Prediction Model Establishment for Routine Nutrient of Peanut Vine by Near-Infrared Reflectance Spectroscopy

FENG Dou, CAI Amin, XUE Xiao, LI Minjie, LI Gaiying, FU Tong, GAO Tengyun

doi:10.3969/j.issn.1006-267x.2019.01.053

Chinese Journal of Animal Nutrition >

2019 , Vol. 31 >Issue 1: 452 - 458

DOI: https://doi.org/10.3969/j.issn.1006-267x.2019.01.053

Molecular Nutrition

Prediction Model Establishment for Routine Nutrient of Peanut Vine by Near-Infrared Reflectance Spectroscopy

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College of Animal Science and Veterinary Medicine, Henan Agricultural University, Zhengzhou 450002, China

Received date: 2018-06-12

Online published: 2019-01-16

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Abstract

In order to explore the application feasibility of prediction of routine nutrient of peanut vine by near-infrared reflectance spectroscopy (NIRS) technology, a total of 107 peanut vine samples in Henan province were collected, the samples were divided into calibration set (n=83) and verification set (n=24), the 8 kinds of routine nutrient contents in peanut vine were analyzed included:dry matter (DM), ether extract (EE), crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), crude ash (Ash), calcium (Ca) and phosphorus (P), and calculated the correlation between predicted value and measured value of verification set, verified the accuracy of the model. The results showed that after pre-treatment of standard normal variate (SNV) + 1st derivative, the predictive effect of DM content in peanut vine was the best[calibration correlation coefficient (RSQcal)=0.989, coefficient of determination (RSQv)=0.968 2]; after pre-treatment of SNV+detrended correction+1st derivative, the predictive effect of NDF content was the best (RSQcal=0.966, RSQv=0.937 3); after pre-treatment of SNV+detrended correction+2nd derivative, the predictive effect of CP content was the best (RSQcal=0.923, RSQv=0.903 6); after different pre-treatment, the RSQcal of ADF and EE contents were > 0.7, and 0.9 > RSQv > 0.7; and the RSQcal of Ca, P and Ash contents were < 0.7, RSQv < 0.7, the predictive effect was not satisfactory. It is concluded that the contents of DM, NDF and CP in peanut vine can be accurately predicted by NIRS technology, the contents of EE and ADF can be predicted roughly, while the contents of Ca, P and Ash cannot be predicted.

Key words： NIRS; peanut vine; routine nutrient

Cite this article

FENG Dou, CAI Amin, XUE Xiao, LI Minjie, LI Gaiying, FU Tong, GAO Tengyun . Prediction Model Establishment for Routine Nutrient of Peanut Vine by Near-Infrared Reflectance Spectroscopy[J]. Chinese Journal of Animal Nutrition, 2019 , 31(1) : 452 -458 . DOI: 10.3969/j.issn.1006-267x.2019.01.053

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