Yield Gap Analysis of Alfalfa Grown under Rainfed Condition in Kansas

The yield and production of alfalfa (Medicago sativa L.) have not been significantly improved in Kansas for the last 30 years even though farmers are using varieties. We noted a significant difference between average reported by researchers. magnitude gap its underlying factors still unknown. Thus, understanding potential is essential to meet future forage demand with limited resources. main objective this study was, therefore, quantify current identify yield-limiting factor rainfed grown Kansas. To achieve objective, we selected 24 counties based on area total production, used county-level yield, daily temperature, rainfall data from past yrs (1988–2017) those counties. applied four statistical approaches: (i) probability distribution function delineate growing season, (ii) stochastic frontier estimate optimum season (GSR) attainable (iii) linear boundary minimum water loss, use efficiency, water-limited (iv) conditional inference tree major contributing weather variables. delineated starting mid-March mid-November model estimated 9.2 Mg ha−1 at an GSR 664 mm, generating 18%. 15.5 existing 624 50%. revealed that 24% variation was explained variables, mainly due followed temperature. However, found only 7% deficit area, indicating cause such wide gap. further investigation other management minimize models might be particularly useful when estimation remote sensing crop simulation applicable terms time, resources, facilities, investments.