Predicting Main Fatty Acids, Oil and Protein Content in Intact Single Seeds of Groundnut by near Infrared Reflectance Spectroscopy

Abstract:

Eighty-four, 61 and 105 groundnut seeds, including high oleate genotypes and F₂ seeds of normal oleate × high oleate crosses, genotypes with high or low oil and F₂ seeds from high oil × low oil crosses, and randomly selected samples representing various origins, different seed sizes, and varied seed coat color and protein content, were used to develop the NIRS models for main fatty acids, oil and protein. For oleic, linoleic and palmitic acid, the optimized spectrum pretreatment method was first derivative plus multiplicative scattering correction; for stearic acid and the four bad fatty acids, first derivative plus vector normalization. The R_cal² and RMSECV for oleic acid were 97.20% and 2.65%; for linoleic acid, 96.90% and 2.40%; and for palmitic acid, 93.39% and 0.53%, respectively. The best spectrum pretreatment method for oil and protein was first derivative plus multiplicative scattering correction and min-max normalization. For oil and protein, the R_cal² was 89.06% and 91.45%, and RMSECV, 0.89% and 0.78%, respectively. The NIRS models can be used to develop groundnut cultivars both with high oil and with high oleate to cater the growing need for biodiesel production.

• Periodical: Advanced Materials Research (Volumes 860-863)
• Pages: 490-496
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.860-863.490
• Online since: December 2013
• Authors: Chuan Tang Wang*, Xiu Zhen Wang, Yue Yi Tang, Qi Wu, Jian Zhi Xu, Dong Qing Hu, Bo Qu
• Keywords: Calibration Equation, Fatty Acid, Groundnut, Intact Single Seed, NIRS, Peanut

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