Developing Calibration Model for Prediction of Malt Barley Genotypes Quality Traits using Fourier Transform near Infrared Spectroscopy

Yadesa Abeshu () and Ashagrie Zewdu ()

Agriculture and Food Sciences Research, 2020, vol. 7, issue 1, 38-45

Abstract: Ethiopia is the second largest barley producer in Africa. But the quality traits are always influenced by the cultivar itself and growing environment. Thus, the study was targeted on developing calibration model for predicting malt barley quality traits of genotypes grown at different locations using near infra-red spectroscopy for selection purposes in barley breeding program. For this purpose, 60 barley samples were collected from Holeta, Debre-Birhan and Bekoji. Samples were chemically analyzed in duplicate for 5 barley traits. The calibration model was developed based on 120 samples spectral data and 60 chemistry data results using the calibration software of the FT-Near Infrared Spectroscopy. The barley 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 β-Glucan calibration model (R²c= 0.90; RPD=3.18) allowed only for screening purpose in some applications. Barley grain dry matter with model parameters result (R2c=0.86; RPD=2.69)shown usable with caution only for rough screening purposes. Hence near infrared spectroscopy is fast and cost-efficient, the breeding program can increase the intensity of variety selection using calibration models reflected good predicting performances except models for dry matter and β-glucan.

Keywords: Barley; Genotypes; Malt; Trait; Near infrared spectroscopy; Calibration; Validation. (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
https://asianonlinejournals.com/index.php/AESR/article/view/1503/1288 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aoj:agafsr:v:7:y:2020:i:1:p:38-45:id:1503

Access Statistics for this article

More articles in Agriculture and Food Sciences Research from Asian Online Journal Publishing Group
Bibliographic data for series maintained by Sara Lim ().