Precision Agriculture

“Open imaging datasets of widely-grown corn lines give breeders and data scientists a shared benchmark for building faster, cheaper crop-improvement tools.”

“A University of Nebraska-built cable-and-sensor robot measures entire corn fields in fine detail, compressing years of hand data-collection in breeding and agronomy trials into a single season.”

“Manure management in the United States must move from a disposal-based model to a circular resource framework that integrates nutrient recovery, emission mitigation, precision application, supportive policy, and site-specific decision-making.”

“Mapping subsurface water pathways with ground-penetrating radar plus surface elevation explained corn and soybean yield variation far better than topography alone (error dropped from 23.7% to 15.3%, and to 10.0% when remote sensing was added). Even without costly subsurface surveys, adding surface flow accumulation cut error to 18.4%, making hydro-topographic zoning a practical basis for site-specific management.”

“Sensor-based N management cut nitrogen application by ~40 kg N/ha in corn with no yield loss across 57 Nebraska on-farm site-years (2015–2023). Benefits are greatest in moderate-to-high yield variability fields with coarser soils. Sensors showed no statistically significant gains in winter wheat. Profit probability exceeded 60% for corn across most price scenarios. Despite consistent evidence, only 11% of Nebraska producers currently use sensor-based approaches — indicating a technology transfer gap.”

“Within-field yield stability and gross margin variations across corn fields and implications for precision conservation.”

“Application of Vegetation Indices for Agricultural Crop Yield Prediction Using Neural Network Techniques.”

“Across 15 North Dakota nitrogen-rate sites, red and red edge NDVI predicted corn yield equally well at V6, but at the later V12 stage red edge NDVI outperformed red NDVI because red readings saturate once the canopy closes. For growers using GreenSeeker or Crop Circle sensors to guide in-season N, red edge is the better choice for late-season sidedress decisions.”

“Detection of Shelterbelt Density Change Using Historic APFO and NAIP Aerial Imagery.”

“Satellite-based identification of tornado damage tracks from the 27 April 2011 severe weather outbreak.”

“Mapping Groundwater Dependent Ecosystems in California.”

“Modeling sustainable agricultural residue removal at the subfield scale.”

“Predicting redoxsensitive contaminant concentrations in groundwater using random forest classification.”

“Mapping Large-Area Landscape Suitability for Honey Bees to Assess the Influence of Land-Use Change on Sustainability of National Pollination Services.”

“A modified surface energy balance algorithm for land (MSEBAL) based on a trapezoidal framework.”

“UAS VIs are robust to soil variability when canopy cover >~30%. NDVI can be biased high by wet soil or compost at ~30–35% cover. PVI showed the lowest sensitivity to soil background and canopy-cover changes.”

“Foliar sprays of eight plant-derived protein hydrolysates on tomato generally increased digital biomass, with two products (A and I) significantly improving relative growth rate and overall growth performance, though chlorophyll fluorescence showed no photosynthetic differences. Metabolomics indicated the biostimulants worked by reprogramming ethylene-precursor, polyamine, and ROS-signaling pathways, and the phenotyping-plus-metabolomics combination proved an efficient way to screen new biostimulant candidates.”

“The Two-Source Energy Balance with a dual temperature (TSEB2T) model was used to estimate evapotranspiration and identify the impact of spatial domain scale under different vine phenological conditions.”

“Exploiting Earth Observation Data to Impute Groundwater Level Measurements with an Extreme Learning Machine.”

“A study was conducted at Portageville, MO, USA, in 2016 and 2017 with the objective to compare yield and irrigation water use efficiency among three water-management treatments for cotton.”

“Spillover effects of organic agriculture on pesticide use on nearby fields.”