Horticultural Crops Research Laboratory

Delivery of biomolecules into plant vascular tissues remains a barrier to managing diseases caused by insect vector-borne pathogens and to modifying phenotypes of established perennial crops. Inspired by the vascularized growth of crown galls induced by Agrobacterium tumefaciens, we repurposed the bacterium’s plant growth regulator (PGR) genes to engineer autonomously dividing, transgene-expressing plant cell structures termed symbionts. A plant transformation vector (pSYM) incorporating the IaaM, IaaH, Ipt and gene5 cassette from A. tumefaciens strain C58 together with a gene of interest on the same transfer DNA was delivered to stems of herbaceous and woody dicots using disarmed A. tumefaciens strain EHA105. Symbiont morphology, vascular differentiation, transgene expression, molecular mobility and protein secretion were evaluated using microscopy, fluorescent reporters, dye tracing, RNA silencing assays and mass spectrometry-based proteomics. pSym inoculation reproducibly generated symbionts across diverse host plant species that were vascularly integrated into their host plants and transgene expression ranging from heterogeneous niches to more uniform patterns. Small molecules moved between symbionts and host vascular tissues, whereas larger proteins exhibited more restricted mobility. Post-transcriptional gene silencing signals moved freely throughout the symbiont and slightly into adjacent stem tissue. Under tested field and greenhouse conditions in potato and tomato, respectively, gall or symbiont formation had no negative impacts on plant growth or tuber and fruit yield. In vitro, symbiont cultures abundantly secreted recombinant protein into surrounding media. Together, these results establish symbionts as a modular, plant bioengineering platform capable of producing and potentially delivering biomolecules without modifying the host plant genome, providing a foundation for vascular-targeted therapeutics and phenotype modulation in crops.

Early and accurate identification and quantification of plant-parasitic nematodes (PPNs) is crucial for their effective control. Although valuable, the current techniques for identifying PPNs, such as morphology and molecular marker-based methods, can be time- and resource-intensive. This study aimed to develop and validate cutting-edge computer vision tools for automated, accurate, and reproducible PPN detection. To achieve this goal, we captured microscopic images of the three economically important PPN genera associated with potato crop: root-lesion nematode (RLN; Pratylenchus spp.), root-knot nematode(RKN; Meloidogyne spp.), and stubby root nematode (SRN; Paratrichodorus and Trichodorus spp.), as well as additional PPNs (PPN-OTHERS) and non-parasitic (NON-PARASITIC) nematodes, for a total of five groups. The captured images (total instances = 8,654) were preprocessed, annotated, and randomly split into three datasets: 75% for training, 15% for validation, and 10% for testing. An object segmentation algorithm, YOLOv11-seg, which predicts each pixel in an image, was trained and evaluated onpreviously unseen images. The model achieved high accuracy in validation (92.4%) and test (88.6%) datasets, with strong performance for key PPN genera (RKN, RLN, and SRN; F1 scores > 0.92; AUC > 0.93 in the test set). Whereas the NON-PARASITIC group showed strong performance (F1 score > 0.846 and AUC > 0.91), the PPN-OTHERS group performed poorly (test accuracy: 43.9%), frequently misclassified as RLNs and NON-PARASITIC nematodes. The results highlight the potential of artificial intelligence-based tools for identifying PPNs, paving the way for the long-term goal of developing automated detection and quantification systems for plant pathogens.

Digital transformation in the agricultural sector offers significant opportunities to enhance the productivity, efficiency, and welfare of smallholder farmers in Indonesia. Nevertheless, the rate of digital technology adoption among smallholder farmers remains relatively low due to limited digital literacy, infrastructure access, economic risks, and suboptimal institutional support. This study aims to develop a more comprehensive conceptual framework to explain the dynamics of digital technology adoption by smallholder farmers in Indonesia. The research employs a qualitative approach with a conceptual paper design through a systematic conceptual review of relevant international and national literature, alongside a synthesis of key theories including Diffusion of Innovation (DOI), Technology Acceptance Model (TAM), and Unified Theory of Acceptance and Use of Technology (UTAUT). The analytical findings indicate that digital technology adoption is a multidimensional socio-technical process involving the interaction of individual cognitive capacity, household economic stability, community social capital, digital infrastructure readiness, and policy and institutional support. Based on theoretical integration and cross-country empirical findings from developing nations, this study develops the Adaptive Socio-Technical Agrarian Digitalization (ASTAD) model, which emphasizes a dynamic adaptive process within the agrarian ecosystem. This model extends classical approaches by incorporating variables such as economic risk buffer capacity, digital learning elasticity, collective trust, digital access stability, and market integration. The contribution of this research lies in reinforcing a systemic perspective for understanding smallholder agricultural digitalization in Indonesia, along with policy implications for promoting an inclusive and sustainable digital ecosystem.

