Abstract
[Objective] To address the long detection cycles, complex operation, and destructive sampling in apple freshness detection, a rapid and non-destructive detection method based on Zigbee wireless sensor network and partial least squares-discriminant analysis (PLS-DA) is proposed. [Methods] With Red Fuji apples as the research object, a gas sensor array acquisition system based on the Zigbee protocol is designed to monitor the concentration changes of four characteristic gases (ethanol, ethylene, oxygen, and carbon dioxide) during apple storage in real time. Least squares filtering is employed to preprocess the raw data, and the stable value, mean value, and maximum value are extracted as freshness feature parameters. A PLS-DA model is constructed to achieve rapid discrimination of apple freshness levels (fresh, sub-fresh, and rotten). [Results] Under indoor storage conditions of 20 ℃ and 50% relative humidity, the four gas sensors exhibit obvious response characteristics to apple volatile gases, with significant differences in gas concentrations among different freshness levels. The first three latent variables of the PLS-DA model cumulatively explain 92.47% of variance, with samples from the training set and prediction set forming clear clusters by category. The overall recognition accuracy of the model for 36 samples in the prediction set reaches 94.44%, with recognition accuracy of 100.00%, 91.67%, and 91.67% for fresh, sub-fresh, and rotten samples, respectively. [Conclusion] This method enables rapid and non-destructive detection of apple freshness.
Publication Date
9-20-2026
First Page
115
Last Page
123
DOI
10.13652/j.spjx.1003.5788.2026.60067
Recommended Citation
Haiyang, Huang; Liqiu, Qu; and Yunlong, Ma
(2026)
"Detection of apple freshness during storage based on Zigbee network and PLS-DA,"
Food and Machinery: Vol. 42:
Iss.
8, Article 15.
DOI: 10.13652/j.spjx.1003.5788.2026.60067
Available at:
https://www.ifoodmm.cn/journal/vol42/iss8/15
References
[1] Sehgal S,Swer T L,Bhalla A,et al.Quality and safety of the frying oils used in small or medium-sized food enterprises in west Delhi,India [J].Oriental Journal of Chemistry,2021,37(3):547-552.
[2] 闫转红,王伟.基于气体传感器阵列的苹果甜度识别技术研究[J].国外电子测量技术,2021,40(10):71-76.Yan Z H,Wang W.Research on apple sweetness recognition technology based on gas sensor array [J].Foreign Electronic Measurement Technology,2021,40(10):71-76.
[3] Dou X J,Zhang L X,Yang R N,et al.Adulteration detection of essence in sesame oil based on headspace gas chromatography-ion mobility spectrometry [J].Food Chemistry,2022,370:131373.
[4] 刘云刚,王伟.基于SFLA优化的BP神经网络苹果鲜度气味识别系统 [J].传感器与微系统,2020,39(8):96-99,106.Liu Y G,Wang W.Apple fresh odor recognition system based on SFLA optimized BP neural network [J].Transducer and Microsystem Technologies,2020,39(8):96-99,106.
[5] 马惠玲,曹梦柯,王栋,等.苹果货架期GAN-BP-ANN预测模型研究 [J].农业机械学报,2021,52(11):367-375.Ma H L,Cao M K,Wang D,et al.Study on shelf-life prediction of apple with GAN-BP-ANN model [J].Transactions of the Chinese Society for Agricultural Machinery,2021,52(11):367-375.
[6] Jiang H Y,Cui Y Y,Jia Y G.Edible oil identification technology based on three-dimensional fluorescence spectroscopy and MPCA-LDA [J].IEEE Access,2024,12:52 496-52 502.
[7] 陈远涛,熊忆舟,薛莹莹,等.基于深度学习的电子鼻食品新鲜度检测与识别技术研究 [J].传感技术学报,2021,34(8):1 131-1 138.Chen Y T,Xiong Y Z,Xue Y Y,et al.Research on electronic nose food freshness detection and recognition technology based on deep learning [J].Chinese Journal of Sensors and Actuators,2021,34(8):1 131-1 138.
[8] 徐静,赵秀洁,孙柯,等.基于电子鼻和乙醇传感器判别草莓新鲜度的研究 [J].食品与机械,2016,32(5):117-121.Xu J,Zhao X J,Sun K,et al.Determination on freshness of strawberry based on electronic nose and ethanol sensor [J].Food & Machinery,2016,32(5):117-121.
[9] 黎新荣.电子鼻在沃柑贮藏时间识别中的应用 [J].南方农业学报,2018,49(9):1 827-1 832.Li X R.Application of electronic nose in identification for storage time of orah [J].Journal of Southern Agriculture,2018,49(9):1 827-1 832.
[10] Bleibaum R N,Stone H,Tan T,et al.Comparison of sensory and consumer results with electronic nose and tongue sensors for apple juices [J].Food Quality and Preference,2002,13(6):409-422.
[11] Cheng P H,Jiang X G,Liu Y D.FT-NIR spectroscopy combined with PLS-DA-SVM for adulteration detection in Xinyang Maojian tea [J].Journal of Food Composition and Analysis,2025,148:108667.
[12] Cui Y Y,Kong D M,Kong L F,et al.Excitation emission matrix fluorescence spectroscopy and parallel factor framework-clustering analysis for oil pollutants identification[J].Spectrochimica Acta Part A:Molecular and Biomolecular Spectroscopy,2021,253:119586.
[13] 孙健飞,王莉,王建鹏.基于改进YOLOv5s的水果新鲜度检测算法研究 [J].现代电子技术,2024,47(22):37-43.Sun J F,Wang L,Wang J P.Research on fruit freshness detection algorithm based on improved YOLOv5s[J].Modern Electronics Technique,2024,47(22):37-43.
[14] 杨明丽,纠海峰,邓薇.基于气味检测的红富士苹果新鲜度识别方法研究 [J].国外电子测量技术,2024,43(10):91-101.Yang M L,Jiu H F,Deng W.Research on the freshness recognition method of red Fuji apples based on odor detection[J].Foreign Electronic Measurement Technology,2024,43(10):91-101.
[15] 沈海军,张汤磊,许振兴,等.基于Fisher判别分析对苹果新鲜度的识别研究 [J].食品工业科技,2023,44(4):361-368.Shen H J,Zhang T L,Xu Z X,et al.Recognition of apple freshness based on Fisher discriminant analysis [J].Science and Technology of Food Industry,2023,44(4):361-368.
[16] 段智英,刘憬璇,李丽丽,等.基于冻结过程分析高压脉冲电场辅助对冷冻苹果品质的影响 [J].食品与机械,2025,41(9):15-22.Duan Z Y,Liu J X,Li L L,et al.Effect of high-voltage pulsed electric field on the quality of frozen apple based on freezing process [J].Food & Machinery,2025,41(9):15-22.
[17] 张瑞琪,杨宁,张一枫.基于改进CNN-SVM和机器视觉的苹果自动分级方法研究 [J].食品与机械,2025,41(9):75-81.Zhang R Q,Yang N,Zhang Y F.An automatic grading method for apples based on improved CNN-SVM and machine vision[J].Food & Machinery,2025,41(9):75-81.
