Yin Hong, Mo Wenlong, Li Luqiao, Ma Yiting, Chen Jinhong, Zhu Shuijin, Zhao Tianlun
College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China.
Hainan Institute, Zhejiang University, Sanya 572025, China.
Foods. 2024 May 20;13(10):1584. doi: 10.3390/foods13101584.
Cottonseed is rich in oil and protein. However, its antinutritional factor content, of phytic acid (PA), has limited its utilization. Near-infrared (NIR) spectroscopy, combined with chemometrics, is an efficient and eco-friendly analytical technique for crop quality analysis. Despite its potential, there are currently no established NIR models for measuring the PA content in fuzzy cottonseeds. In this research, a total of 456 samples of fuzzy cottonseed were used as the experimental materials. Spectral pre-treatments, including first derivative (1D) and standard normal variable transformation (SNV), were applied, and the linear partial least squares (PLS), nonlinear support vector machine (SVM), and random forest (RF) methods were utilized to develop accurate calibration models for predicting the content of PA in fuzzy cottonseed. The results showed that the spectral pre-treatment significantly improved the prediction performance of the models, with the RF model exhibiting the best prediction performance. The RF model had a coefficient of determination in prediction ) of 0.9114, and its residual predictive deviation (RPD) was 3.9828, which indicates its high accuracy in measuring the PA content in fuzzy cottonseed. Additionally, this method avoids the costly and time-consuming delinting and crushing of cottonseeds, making it an economical and environmentally friendly alternative.
棉籽富含油脂和蛋白质。然而，其抗营养因子植酸（PA）的含量限制了它的利用。近红外（NIR）光谱结合化学计量学，是一种用于作物品质分析的高效且环保的分析技术。尽管有其潜力，但目前尚无用于测定毛棉籽中PA含量的成熟近红外模型。在本研究中，共使用456份毛棉籽样品作为实验材料。应用了包括一阶导数（1D）和标准正态变量变换（SNV）在内的光谱预处理，并利用线性偏最小二乘法（PLS）、非线性支持向量机（SVM）和随机森林（RF）方法建立了准确的校准模型，用于预测毛棉籽中PA的含量。结果表明，光谱预处理显著提高了模型的预测性能，其中RF模型表现出最佳的预测性能。RF模型的预测决定系数为0.9114，其剩余预测偏差（RPD）为3.9828，这表明它在测定毛棉籽中PA含量方面具有很高的准确性。此外，该方法避免了棉籽脱绒和粉碎的高成本和耗时过程，使其成为一种经济且环保的选择。
