Utilizing NDVI and remote sensing data to identify spatial variability in plant stress as influenced by management

Understanding plant stress and its spatial distribution has been a goal of both crop physiologists and producers. Recognizing variability in plant growth early can aid in identifying yield-limiting factors such as soils, nutrient availability, and/or environmental limitations. Active sensors have been used to gather reflectance data from crop canopies and to calculate NDVI (Normalized Difference Vegetative Index). NDVI has been associated with percent ground cover, LAI, biomass accumulation, and nitrogen use efficiency. This study contends that NDVI can be used to characterize spatial variability in plant growth and is correlated with grain yield. NDVI values were measured bi-weekly through the growing seasons of 2010 and 2011in corn (Zea mays L.) grown at a location with soil and topographic variability. Grain yield was collected following each growing season. Management practices and characteristics of the site were associated with each plot in order to identify contributing factors to spatial variations in NDVI values. Two cropping rotations were used, continuous corn, and a corn soybean small grain/soybean double crop. Results showed differences in corn growth at different landscape positions could be identified with NDVI. The strength of this relationship was greatest eight weeks after planting. A relationship was also established between NDVI and grain yield. NDVI measurements can be used to identify the variability of grain yield in continuous corn production when taken following the accumulation of 800 to 900 growing degree days. This demonstrated success presents the opportunity to use this technology in characterizing production potential and making managerial decisions across a landscape