Abstract: Both the vastness of pasturelands and the value they contain—e.g., food security, ecosystem services—have resulted in increased scientific and industry efforts to remotely monitor them via satellite imagery and machine learning (ML). However, the transferability of these models is… Read More
Journal PapersJournal Papers
Plant parasitic nematode identification in complex samples with deep learning
Abstract: Plant parasitic nematodes are significant contributors to yield loss worldwide, causing devastating losses to every crop species, in every climate. Mitigating these losses requires swift and informed management strategies, centered on identification and quantification of field populations. Current plant… Read More
Histogram Layers for Neural “Engineered” Features
Abstract: In the computer vision literature, many effective histogram-based features have been developed. These engineered features include local binary patterns and edge histogram descriptors among others and they have been shown to be informative features for a variety of computer… Read More
Facilitating macrosystem biology with organismal-scale airborne remote sensing: Challenges and opportunities
Abstract: Emergent ecosystem properties, such as population and trait distributions, biodiversity and energy and water fluxes, occur because of the dynamic interactions of individuals in their environment. Remote sensing, where image data is collected over large areas, can provide information… Read More
Toward a General Framework for AI‑Enabled Prediction in Crop Improvement
Abstract: The curse of dimensionality in genomic prediction has been established and hampers genetic gain for complex traits. Artificial intelligence (AI) that fuses symbolic and sub-symbolic approaches to prediction is emerging as an approach that can deal effectively with this… Read More
Interactive Segmentation with Prototype Learning for Few-Shot Root Annotation
Abstract: Fine-scale pixel-level annotation of minirhizotron root images is a less common and challenging task. We present an interactive segmentation framework to accelerate root annotation. We leverage the concept of few-shot segmentation so that the pre-trained model can be effectively… Read More
Automated potato tuber mass estimation and grading with multiangle 2D images
Abstract: Estimating potato tuber mass and size grading with computer vision can help breeders, farmers, and potato processing units reduce manual labor for potato post-harvest handling through optimized technology. The objective of the study was to estimate potato tuber mass… Read More
Individual canopy tree species maps for the National Ecological Observatory Network
Abstract: The ecology of forest ecosystems depends on the composition of trees. Capturing fine-grained information on individual trees at broad scales provides a unique perspective on forest ecosystems, forest restoration and responses to disturbance. Individual tree data at wide extents… Read More
Estimating Soil Mineral Nitrogen from Data-sparse Field Experiments using Crop Model-guided Deep Learning Approach
Abstract: Sandy soils are susceptible to excessive nitrogen (N) leaching under intensive crop production which is linked with the soil’s low nutrient holding capacity and high-water infiltration rate. Estimating soil mineral nitrogen (SMN) at the daily time-step is crucial in… Read More
Hyperspectral signals in the soil: Plant–soil hydraulic connection and disequilibrium as mechanisms of drought tolerance and rapid recovery
Abstract: Predicting soil water status remotely is appealing due to its low cost and large-scale application. During drought, plants can disconnect from the soil, causing disequilibrium between soil and plant water potentials at pre-dawn. The impact of this disequilibrium on… Read More