cornell-Geneva rootstocks G.11, G.202, G.214, G.30, G.41, G.890, G.935, G.969, the Malling rootstocks M.7, MM.106, and the Vineland rootstocks V.1, V.5, V.6, and V.7. The industry standard Malling rootstocks M.26 EMLA and M.9-T337 were included for comparison purposes. Tree mortality, trunk cross-sectional area, tree canopy size, amount of rootstock suckering, yield, and fruit number were measured annually. All measured parameters were influenced by location and rootstock, and the interaction of these two factors was significant. Overall, after 10 years and averaged over all locations, rootstock vigor separated into three distinct rootstock classes: those similar to M.9-T337 (G.11), those similar to M.26 EMLA (G.935, G.41, B.10, G.214, G.969), and those more vigorous than M.26 EMLA (V.1, G.30, M.7, V.7, MM.106, V.6, G.890, V.5). G.202 performance was unusual and therefore was omitted from data analysis. Cumulative yields were generally greater on trees with the highest vigor. Averaged over all locations, all Geneva, Vineland, and Budagovsky rootstocks had cumulative yields higher than the industry standards M.9-T337 and M.26 EMLA. The newer rootstocks B.10, V.5, V.6, V.7 and all the Geneva rootstocks, had good to excellent cumulative yields. G.890 stood out as having exceptional cumulative yield among all the rootstock genotypes evaluated. Averaged over all locations, cumulative yield efficiency was greatest for M.9-T337 and all the Geneva rootstocks, as well as B.10. Overall, the strong rootstock by location interaction on cumulative yield observed in this trial illustrates the importance of testing rootstocks at a regional level. These results are reflective of orchard vigor and yields after 10 years and provide apple producers with performance indicators to make more informed decisions concerning rootstock selection for their orchard training systems and planting locations using a weak scion cultivar.
Multiomics analysis revealed the temporally common and specific molecular changes in Arabidopsis thaliana (L.) under salt stress
Chen, Zixuan; Ye, Chanjuan; Zeng, Yuan; Guo, Jie; Zhou, Xinqiao; Chen, Dagang; Liu, Juan; Liu, Chuanguang; Jaremko, Mariusz; Chen, Ke; Fan, Guoqiang (2025-11-19)
Salt stress is a major abiotic constraint that limits plant growth and productivity worldwide. In this study, we performed a comprehensive temporal analysis using transcriptomics (6 h), ribosome profiling (12 h), proteomics and phytohormone quantification (24 h), and metabolomics (48 h) to uncover the regulatory mechanisms in Arabidopsis thaliana underlying salt stress adaptation. Novel transcriptional regulators, including JAZ7, CBF4, bHLH92, and NAC041 that responded rapidly to early salt stress, were identified. At the post-transcriptional level, TAS1C and TAS2, along with chloroplast tRNAs (AtTRNR.1, AtTRNC, AtTRNV.1), were found to be translationally upregulated, suggesting a previously unrecognized role of organellar translation in stress response. At the protein level, chloroplast functional proteins, AtPSBA, AtRBCL, AtPSAA, AtPSAB, were revealed to respond to salt stress. Some functional proteins, including AtCER1, AtGGL19, and AtLEA14, with opposite trends between transcription and translation, highlighting the complexity of salt stress adaptation. Abscisic acid (ABA) was significantly upregulated, while jasmonic acid (JA) was dramatically suppressed, with AtOPR3 and JAZ7 identified as key regulatory nodes. Metabolomics analysis further showed that d-proline and 1-pyrroline-2-carboxylate accumulated at later stages, potentially contributing to increased salt stress resistance. Overall, these findings provide new insights into the temporal regulation of stress adaptation and identify candidate genes and metabolites that may serve as targets for improving salt tolerance in crops.
