Developing Calibration Model for Prediction of Malt Barley and Teff Genotypes Quality Traits Using Near Infrared Spectroscopy (Nirs)
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Date
2019-06-24
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Addis Ababa University
Abstract
Barley is one of the most important cereal crop largely produced in Ethiopian central, mid and high altitude areas. Even if the country is the second largest barley producer in Africa next to Morocco, the quality traits are always influenced by the cultivar itself and growing environment. Teff is also cultivated in Ethiopia widely as first among common cereals in area coverage and 2/3 of the population daily protein intake. Similarly it is globally interesting crop because of its whole grain nutritional merits and gluten free protein. However, breeders need simple and fast methods to select good quality traits of these crops in their breeding program to meet the targeted end use. Thus the study was targeted on developing calibration model for predicting malt barley and teff quality traits for genotypes grown at different locations using near infra-red spectroscopy. For this purpose 60 barley samples were collected from Holeta, Debre-Birhan and Bekoji, in similar way 60 teff samples were also collected from Holeta, Debre-Zeit and Ginchi. These samples were chemically analyzed for barley traits extract(%), protein(%), friability(%), beta-glucan(mg/L) and moisture(%), for teff traits protein(%) and moisture(%) using international methods. For barley and teff traits mentioned above, calibration model was developed using 120 samples in duplicate based on the calibration software of the Fourier Transform Near Infrared Spectroscopy. The barley and teff Protein calibration model having (R²c= 0.97; RPD=5.7 and R2c=0.94; RPD=4.16) respectively, can be regarded as broadly applicable; Extract and Friability (R²c= 0.96; RPD=4.54 and R2c=0.95; RPD=4.36) respectively were accepted as useable with good prediction capability; whereas ß-Glucan calibration model (R²c= 0.90; RPD=3.18) allowed only for screening purpose in some applications, because it delivered less trusted model as its model statistical parameters reflected. Barley and teff grain dry matter with model parameters result(R2c=0.86; RPD=2.69 and R2c=0.87; RPD=2.77) respectively shown less performed as compared to others, but were usable with caution for rough screening purposes. Therefore, since near infrared spectroscopy is fast and cost-efficient the breeding program can increase the intensity of variety selection using these models.
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Barley, Teff, Malt, Trait, Near Infrared Spectroscopy, Calibration, Validation