Drone based imagery shows the potential to highlight differences in crop status pertaining to nematode populations in soybean. In addition, integrating the imagery with machine learning models enables yield estimation much before harvest up to an accuracy of 87%. This provides growers with insights into crop health and yield conditions prompting for timely management decisions such as application of fertilizer or fungicides and irrigation. In addition, growers would also benefit from preharvest yield estimations for harvest, storage, and sales planning. This helps to realize optimal yield.

"The Agroclimate Viewer & Planner App: NDVI only is a free interactive web-based tool designed to help growers and researchers to monitor crop health in the fields. By leveraging Google Earth Engine (GEE), the application provides insights through satellite imagery. Users can draw field boundaries and generate NDVI visualizations to aid in informed agricultural decision-making.

The Agroclimate Viewer & Planner App is a free interactive web-based tool designed to help growers and other users monitor, forecast, and analyze agroclimatic conditions for their croplands. By leveraging Google Earth Engine (GEE), the application provides insights through satellite imagery, weather forecasts, soil data, and climate patterns. Users can draw field boundaries, select specific parameters, and generate visualizations to aid in informed agricultural decision-making.

Over past decades, there has been a steep emergence in the use of larger and heavier agricultural machinery including for tillage, planting, spraying, and harvesting. Although this is done to achieve higher productivity and efficiency, the unregulated traffic in the crop fields raise wheel loads to result in heavy soil compaction risks. Soil compaction is one of the major reasons for soil health degradation impacting physical, chemical, and biological properties of the soil and eventually the crop productivity. We present the impact of soil compaction on crop yield and assess Controlled traffic farming (CTF) as a possible solution. Study results show that the soil compaction was higher for the track zone compared to the no-track zone for both the corn and soybean growing fields. Importantly, this impact was prominent in the root zone depth i.e., till and beyond the hard pan. In some cases, the compaction varied so prominently that it led to the formation of two hard pans. Evaluations for the CTF also showed a trend that the field treatments with no cover crop experienced the highest soil compactions whereas the treatments with cover crop experienced the least compaction in most cases. It was also evident that soil compaction led to reduced crop health which likely also impacts the crop yield.

Drone-based spectral imaging is a nondestructive approach for estimating corn grain yield efficiently prior to harvest. Such spatial estimations if done early in the season could help growers to identify lower performing areas of the field. This will guide them to adopt prompt, precise and cost-effective crop management operations (e.g., irrigation, fertilizer or fungicide applications) in the same season or before/during next cropping season. Pre-harvest yield estimates would help in better planning and allocation of harvest, storage, and sales resources for higher profitability and crop value. This article summarizes a recent exploration on drone-based multispectral imagery to estimate grain yield potential of corn.

Peanut is a “cash” commodity for Virginians and most farmers grow this crop for certified seed. Seed quality and germination in particular are, therefore, very important. Even though the 2022 results were inconclusive, potential for prohexadione calcium to reduce germination and increase abnormal seedling production was clearly suggested by these data. The inconclusiveness could have been the result of a combination of factors, other than PC, affecting seed quality during storage. A differential response of the cultivars to both, seed aging and PC, was clearly suggested by our preliminary data. Evidence that PC may affect the seed quality, through seed weight, was also notable from the 2022 tests.

Faba bean (Vicia faba L.), also known as fava bean, broad bean, horse bean, or Windsor bean, is a leguminous crop used as food, feed, forage, or cover crop in different parts of the world. This crop can be used for food, feed, and as a ground cover crop. It is highly nutritious and has high protein content, the second after soybean when comparing with the common grown legumes including, dry beans, lentils, peas, cowpeas, and chickpeas. The high protein content makes faba bean an excellent source for plant-based foods, like meat and milk. Compared to the other cool-season legumes such as pea and lupin, faba bean can attain and fix substantially more nitrogen from the atmosphere to soil. Because of temperature increase during summer, a winter crop can ensure cropping system diversification while minimizing the negative effects of summer heat on yield and economic return, and this crop can potentially be faba bean. A USDA-funded project at the Virginia Tech’ s Tidewater Agricultural Research and Extension Center (TAREC) in Suffolk, VA, is focused on introduction of faba bean as a winter seed crop with multiple benefits for the Mid-Atlantic cropping systems. The project includes collaborators from the University of Maryland, University of Delaware, North Carolina State University, and University of Georgia, in addition to the Virginia State University and Virginia Tech. Started in 2023 and lasting until 2027, the project will address objectives related to cultivar development through breeding, genetics and physiological strategies, identification of the best agronomic practices to maximize yield and economic return, economic and marketing logistics, and consumer acceptance. As the results became available, the PI will provide updates on this new crop for the region.