Effects of Clipping Heifer Hair Coats on Vaginal Temperatures and Performance of Fall-Born Heifers Stocked on Toxic Endophyte-Infected Tall Fescue During the Summer
Beard, Christopher T.; Swecker, William S.; Abaye, Ozzie; Pent, Gabriel J. (MDPI, 2025-11-12)
Achieving satisfactory levels of weight gain for developing replacement beef heifers is challenging when utilizing toxic endophyte-infected tall fescue (Schedonorus arundinaceus) as the primary forage. This is due to the intensifying impact of ergot alkaloids produced by the fungal endophyte on heifer heat stress in the summer. The purpose of this trial was to determine if clipping hair coats would reduce heat stress impacts experienced by fall-born heifers stocked on toxic endophyte-infected tall fescue. Heifers were randomly assigned to a control cohort and a clipped cohort. The heifers in the clipped treatment group were sheared along the body of the heifer. Vaginal temperature loggers were used to record core temperatures every ten minutes during several sampling periods. Hair coats on clipped heifers resembled hair coats of the control heifers by the conclusion of the 16-week trial. Average daily gains of the clipped heifers exceeded the average daily gains of the control heifers only in the first four-week period. There were no differences in seasonal average daily gain or pregnancy rates. Clipped heifers had cooler core temperatures by 0.2–0.3 °C in the morning compared to the control heifers. Clipping hair coats of heifers only provided short-term relief for cattle stocked on toxic endophyte-infected tall fescue.
Abiotic Factors Affecting Vector-Borne Plant Pathogen Complexes: Elevated CO2 and the Barley Yellow Dwarf Pathosystem
Parizad, Shirin; Yang, Jingya; Oeller, Liesl; Nikoukar, Atoosa; Liang, Xi; Rashed, Arash (MDPI, 2025-11-22)
Changes in atmospheric CO₂ are known to influence plant physiology, subsequently affecting the nature of their interactions with their biotic environment. Barley yellow dwarf virus (BYDV), one of the most widespread and damaging viruses of small grains, is transmitted by cereal aphids and has a broad range of cultivated and uncultivated hosts from the Poaceae family. Here, we examined the effects of elevated CO₂ on plant physiology, Rhopalosiphum padi L. performance, and the accumulation of BYDV (strain BYDV-PAV) in winter wheat (Triticum aestivum L.), foxtail barley (Hordeum jubatum L.), and green foxtail (Setaria viridis (L.) Beauv.). A growth chamber experiment was conducted under ambient (420 ppm) and elevated CO₂ (700 ppm) with aphid-infested and uninfested plants. Elevated CO₂ significantly increased total plant biomass in all species but did not affect aphid survival or reproduction. The root biomass of winter wheat and foxtail barley, but not green foxtail, increased under elevated CO₂. However, no significant effect of aphids/BYDV was detected on total plant biomass. Transpiration rates varied with host plant and aphid presence but were not affected by CO₂ level. Total water-soluble carbohydrate concentration was unaffected by CO₂ or aphids. BYDV-PAV accumulation varied by host plant species, with winter wheat having the highest virus titer, followed by foxtail barley and green foxtail. Virus titers were increased under elevated CO₂ in all host plant species. We demonstrated that uncultivated grasses are important reservoirs for both BYDV-PAV and the R. padi vector and suggested that elevated CO₂ may enhance virus accumulation across the evaluated host plants. This underscores the need to consider the role of non-crop hosts in developing management plans and/or predicting BYDV dynamics in small grains.
