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ARS Home » Plains Area » El Reno, Oklahoma » Grazinglands Research Laboratory » Agroclimate and Natural Resources Research » Research » Publications at this Location » Publication #315697

Research Project: AGRICULTURAL LAND MANAGEMENT TO OPTIMIZE PRODUCTIVITY AND NATURAL RESOURCE CONSERVATION AT FARM AND WATERSHED SCALES

Location: Agroclimate and Natural Resources Research

Title: Canopy visible and near-infrared reflectance data to estimate alfalfa nutritive attributes before harvest

Author
item Starks, Patrick - Pat
item Turner, Kenneth - Ken
item Brown, Michael - Retired ARS Employee
item Venuto, Bradley - Retired ARS Employee

Submitted to: Crop Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/24/2015
Publication Date: 12/30/2015
Citation: Starks, P.J., Turner, K.E., Brown, M.A., Venuto, B.C. 2015. Canopy visible and near-infrared reflectance data to estimate alfalfa nutritive attributes before harvest. Crop Science. 56:484-494.

Interpretive Summary: Proximal sensing could help improve profit margins by timing the cutting or harvesting of alfalfa (Medicago sativa L.), in rapid assessment of nutritive values, such as total nitrogen (N), neutral detergent fiber (NDF), and acid detergent fiber (ADF) as well as nutritive quality indicators such as relative feed value (RFV) and a forage energy:protein ratio, over large areas devoted to growing alfalfa. Hyperspectral reflectance data were acquired over seven alfalfa cultivars for which total N, NDF, and ADF (as % of dry matter) were measured in the laboratory. Of the 580 samples of proximally-sensed data and corresponding N, ADF, and NDF values, 177 were used to develop calibration equations to predict total N, NDF, and ADF of the remaining 403 samples. Proximally-sensed values of NDF, ADF, and crude protein (CP = total N *6.25) were used to calculate RFV and total digestible nutrients:crude protein (TDN:CP) ratio. Measured total N, NDF, ADF, RFV, and the TDN:CP ratio were used to assess the accuracy of the corresponding predicted values from proximal sensing. Calibration equations explained from 78 to 83% of the variation in total N, NDF, and ADF. About 80% of the RFV-based hay grade classifications were correctly predicted. Predicted TDN:CP ratios accounted for about 78% of the variability of actual TDN:CP ratios. Reasonably accurate measurements of total N, NDF, ADF, and TDN:CP ratios of alfalfa herbage were obtained from proximally-sensed canopy reflectance data. Relative feed value was successfully predicted from proximal data, especially for the prime and hay grade 1 ca

Technical Abstract: Proximal sensing could help improve profit margins by timing the cutting or harvesting of alfalfa (Medicago sativa L.), in rapid assessment of nutritive values, such as total nitrogen (N), neutral detergent fiber (NDF), and acid detergent fiber (ADF) as well as nutritive quality indicators such as relative feed value (RFV) and a forage energy:protein ratio, over large areas devoted to growing alfalfa. Hyperspectral reflectance data were acquired over seven alfalfa cultivars for which total N, NDF, and ADF (as % of dry matter) were measured in the laboratory. Of the 580 samples of proximally-sensed data and corresponding N, ADF, and NDF values, 177 were used to develop calibration equations to predict total N, NDF, and ADF of the remaining 403 samples. Proximally-sensed values of NDF, ADF, and crude protein (CP = total N *6.25) were used to calculate RFV and total digestible nutrients:crude protein (TDN:CP) ratio. Measured total N, NDF, ADF, RFV, and the TDN:CP ratio were used to assess the accuracy of the corresponding predicted values from proximal sensing. Calibration equations explained from 78 to 83% of the variation in total N, NDF, and ADF. About 80% of the RFV-based hay grade classifications were correctly predicted. Predicted TDN:CP ratios accounted for about 78% of the variability of actual TDN:CP ratios. Reasonably accurate measurements of total N, NDF, ADF, and TDN:CP ratios of alfalfa herbage were obtained from proximally-sensed canopy reflectance data. Relative feed value was successfully predicted from proximal data, especially for the prime and hay grade 1 categories.