Lessons Learned from Mississippi's Centennial Rotation - Yields, Nutrient Uptake and Nutrient Removal.

Long-term crop rotation returned to the Midsouth following many years of continuous cotton production. Irrigated corn and soybean have become more profitable and have replaced cotton on many farms.  In 2004, a long-term rotation study was initiated on the Delta Research and Extension Center.  It has been designed to utilize the latest technology available for crop production.  Cotton, corn, and soybean, with cotton as the only continuous crop are being evaluated.  The study includes five rotation systems along with continuous cotton.  The rotations include 1) continuous cotton, 2) cotton/corn [1:1], 3) cotton/ cotton/corn [2:1], 4) corn/soybean [1:1], 5) soybean/corn/cotton [1:1:1], and 6) soybean/corn/cotton/ cotton [1:1:2].  Each crop is grown each year in order for direct comparisons of the systems with respect to production and price.  In many years, producers make their decision on crop mix based on prices.  Grain prices reached all-time highs and crops have set all-time record yields in the last few years.   Early planting, irrigation, and early harvest have given the Mississippi producer a distinct advantage in the market place.  Adding grain crops to rotations also increase total nutrient uptake and removal compared to cotton.  With comparable yields, nitrogen (N), phosphorus (P) and potassium (K) removal by grain crops could be two to three times higher than cotton.  This requires additional nutrient replacement in order to maintain high yields.  After 12 years, continuous cotton has removed far less nutrients compared to a corn/soybean rotation.   The more grain crops in a rotational system, the greater the N, P, and K removal and subsequent need for replacement.   As these rotations continue the difference in nutrient removal will also continue to grow.  Unlike many of the long-term rotation studies, the Centennial Rotation is replicated and allows for statistical comparisons of systems with fewer years of data.