An AI-Enabled System for Automated Plant Detection and Site-Specific Fertilizer Application for Cotton Crops
Chouriya, Arjun; Soni, Peeyush; Chandel, Abhilash K.; Patel, Ajay Kumar (MDPI, 2025-10-08)
Typical fertilizer applicators are often restricted in performance due to non-uniformity in distribution, required labor and time intensiveness, high discharge rate, chemical input wastage, and fostering weed proliferation. To address this gap in production agriculture, an automated variable-rate fertilizer applicator was developed for the cotton crop that is based on deep learning-initiated electronic control unit (ECU). The applicator comprises (a) plant recognition unit (PRU) to capture and predict presence (or absence) of cotton plants using the YOLOv7 recognition model deployed on-board Raspberry Pi microprocessor (Wale, UK), and relay decision to a microcontroller; (b) an ECU to control stepper motor of fertilizer metering unit as per received cotton-detection signal from the PRU; and (c) fertilizer metering unit that delivers precisely metered granular fertilizer to the targeted cotton plant when corresponding stepper motor is triggered by the microcontroller. The trials were conducted in the laboratory on a custom testbed using artificial cotton plants, with the camera positioned 0.21 m ahead of the discharge tube and 16 cm above the plants. The system was evaluated at forward speeds ranging from 0.2 to 1.0 km/h under lighting levels of 3000, 5000, and 7000 lux to simulate varying illumination conditions in the field. Precision, recall, F1-score, and mAP of the plant recognition model were determined as 1.00 at 0.669 confidence, 0.97 at 0.000 confidence, 0.87 at 0.151 confidence, and 0.906 at 0.5 confidence, respectively. The mean absolute percent error (MAPE) of 6.15% and 9.1%, and mean absolute deviation (MAD) of 0.81 g/plant and 1.20 g/plant, on application of urea and Diammonium Phosphate (DAP), were observed, respectively. The statistical analysis showed no significant effect of the forward speed of the conveying system on fertilizer application rate (p > 0.05), thereby offering a uniform application throughout, independent of the forward speed. The developed fertilizer applicator enhances precision in site-specific applications, minimizes fertilizer wastage, and reduces labor requirements. Eventually, this fertilizer applicator placed the fertilizer near targeted plants as per the recommended dosage.
UAS-Based Spectral and Phenological Modeling for Sustainable Mechanization and Nutrient Management in Horticultural Crops
Suero, Alexis; Torres-Quezada, Emmanuel; López, Lorena; Reiter, Mark; Biscaia, Andre; Fuentes-Peñailillo, Fernando (MDPI, 2025-11-30)
Potatoes are an economically important crop in Virginia, USA, where growers must balance planting dates, nitrogen (N) management, and variable crop prices. Early planting exposes crops to low temperatures that limit growth, whereas late planting increases pest pressure and nutrient inefficiency. This study evaluated the effects of planting dates, N rates, and application timing on potato growth, yield, and pest incidence. We also assessed whether soil physicochemical properties could predict the presence of wireworms and plant-parasitic nematodes (PPNs) using complementary on-farm samples collected across Eastern Virginia between March and July 2023. Three planting dates (early-March, late-March, and early-April) were combined with five N rates (0, 146, 180, 213, and 247 kg N·ha⁻¹) under early- and late-application regimes. We collected data on plant emergence, flowering time, soil nitrate, biomass, tuber yield, pest damage, and UAS-derived metrics. Results showed that late-March planting with 180 kg N·ha⁻¹ achieved the highest gross profit while maintaining competitive yields (25.06 Mg·ha⁻¹), representing 24% and 6% improvements over traditional practices, respectively. Early-April planting produced the largest tubers, with a mean tuber weight 19% higher than the other planting dates. The Normalized Difference Red Edge Index (NDRE) was strongly correlated with N content in plant tissue (R² = 0.81; r ≈ 0.90), and UAS-derived plant area accurately predicted tuber yield 4–6 weeks before harvest (R² = 0.75). Wireworm damage was significantly higher in early-March plantings due to delayed insecticide application, while soil nitrate concentration and percent H saturation were identified as key predictors of wireworm presence. Although less effectively modeled due to limited sample size, PPN occurrence was influenced by potassium saturation and soil pH. Aligning planting dates and nitrogen applications with crop phenology, using growing degree days (GDD), enhanced nitrogen management, and yield prediction.