Understanding and quantifying the influence of row orientation on crop water consumption is necessary to inform the design of sustainable field architectures and irrigation schedules, which is particularly beneficial for high-value-crop farms located in water-limited regions, such as California vineyards. Although some scientific literature addresses this for typical row orientations (i.e., North-South and East-West), Southwest-Northeast (SWNE) and Northwest-Southeast (NWSE) row orientations remain largely unaccounted for. In this study, Two-Source Energy Balance (TSEB) model simulations are performed during 2021 and 2022 to quantify the differences in satellite-based evapotranspiration (ET) between vineyard blocks oriented SWNE and NWSE. Simulated daily ET is similar during the vine dormant seasons, but consistently higher for SWNE blocks during the growing season, with average differences of 1.2 ± 0.36 mm day −1 in 2021 and 1.5 ± 0.55 mm day −1 in 2022. Long-term averages of eddy covariance fluxes confirm the simulated ET separation during the growing season, but day-to-day values suggest smaller differences compared to TSEB. Landsat-based Leaf Area Index (LAI), land surface temperature (LST) and albedo inputs forcing TSEB also show separation. A sensitivity analysis suggests that TSEB is highly responsive to LST and albedo, showing high correlations (r 2 = 0.88 and r 2 = 0.86, respectively) with modelled ET differences. Two radiative transfer models indicate greater canopy radiation interception and shadowing in SWNE vineyards, which are likely captured by the satellite-based TSEB inputs. The results of this study add to the comprehensive understanding of row geometry influence on vineyard water demands needed to optimize agricultural applications of ET models. • Two-Source Energy Balance model ET is different in Southwest-Northeast and Northwest-Southeast vineyards. • Simulated ET is 1.32 mm day −1 higher in Southwest-Northeast vineyards on average. • Eddy covariance fluxes confirm simulated ET differences but suggest model overestimation. • Modelled radiation interception is up to 15 % higher in Southwest-Northeast vines. • The Two-Source Energy Balance model is sensitive to satellite-based inputs likely capturing row shadow differences.

ABSTRACT Soil health is central to sustainable agriculture and a key goal of regenerative and organic farming. However, monitoring changes in soil health remains challenging due to the lack of regionally relevant benchmarks and context‐specific indicators. This study assessed the impacts of long‐term and combined regenerative management practices on soil health across 87 California vineyards with diverse management histories, microclimates, and soils. Three key indicators, including aggregate stability, mineralizable carbon, and soil organic carbon, were used to develop region‐specific soil health scoring functions. These were adapted from Cornell's Comprehensive Assessment of Soil Health and the Soil Health Institute frameworks. Indicator values generally trended lower than existing benchmarks, emphasizing the need for crop‐ and region‐specific scoring systems. Results from mixed‐effects models and fuzzy‐set qualitative comparative analysis (fsQCA) indicate that long‐term cover cropping (≥ 10 years) was the most consistent driver of high soil health scores, especially when combined with other practices. Livestock integration improved soil organic carbon and mineralizable carbon scores in under 10 years, showing potential to accelerate soil health benefits. Our results highlight the importance of tailoring practices to local soil and climate conditions. Findings also support the development of more flexible, regionally informed soil health frameworks.

ABSTRACTIn white wines, early detection of oxidation would alert winemakers to monitor potentially troubled wine more closely and take preventative measures to mitigate undesirable browning, flavors, and odors in their products. Current early oxidation detection methods include assessment by browning index, trained sensory panels, and quantification of byproducts such as quinones. The objective of this study was to assess the capability of the e‐tongue, a fairly new instrument that has previously been used to detect wine faults caused by spoilage organisms, in detecting early oxidative changes in Chardonnay wine. Clear bottles of Chardonnay were stored partially opened (treatment) in the dark at 2.2°C for 24 weeks. Wines were assessed at seven time intervals (0, 1, 2, 4, 8, 16, and 24 weeks) using the e‐tongue and a semi‐trained sensory panel with rate‐all‐that‐apply descriptors. Beginning at week 8 of storage, the e‐tongue discrimination indices (DI) between control and treated wine (sealed wine stored alongside partially opened wine bottles) were high (DI > 80%) and remained high throughout the study, indicating that the e‐tongue distinguished between control and treated samples. However, sensory panelists detected an increase in the intensity of vinegar/nail polish remover aroma attributes, attributes associated with wine oxidation, after 16 weeks of storage. These results suggest that the e‐tongue is a useful tool in the early detection of oxidized wine samples as compared to a sensory panel that perceived differences between control and treated wines 8 weeks after differences were detected by the e‐tongue.

