赵娟,沈懋生,浦育歌,陈昂,李豪.基于近红外光谱与多品质指标的苹果出库评价模型研究[J].农业机械学报,2023,54(2):386-395.
ZHAO Juan,SHEN Maosheng,PU Yuge,CHEN Ang,LI Hao.Out-of-warehouse Evaluation and Prediction Model of Apple Based on Near-infrared Spectroscopy Combined with Multiple Quality Indexes[J].Transactions of the Chinese Society for Agricultural Machinery,2023,54(2):386-395.
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基于近红外光谱与多品质指标的苹果出库评价模型研究   [下载全文]
Out-of-warehouse Evaluation and Prediction Model of Apple Based on Near-infrared Spectroscopy Combined with Multiple Quality Indexes   [Download Pdf][in English]
投稿时间:2022-06-27  
DOI:10.6041/j.issn.1000-1298.2023.02.040
中文关键词:  苹果  近红外光谱  气调贮藏期  非线性自回归  综合评价
基金项目:国家自然科学基金项目(31701664)
作者单位
赵娟 西北农林科技大学 
沈懋生 西北农林科技大学 
浦育歌 西北农林科技大学 
陈昂 西北农林科技大学 
李豪 西北农林科技大学 
中文摘要:富士苹果在贮藏期后熟过程中其生理特性发生变化,不适宜的贮藏会影响出库品质和售卖价格。为使贮藏期果实以较好的品质出库销售,开展对贮藏后熟苹果品质模型研究,并在此基础上对苹果出库进行评价和预测。采集了全贮藏期不同时间苹果样本的近红外光谱和品质指标(可溶性固形物含量、硬度和失重率),分析贮藏期间果实漫反射光谱和品质指标变化规律,基于波长1000~2400nm范围内的漫反射光谱结合预处理和特征波长提取方法,建立贮藏期苹果品质的偏最小二乘(PLS)和带有反馈的非线性自回归(NARX)预测模型,根据行业标准确定苹果出库品质判断依据,采用基于熵权的TOPSIS法对果实出库品质进行综合评价,实现PLS对品质得分和NARX对多品质指标的预测。结果表明,在预测SSC含量、硬度和失重率时,最优模型分别为CARS-SPA-PLS、CARS-NARX和SPA-NARX,相关系数分别为0.914、0.796和0.918,均方根误差分别为0.511°Brix、0.475kg/cm2和0.682%;在预测品质得分时,PLS模型的相关系数与均方根误差分别为0.896和0.0434,NARX多输出模型的相关系数分别为0.794、0.785和0.905,均方根误差分别为0.308°Brix、0.492kg/cm2和0.714%。应用近红外光谱技术能实现对果实贮藏品质监测和出库品质筛选,可为高效贮藏管理技术提供方法。
ZHAO Juan  SHEN Maosheng  PU Yuge  CHEN Ang  LI Hao
Northwest A&F University
Key Words:apple  near infrared spectroscopy  controlled atmosphere storage  nonlinear autoregression  comprehensive assessment
Abstract:The physiological characteristics of Fuji apples change during the post-ripening process of storage. If the storage time is too short, the best edible quality cannot be achieved. Excessive storage will seriously reduce the quality, then affects the quality of out-of-warehouse and the selling price. In order to make the fruits during the storage period with better quality for sale, the study on the quality prediction model of apple during storage was carried out, and on this basis, the out-of-warehouse quality of apple was evaluated and predicted. The near-infrared spectrum and quality indexes (soluble solid content (SSC), hardness and weight loss rate) of apple at different times during the whole storage period were collected. The variation rule of fruit diffuse reflectance spectrum and quality index during storage was analyzed. Partial least squares (PLS) and nonlinear autoregressive with external input (NARX) prediction model for apple quality during storage was established based on the diffuse reflectance spectrum in the wavelength range of 1000~2400nm, combined with pretreatment and feature wavelength extraction. According to apple industry standards, the judgment basis of apple out-of-warehouse quality was determined, and the TOPSIS method based on entropy weight was used to comprehensively evaluate the fruit out-of-warehouse quality, and realize the prediction of the quality score by PLS and the prediction of multiple quality indexes by NARX. The results showed that when predicting SSC, hardness and weight loss rate, the optimal models were CARS-SPA-PLS, CARS-NARX and SPA-NARX, respectively, the correlation coefficients were 0.914, 0.796 and 0.918, and the root mean square errors were 0.511°Brix, 0.475kg/cm and 0.682%. When predicting quality scores, the correlation coefficient and root mean square error of the PLS model were 0.896 and 0.0434, respectively, the correlation coefficient of the NARX multi-output model were 0.794, 0.785 and 0.905, and the root mean square errors were 0.308°Brix, 0.492kg/cm2 and 0.714%. The application of near-infrared spectroscopy technology can realize the detection of fruit storage quality and the screening of quality of out-of-warehouse, and the research result can provide a method for efficient storage management technology.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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