Evaluation of insecticide efficacy against diamondback moth and other lepidopteran pests in collards in Virginia, 2025
Sydnor, Taylore; Del Pozo-Valdivia, Alejandro; Kuhar, Thomas P. (Oxford University Press, 2025-01-20)
Levels of Salmonella enterica and Listeria monocytogenes in Alternative Irrigation Water Vary Based on Water Source on the Eastern Shore of Maryland
Acheamfour, Chanelle L.; Parveen, Salina; Hashem, Fawzy; Sharma, Manan; Gerdes, Megan E.; May, Eric B.; Rogers, Koriante; Haymaker, Joseph; Duncan, Rico; Foust, Derek; Taabodi, Maryam; Handy, Eric T.; East, Cheryl; Bradshaw, Rhodel; Kim, Seongyun; Micallef, Shirley A.; Callahan, Mary Theresa; Allard, Sarah; Anderson-Coughlin, Brienna; Craighead, Shani; Gartley, Samantha; Vanore, Adam; Kniel, Kalmia E.; Solaiman, Sultana; Bui, Anthony; Murray, Rianna; Craddock, Hillary A.; Kulkarni, Prachi; Goldstein, Rachel E. Rosenberg; Sapkota, Amy R. (American Society for Microbiology, 2021-10)
Irrigation water sources have been shown to harbor foodborne pathogens and could contribute to the outbreak of foodborne illness related to consumption of contaminated produce. Determining the probability of and the degree to which these irrigation water sources contain these pathogens is paramount. The purpose of this study was to determine the prevalence of Salmonella enterica and Listeria monocytogenes in alternative irrigation water sources. Water samples (n = 188) were collected over 2 years (2016 to 2018) from 2 reclaimed water plants, 3 nontidal freshwater rivers, and 1 tidal brackish river on Maryland’s Eastern Shore (ESM). Samples were collected by filtration using modified Moore swabs (MMS) and analyzed by culture methods. Pathogen levels were quantified using a modified most probable number (MPN) procedure with three different volumes (10 liters, 1 liter, and 0.1 liter). Overall, 65% (122/188) and 40% (76/188) of water samples were positive for S. enterica and L. monocytogenes, respectively. For both pathogens, MPN values ranged from 0.015 to 11 MPN/liter. Pathogen levels (MPN/liter) were significantly (P, 0.05) greater for the nontidal freshwater river sites and the tidal brackish river site than the reclaimed water sites. L. monocytogenes levels in water varied based on season. Detection of S. enterica was more likely with 10-liter filtration compared to 0.1-liter filtration. The physicochemical factors measured attributed only 6.4% of the constrained variance to the levels of both pathogens. This study shows clear variations in S. enterica and L. monocytogenes levels in irrigation water sources on ESM. IMPORTANCE In the last several decades, Maryland’s Eastern Shore has seen significant declines in groundwater levels. While this area is not currently experiencing drought conditions or water scarcity, this research represents a proactive approach. Efforts, to investigate the levels of pathogenic bacteria and the microbial quality of alternative irrigation water are important for sustainable irrigation practices into the future. This research will be used to determine the suitability of alternative irrigation water sources for use in fresh produce irrigation to conserve groundwater.
