OPTIMIZING NEAR INFRARED REFLECTANCE SPECTROSCOPY TO PREDICT NUTRITIONAL QUALITY IN CHICKPEA HAULMS FOR LIVESTOCK FEED
Asian Journal of Advances in Research, Volume 4, Issue 1,
The near infrared reﬂectance spectroscopy (NIRS) was used to develop calibration equations to predict chickpea haulm (Cicer arietinum) feed quality traits and mineral constituents. A total of 1348 cultivars of chickpea representing a nation-wide range of environments in Ethiopia and genotypic diversity (113 cultivars and 7 landraces) used in the framework of the Ethiopian National Chickpea Breeding and Genetics Program were scanned using a FOSS 5000 spectrophotometer. 130 samples representing the spectral characteristics of the chickpea haulms, selected using WinISI II software V.1.50, were chemically analyzed for the development of the calibration equations. A modiﬁed partial least-squares (MPLS) regression with cross validation was used to conﬁrm the equations and identify possible spectral outliers (GH-value>3, where GH is the Mahalanobis distance). Values for coeﬃcient of determination (R), standard error of prediction SEP(C) and ratio of performance deviation (RPD) were used for validation of the equations. Results showed ash (r =0.97; RPD=3.64), crude protein (r2= 0.99; RPD = 8.09), acid detergent ﬁber (r2 = 0.99; RPD = 6.43), neutral detergent ﬁber (r2=0.99; RPD = 6.65), lignin (r2 = 0.99; RPD =5), ME (r=0.99; RPD=24.3), IVOMD (r=0.99; RPD=26). These results show that the calibration equations can accurately predict nutritional quality traits of chickpea haulms. The use of the NIRS method can facilitate cost-eﬀective and rapid decision making by researchers and farmers.
- Calibration equations
- chickpea haulms
- multi-location trial
- nutritional quality.
How to Cite
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