In:
Journal of the American Oil Chemists' Society, Wiley, Vol. 97, No. 4 ( 2020-04), p. 331-340
Abstract:
Rapid and accurate analysis of cottonseed protein content and the composition of fatty acids (especially, saturated fatty acids) is often required in cotton production and breeding programs. This study aimed to establish a set of effective estimation models for these parameters. Near infrared reflectance spectroscopy (NIRS) calibration equations using partial least‐squares regression for protein concentration, oil concentration, and five fatty acids of shell‐intact cottonseeds were established based on 90 varieties, and the prediction abilities of the calibration models were verified using 45 other varieties. The prediction abilities of the NIRS calibration equations were basically consistent with external validation results. Each equation was assessed based on the ratio of performance to deviation (RPD p ). Protein content and seed total fatty acid (STA) content had high RPD p values (3.687 and 3.530, respectively), whereas cottonseed kernel total fatty acid (KTA) content, linoleic acid (18:2), stearic acid (18:0), myristic acid (14:0), and palmitic acid (16:0) exhibited relatively high RPD p (2.866, 2.836, 2.697, 2.676, and 2.506, respectively). The calibration model for oleic acid (18:1) had a low RPD p (1.945). The results indicated that NIRS can be used to rapidly determine contents of STA, KTA, protein, stearic acid (18:0), myristic acid (14:0), and palmitic acid (16:0) in shell‐intact cottonseed.
Type of Medium:
Online Resource
ISSN:
0003-021X
,
1558-9331
Language:
English
Publisher:
Wiley
Publication Date:
2020
detail.hit.zdb_id:
2041388-9
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