Asian Journal of Advances in Research

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.