![]() Field-scale management can therefore be improved by understanding relationships between NDVI, yield, and GPC. Despite this, yield and GPC can be positively related depending on edaphic properties and management interventions, with great advantage to producers. Wheat yield and GPC are often inversely related within a field because water stress during grain filling increases GPC but decreases yield. Understanding GPC is critical not only for agricultural management but also for the global food system as it is predicted to decrease in a changing climate. Other crop attributes also determine price, like grain protein content (GPC) for the case of wheat ( Triticum aestivum L.). Following this notion, the yields of many different crops have been estimated using NDVI and related vegetation indices using aerial and satellite-based platforms. Canopy spectral reflectance indices like the normalized difference vegetation index (NDVI) are useful for estimating crop yield within individual fields because the absorption and reflectance of red and near-infrared wavelengths is a good proxy for leaf area, which in turn is a good proxy for growth and yield. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist.Ĭrop yields are often quite variable within individual fields due to differences in soil fertility, topography, weediness, and management efforts, but also for reasons that are not entirely clear. PS: United States National Science Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. įunding: PS: Montana Wheat and Barley Committee. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: Data are published on figshare at. Received: SeptemAccepted: FebruPublished: March 22, 2022Ĭopyright: © 2022 Stoy et al. PLoS ONE 17(3):Įditor: Aimin Zhang, Institute of Genetics and Developmental Biology Chinese Academy of Sciences, CHINA Future research should seek to determine an ‘optimum’ spatial scale for NDVI observations that minimizes effort (and therefore cost) while maintaining the ability of producers to make management decisions that positively impact wheat yield and GPC.Ĭitation: Stoy PC, Khan AM, Wipf A, Silverman N, Powell SL (2022) The spatial variability of NDVI within a wheat field: Information content and implications for yield and grain protein monitoring. Results suggest that larger pixels can reasonably capture the information content of within-field NDVI, but the 30 m Landsat scale is too coarse to describe some of the key features of the field, which are consistent with topography, historic management practices, and edaphic variability. Radially-averaged power spectra of UAV-measured NDVI revealed relatively steep power-law relationships with exponentially less variance at finer spatial scales. Spatial averaging to the scale of the harvester also made little difference in the total information content of NDVI fit using Beta distributions as quantified using the Kullback-Leibler divergence. The variance in NDVI observations was “averaged out” at larger pixel sizes but only ~ 20% of the total variance was averaged out at the spatial scale of the harvester on some measurement dates. ![]() We sought to understand the optimal spatial scale for interpreting UAV observations given that the ~ 10 cm pixels yielded more than 12 million measurements at far finer resolution than the 12 m scale of the harvester. A multiple linear model using information from four (three) UAV flyovers was selected as the most parsimonious and predicted 26% (40%) of the variability in wheat yield (GPC). Landsat observations were poorly related to yield and GPC measurements. We measured yield and GPC in a winter wheat field in Sun River, Montana, USA, and tested the ability of normalized difference vegetation index (NDVI) measurements from an unoccupied aerial vehicle (UAV) on spatial scales of ~10 cm and from Landsat on spatial scales of 30 m to predict them. The price offered to producers depends not only on yield but also grain protein content (GPC), which are often negatively related at the field scale but can positively covary depending in part on management strategies, emphasizing the need to understand their variability within individual fields. Wheat is a staple crop that is critical for feeding a hungry and growing planet, but its nutritive value has declined as global temperatures have warmed.
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