Modelling postharvest quality of blueberry affected by biological variability using image and spectral data

详细信息    查看全文

• 作者：Meng-Han Hu ; Qing-Li Dong and Bao-Lin Liu
• 刊名：Journal of the Science of Food and Agriculture
• 出版年：2016
• 出版时间：15 August 2016
• 年：2016
• 卷：96
• 期：10
• 页码：3365-3373
• 全文大小：1345K
• ISSN：1097-0010

文摘

Hyperspectral reflectance and transmittance sensing as well as near-infrared (NIR) spectroscopy were investigated as non-destructive tools for estimating blueberry firmness, elastic modulus and soluble solid content (SSC). Least squares–support vector machine models were established from these three spectra based on samples from three cultivars viz. Bluecrop, Duke and M2 and two harvest years viz. 2014 and 2015 for predicting blueberry postharvest quality.