A quantitative model for rapid detection of main quality indicators of peanut kernels using near-infrared spectroscopy
A rapid near-infrared spectroscopy method was established for determination of crude protein,crude fat,oleic acid,and linoleic acid content in peanut kernels.Near infrared spectra of the kernels were collected using a DA7200 near-infrared analyzer.The content of crude protein and crude fat were determined using Kjeldahl nitrogen determination method and Soxhlet extraction method,respectively.The relative content of oleic acid and linoleic acid was determined using gas chromatography.Partial least squares method was used to construct a near-infrared prediction model for the main quality indicators of peanut kernels.The results showed that the determination coefficients of the model for crude protein,crude fat,oleic acid,and linoleic acid content in peanut kernels were 0.927 0,0.964 7,0.991 5,and 0.991 5 with root mean square errors as 0.870 2,0.563 1,1.667 1,and 1.404 0,respectively.After external verification,the determination coefficients of the independent test set were 0.960 8,0.946 0,0.960 5,and 0.949 2,respectively.This model accurately predicted the content of crude protein,crude fat,oleic acid,and linoleic acid in peanut kernels,and achieved rapid and non-destructive determination of the main quality indicators of peanut kernels,which is helpful for improvement of breeding efficiency of high-quality peanut varieties.
万方数据
维普