Botrytis cinerea, a high-risk pathogen for fungicide resistance development, poses a significant threat to yield and fruit quality of blueberry and red raspberry in the Pacific Northwest. Succinate dehydrogenase inhibitor (SDHI) fungicides are effective botryticides that are considered medium to high risk for resistance development. Analysis of sdhB sequences from Botrytis isolates (n = 278) exhibiting different levels of sensitivity to any of four SDHIs (boscalid, fluxapyroxad, fluopyram, and isofetamid) revealed six previously characterized mutations in 244 isolates (N230I, P225F, H272R, H272V, H272Y, and I274V) at frequencies of 40, 22, 22, 10, 5, and 1%, respectively. Different mutations in the sdhB gene resulted in 12 phenotypic profiles exhibiting in vitro resistance to the four SDHIs. In contrast, sdhC and sdhD sequences revealed no consistent mutations linked to a specific fungicide resistance profile. Importantly, among the mutations in sdhB, 72% were P225F, H272V, or N230I, which confer cross-resistance to multiple SDHI fungicides. These findings emphasize the need for balanced use and rotation of fungicides to manage Botrytis effectively in blueberry and red raspberry fields in the Pacific Northwest.

A neuropeptide, the CAPA, and its cognate receptor have been diversely characterized in different orders of class Insecta. CAPA peptides are synthesized in the abdominal neurohemal system and activate their corresponding receptor, CAPA receptor (CAPA-R), a type of G protein-coupled receptor (GPCR), to initiate cellular signals for diverse physiological functions in insects. Activation of the CAPA-R in Malpighian tubules results in ion-water homeostasis via antidiuresis in the majority of insect species; however, diuresis and myotropic activities are also known to result. Antidiuretic activity of CAPA peptides has been reported from mosquitoes, assassin bugs, spotted wing drosophila, and more; hence, this group of peptides also holds importance as potential targets when it comes to medical and agricultural entomology. GPCRs form a diverse family of cell membrane receptors responsible for signal transduction across the cell membrane in humans as well as in insects. With the advances in knowledge of human GPCRs, their physiological functions in agriculturally important insects have offered an opportunity for designing and implementing GPCR-targeting compounds in integrated pest management programs. In this review, we present a comprehensive view on physiological factors and peptides responsible for the diuresis/anti-diuresis in insects with special reference to the CAPA peptide-receptor interaction. The major focus is on the role of CAPA peptides in fluid and energy homeostasis, stress tolerance, muscle functioning, regulation of reproduction, and diapause-related processes. We end by outlining the significance of insect excretion with respect to the capa-r gene silencing and pest management.

Research efforts are needed to develop new biocontrol strategies against plant-parasitic nematodes (PPNs) to replace chemicals and maintain sustainable crop production. In this study, filtrates obtained from fungi isolated from cyst nematodes (Heteroderidae) were evaluated for activity against eggs and second-stage juveniles (J2) of five PPNs: Globdera ellingtonae, Heterodera glycines, Meloidogyne incognita, M. hapla, and M. chitwoodi. Initially, filtrates of 42 fungal isolates were evaluated for effects on G. ellingtonae and H. glycines egg viability. After the initial screening, six of the fungal isolates were selected for further evaluation against additional PPN eggs and J2 based upon evidence of usage in other studies, fast growth, and frequency of isolation. Filtrates from Alternaria tenuissima JB217, Fusarium acaciae-mearnsii JB201, Purpureocillium lilacinum JB209, and Trichoderma virens JB98 reduced H. glycines egg viability by >80%. Aureobasium sp. JB70, F. proliferatum JB173, and P. lilacinum JB209 reduced G. ellingtonae egg viability by >50% but had negligible effect on the J2 stage of this nematode. Filtrate from F. acaciae-mearnsii JB201was the most lethal against PPNs, immobilizing ~100% of J2 of all nematode species while filtrate from A. tenuissima JB217 only immobilized J2 of G. ellingtonae, M. chitwoodi, and M. hapla. These fungal filtrates are therefore promising alternative sources of natural bioactive substances for the potential management of PPNs.