Determining Relationships and Patterns in the Nutrisolutions® Plant Tissue Database Using Multivariate Analytics.

WinField-United is a data-driven company that delivers unmatched data and insights to help growers reach maximum yield potential. The NutriSolutions® 360 program offered by WinField-United provides plant tissue and soil analysis to optimize in-season plant nutrition and product applications. Since 2009, WinField-United has collected more than 418,000 tissue samples through the NutriSolutions® 360 program in 37 different crops. Despite the success of the NutriSolutions® 360 program, interpreting nutrient deficiencies and making recommendations based on tissue testing is still complicated by crop growth stage, nutrient interactions, and localized field conditions. The NutriSolutions® 360 tissue database provides an opportunity to use advanced analytics for deeper understanding and discovery of plant nutrition. Using multivariate approaches, 88,502 corn tissue samples collected from 2010 to 2014 in the states of Wisconsin, South Dakota, Nebraska, Iowa, Ohio, and Indiana were analyzed. On average, 60% or more of the samples were less than adequate for nitrogen, sulfur, potassium, manganese, and zinc concentrations during vegetative growth stages from 2010 to 2014. Correlation coefficients between nutrients indicated relationships between nitrogen and sulfur and copper for each state. A relationship between nitrogen and potassium was not detected for any state. Principal component analysis confirmed univariate nutrient relationships and showed nutrient synergy and antagonism that differed for each state. Zinc deficiency was the most common pattern in South Dakota and Nebraska while co-occurring deficiencies of potassium with zinc, manganese or magnesium were most common in Indiana, Ohio and Iowa. Correcting nutrient deficiencies may require consideration of multiple nutrients simultaneously and micronutrients that interact with nitrogen, phosphorus, or potassium. Using multivariate analytical approaches can reveal new insights to better guide nutrient application decisions.