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Browsing Cooperative Extension by Author "Miller, Jarrod O."
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Item Assessing relationships of cover crop biomass and nitrogen content to multispectral imagery(Agronomy Journal, 2024-02-29) Miller, Jarrod O.; Shober, Amy L.; Taraila, JamieCover crops provide valuable roles in sustainable agriculture, provided they produce enough biomass. To accurately measure their services to field management, spatial estimates would be useful to producers. This study used multispectral drone imagery to produce maps of normalized difference vegetation index (NDVI), normalized difference red edge index (NDRE), and a digital surface model (DSM) of cover crop plots on sandy, Mid-Atlantic soils. Cover crops included cereal rye (Secale cereale), mixtures of rye and crimson clover (Trifolium incarnatum), and mixtures of rye and hairy vetch (Vicia villosa). Their biomass was sampled in the spring of 2019, 2020, and 2021, dried, weighed, and analyzed for total nitrogen (N) content. Measurements of NDVI became saturated (i.e., reached a linear plateau) at 3.86 Mg biomass ha−1, NDRE at 5.72 Mg biomass ha−1, and the DSM at 5.11 Mg biomass ha−1. The measured N content became saturated at 80.9, 139.1, and 75 kg N ha−1 for NDVI, NDRE, and the DSM, respectively. Based on log transformations, NDVI was a stronger predictor of biomass and N, but not C:N. The NDRE was important for biomass, N, and C:N, while the DSM interactions with cover crop species helped predict both the N content and C:N of cover crop tissues. Accumulated growing degree days was important as an individual variable for biomass and N and as an interaction with cover crop species. Abbreviations DSM digital surface model GDD growing degree days NDRE normalized difference red edge index NDVI normalized difference vegetation indexItem Post-harvest drone flights to measure weed growth and yield associations(Agricultural & Environmental Letters, 2022-06-14) Miller, Jarrod O.; Shober, Amy L.; VanGessel, Mark J.Drone flights are often only performed during the growing season, with no data collected once harvest has been completed, although they could be used to measure winter annual weed growth. Using a drone mounted with a multispectral sensor, we flew small plot corn (Zea mays L.) fertility, cover crop, and population studies at black layer and 0–14 d after harvest (DAH). Yields had positive correlations to normalized difference vegetation index (NDVI) at black layer but often had negative correlations to corn yields 0–14 DAH. After harvest, NDVI could be associated with weed growth, and negative correlations to yield could point to reduced corn canopy allowing light to reach late-season weeds. In fertility studies, excess nitrogen appears to increase weed biomass after harvest, which can be easily identified through drone imagery. Flights should be performed after corn harvest as weed growth may provide additional insight into management decisions. Core Ideas: - Corn yields can be correlated to post-harvest weed biomass by using NDVI. - Drone flights efficiently mapped weeds and made correlations to yield and management. - Fall weed control can be prioritized using drone mapping. Abbreviations: DAH days after harvest LAI leaf area index NDVI normalized difference vegetation index