A Nondestructive Method to Estimate Standing Crop of Purple Threeawn and Blue Grama

Abstract

We used multiple regression analysis to develop models to predict standing crop of purple threeawn (Aristida purpurea Nutt.) and blue grama (Bouteloua gracilis [H.B.K.] Griffiths) nondestructively. Data were collected for 3 yr on the Texas Tech University Native Rangeland, Lubbock, TX, USA. Independent variables included plant length and area measurements (basal area and cross-sectional area at a 7.5-cm plant height and at 50% of total plant height). One hundred randomly selected plants of each species were measured in June 2008; 50 plants of each species were measured in June 2009 and 2010. Coefficients of determination exceeded 0.91 for both species in all 3 yr of measurement. For both species and years, cross-sectional area at 7.5 cm was the most important single predictor variable. For each species, models differed among years. Our regression models were successful at predicting mid- to late-season standing crop of purple threeawn and blue grama grass and provide an effective method for nondestructive monitoring of these species. This approach should be applicable to similar morphotypes of these species.