Variations in Bacterial Communities and Antibiotic Resistance Genes Across Diverse Recycled and Surface Water Irrigation Sources in the Mid-Atlantic and Southwest United States: A CONSERVE Two-Year Field Study
Malayil, Leena; Ramachandran, Padmini; Chattopadhyay, Suhana; Allard, Sarah M.; Bui, Anthony; Butron, Jicell; Callahan, Mary Theresa; Craddock, Hillary A.; Murray, Rianna; East, Cheryl; Sharma, Manan; Kniel, Kalmia; Micallef, Shirley A.; Hashem, Fawzy; Gerba, Charles P.; Ravishankar, Sadhana; Parveen, Salina; May, Eric; Handy, Eric; Kulkarni, Prachi; Anderson-Coughlin, Brienna; Craighead, Shani; Gartley, Samantha; Vanore, Adam; Duncan, Rico; Foust, Derek; Betancourt, Walter; Zhu, Libin; Mongodin, Emmanuel F.; Sapkota, Amir; Pop, Mihai; Haymaker, Joseph; Sapkota, Amy R. (American Chemical Society, 2022-11-01)
Reduced availability of agricultural water has spurred increased interest in using recycled irrigation water for U.S. food crop production. However, there are significant knowledge gaps concerning the microbiological quality of these water sources. To address these gaps, we used 16S rRNA gene and metagenomic sequencing to characterize taxonomic and functional variations (e.g., antimicrobial resistance) in bacterial communities across diverse recycled and surface water irrigation sources. We collected 1 L water samples (n = 410) between 2016 and 2018 from the Mid-Atlantic (12 sites) and Southwest (10 sites) U.S. Samples were filtered, and DNA was extracted. The V3-V4 regions of the 16S rRNA gene were then PCR amplified and sequenced. Metagenomic sequencing was also performed to characterize antibiotic, metal, and biocide resistance genes. Bacterial alpha and beta diversities were significantly different (p < 0.001) across water types and seasons. Pathogenic bacteria, such as Salmonella enterica, Staphylococcus aureus, and Aeromonas hydrophilia were observed across sample types. The most common antibiotic resistance genes identified coded against macrolides/lincosamides/streptogramins, aminoglycosides, rifampin and elfamycins, and their read counts fluctuated across seasons. We also observed multi-metal and multi-biocide resistance across all water types. To our knowledge, this is the most comprehensive longitudinal study to date of U.S. recycled water and surface water used for irrigation. Our findings improve understanding of the potential differences in the risk of exposure to bacterial pathogens and antibiotic resistance genes originating from diverse irrigation water sources across seasons and U.S. regions.
Detection of Salmonella enterica and Listeria monocytogenes in alternative irrigation water by culture and qPCR-based methods in the Mid-Atlantic U.S.
Acheamfour, Chanelle L.; Parveen, Salina; Gutierrez, Alan; Handy, Eric T.; Behal, Sara; Kim, Donghyun; Kim, Seongyun; East, Cheryl; Xiong, Ray; Haymaker, Joseph; Micallef, Shirley A.; Goldstein, Rachel E. Rosenberg; Kniel, Kalmia E.; Sapkota, Amy R.; Hashem, Fawzy; Sharma, Manan (American Society for Microbiology, 2024-04-02)
Alternative irrigation waters (rivers, ponds, and reclaimed water) can harbor bacterial foodborne pathogens like Salmonella enterica and Listeria monocytogenes, potentially contaminating fruit and vegetable commodities. Detecting foodborne pathogens using qPCR-based methods may accelerate testing methods and procedures compared to culture-based methods. This study compared detection of S. enterica and L. monocytogenes by qPCR (real-time PCR) and culture methods in irrigation waters to determine the influence of water type (river, pond, and reclaimed water), season (winter, spring, summer, and fall), or volume (0.1, 1, and 10 L) on sensitivity, accuracy, specificity, and positive (PPV), and negative (NPV) predictive values of these methods. Water samples were collected by filtration through modified Moore swabs (MMS) over a 2-year period at 11 sites in the Mid-Atlantic U.S. on a bi-weekly or monthly schedule. For qPCR, bacterial DNA from culture-enriched samples (n = 1,990) was analyzed by multiplex qPCR specific for S. enterica and L. monocytogenes. For culture detection, enriched samples were selectively enriched, isolated, and PCR confirmed. PPVs for qPCR detection of S. enterica and L. monocytogenes were 68% and 67%, respectively. The NPV were 87% (S. enterica) and 85% (L. monocytogenes). Higher levels of qPCR/culture agreement were observed in spring and summer compared to fall and winter for S. enterica; for L. monocytogenes, lower levels of agreement were observed in winter compared to spring, summer, and fall. Reclaimed and pond water supported higher levels of qPCR/culture agreement compared to river water for both S. enterica and L. monocytogenes, indicating that water type may influence the agreement of these results.
