Mixed-Species Cover Crop Biomass Estimation Using Planet Imagery.

Cover crop biomass is helpful for weed and pest control, soil erosion control, nutrient recycling, and overall soil health and crop productivity improvement. These benefits may vary based on cover crop species and their biomass. There is growing interest in the agricultural sector of using remotely sensed imagery to estimate cover crop biomass. Four small plot study sites located at the United States Department of Agriculture Agricultural Research Service, Crop Production Systems Research Unit farm, Stoneville, MS with different cereals, legumes, and their mixture as fall-seeded cover crops were selected for this analysis. A randomized complete block design with four replications was used at all four study sites. Cover crop biomass and canopy-level hyperspectral data were collected at the end of April, just before cover crop termination. High-resolution (3 m) PlanetScope imagery (Dove satellite constellation with PS2.SD and PSB.SD sensors) was collected throughout the cover crop season from November to April in the 2021 and 2022 study cycles. Results showed that mixed cover crop increased biomass production up to 24% higher compared to single species rye. Reflectance bands (blue, green, red and near infrared) and vegetation indices derived from imagery collected during March were more strongly correlated with biomass (r = 0-0.74) compared to imagery from November (r = 0.01-0.41) and April (r = 0.03-0.57), suggesting that the timing of imagery acquisition is important for biomass estimation. The highest correlation was observed with the near-infrared band (r = 0.74) during March. The R2 for biomass prediction with the random forest model improved from 0.25 to 0.61 when cover crop species/mix information was added along with Planet imagery bands and vegetation indices as biomass predictors. More study with multiple timepoint biomass, hyperspectral, and imagery collection is needed to choose appropriate bands and estimate the biomass of mix cover crop species.

Glyphosate-resistant and glyphosate-susceptible Palmer amaranth (Amaranthus palmeri S. Wats.): hyperspectral reflectance properties of plants and potential for classification.

BACKGROUND: Palmer amaranth (Amaranthus palmeri S. Wats.) is a troublesome agronomic weed in the southern United States, and several populations have evolved resistance to glyphosate. This paper reports on spectral signatures of glyphosate-resistant (GR) and glyphosate-sensitive (GS) plants, and explores the potential of using hyperspectral sensors to distinguish GR from GS plants. RESULTS: GS plants have higher light reflectance in the visible region and lower light reflectance in the infrared region of the spectrum compared with GR plants. The normalized reflectance spectrum of the GR and GS plants had best separability in the 400-500 nm, 650-690 nm, 730-740 nm and 800-900 nm spectral regions. Fourteen wavebands from within or near these four spectral regions provided a classification of unknown set of GR and GS plants, with a validation accuracy of 94% for greenhouse-grown plants and 96% for field-grown plants. CONCLUSIONS: GR and GS Palmer amaranth plants have unique hyperspectral reflectance properties, and there are four distinct regions of the spectrum that can separate the GR from GS plants. These results demonstrate that hyperspectral imaging has potential application to distinguish GR from GS Palmer amaranth plants (without a glyphosate treatment), with future implications for glyphosate resistance management. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.