Utilizing NDVI and Remote Sensing Data to Identify Spatial Variability In Plant Stress As Influenced by Landscape Position and Crop Management.

Understanding plant stress and its distribution spatially within a production setting has long been a goal of physiologists and producers alike. Recognizing this variability in plant growth early in a growing season can aid in identify factors limiting overall yields. Oftentimes these are associated with soil characteristics, nutrient availability, or environmental limitations. Technological advances in crop monitoring have made it possible to gather vegetative indices quickly and economically. The use of active sensors to gather reflectance from a crop canopy has been used to measure NDVI (Normalized Differential Vegetative Index). NDVI has been associated with percent ground cover, LAI, biomass accumulation, and nitrogen use efficiency. While vegetative indices have been proven to have weaknesses identifying highly specific physiological characteristics, this study contends that vegetative indices, specifically NDVI, can be used to characterize the spatial variability of plant development under different management techniques and can be correlated to edaphic characteristics of a location. NDVI values were measured bi-weekly over the course of a growing season specifically targeting maize grown at locations with known spatial and managerial variability. Soil type, macronutrient availability, slope, soil moisture and position on the landscape of each site were noted and associated with each plot. Management characteristics such as planting population, cropping history, and pest management were noted in order to identify contributing factors in the spatial variability of NDVI values. Two cropping rotations were used, being continuous corn and a corn, soybean, small grain/soybean double crop rotation. Variations in NDVI values over the course of the growing season were similar to differences in final grain yield. The use of mid-season NDVI values as an indicator of variations in crop development, stress, and productivity are supported by this study. Identifying the root cause of those variations cannot be based on NDVI alone. Other intrinsic factors related to crop production and its location on a landscape must be known in order to make management decisions based on the level of variation in both grain yield and NDVI values.