U.S. cereal rye winter cover crop growth database
Huddell, Alexandria; Thapa, Resham; Marcillo, Guillermo; Ackroyd, Victoria; Bagavathiannan, Muthukumar; Balkcom, Kipling; Bradley, Kevin; Darby, Heather; Reiter, Mark S.; Haymaker, Joseph; Flessner, Michael L.; Wolters, Bethany; Ketterings, Quirine; Kladivko, Eileen; Miller, Jarrod; VanGessel, Mark; Mirsky, Steven (Nature Portfolio, 2024-02-13)
Winter cover crop performance metrics (i.e., vegetative biomass quantity and quality) affect ecosystem services provisions, but they vary widely due to differences in agronomic practices, soil properties, and climate. Cereal rye (Secale cereale) is the most common winter cover crop in the United States due to its winter hardiness, low seed cost, and high biomass production. We compiled data on cereal rye winter cover crop performance metrics, agronomic practices, and soil properties across the eastern half of the United States. The dataset includes a total of 5,695 cereal rye biomass observations across 208 site-years between 2001–2022 and encompasses a wide range of agronomic, soils, and climate conditions. Cereal rye biomass values had a mean of 3,428 kg ha⁻¹, a median of 2,458 kg ha⁻¹, and a standard deviation of 3,163 kg ha⁻¹. The data can be used for empirical analyses, to calibrate, validate, and evaluate process-based models, and to develop decision support tools for management and policy decisions.
High-resolution surface and rootzone soil moisture over US cropland: A novel framework assimilating multi-source remote sensing data, machine learning, and the Layered Green and Ampt Infiltration with Redistribution model
Cai, Shuohao; Xu, Yijia; Yang, Zhengwei; Crow, Wade; Zhang, Zhou; Reberg-Horton, Chris; Schomberg, Harry; Mirsky, Steven; Seehaver, Sarah; Park, Dara; Treadwell, Danielle; Haymaker, Joseph; Reiter, Mark S.; Flessner, Michael L.; Sias, Cynthia; Tomlinson, Peter; Huang, Jingyi (Elsevier, 2026-03-01)
Accurate and high spatiotemporal resolution soil moisture (SM) monitoring in cropland is important for water resource management, drought forecasting, and nutrient transport estimation at the field scale for sustainable crop production. Although recent research has applied machine learning (ML) to downscale coarse-resolution satellite SM products, most of this past work has focused only on surface SM estimation, and the performance of rootzone SM products has not been intensively evaluated in cropland. This study introduces a novel framework that integrates multi-source satellite-based ML models with the Layered Green and Ampt Infiltration with Redistribution (LGAR) model to produce high-resolution (100 m, hourly) SM products for both the surface layer (0–5 cm) and rootzone (0–100 cm) across cropland in the contiguous United States (CONUS). First, six ML models were trained using multiple high-resolution remote sensing datasets (Sentinel-1, Sentinel-2, and Landsat) to predict surface and rootzone SM. These ML predictions were then assimilated into the LGAR model using the ensemble Kalman filter (EnKF). The framework was developed and validated using an eight-fold cross-validation scheme with in-situ data from 431 cropland sites across CONUS, sourced from three networks (SCAN, USCRN, and PSA). The 100-m hourly SM data from this framework surpasses existing products (9-km SMAP L4, SMAP-based 1-km thermal hydraulic disaggregation of SM product) in spatial and temporal resolution and captures rootzone SM that is not available in the SMAP-HydroBlocks SM product. It achieves good performance, with median bias-corrected root mean squared error (ubRMSE) of 0.053 m3/m3 and median Kling-Gupta efficiency (KGE) of 0.379 in the surface layer, and median ubRMSE of 0.027 m3/m3 and median KGE of 0.302 in the rootzone. While the framework demonstrates strong performance, its accuracy varies across climatic regimes, with surface SM performing better in non-humid areas (median KGE = 0.375 versus median KGE = 0.416) and rootzone SM in humid regions (median KGE = 0.313 versus median KGE = 0.127). This high-resolution cropland SM product can potentially benefit multiple agricultural applications, such as irrigation management and nutrient leaching estimation, and provide valuable insights to support farmers and land managers in decision-making processes.

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