林卫国 , 李云川 , 陈先圣 , 周大猷 , 王大臣 , 王英力 , 黄远 . 基于机器学习的水果成熟度无损检测技术研究进展[J]. 植物学报, 2026 , 61(4) : 549 -714 . DOI: 10.11983/CBB25224

Amaral MH, Walsh KB (2023). In—orchard sizing of mango fruit: 2. Forward estimation of size at harvest. Horticulturae 9, 54.

Aouadi B, Zaukuu JLZ, Vitális F, Bodor Z, Fehér O, Gillay Z, Bazar G, Kovacs Z (2020). Historical evolution and food control achievements of near infrared spectroscopy, electronic nose, and electronic tongue—critical overview. Sensors 20, 5479.

Arai N, Miyake M, Yamamoto K, Kajiwara I, Hosoya N (2021). Soft mango firmness assessment based on rayleigh waves generated by a laser—induced plasma shock wave technique. Foods 10, 323.

Bai JH, Jordán MJ, Li J (2022). Editorial: metabolism of fruit volatile organic compounds. Front Plant Sci 13, 873515.

Batista—Silva W, Nascimento VL, Medeiros DB, Nunes—Nesi A, Ribeiro DM, Zsögön A, Araújo WL (2018). Modifications in organic acid profiles during fruit development and ripening: correlation or causation? Front Plant Sci 9, 1689.

Betemps DL, Fachinello JC, Galarça SP, Portela NM, Remorini D, Massai R, Agati G (2012). Non—destructive evaluation of ripening and quality traits in apples using a multiparametric fluorescence sensor. J Sci Food Agric 92, 1855-1864.

Bhargava A, Sachdeva A, Sharma K, Alsharif MH, Uthansakul P, Uthansakul M (2024). Hyperspectral imaging and its applications: a review. Heliyon 10, e33208.

Chen N, Le DX, Liu Z, Wan X, Li B, Wu J, Liu YD (2025a). Combination of Laser Doppler Vibrometry (LDV) and Vis/NIRs to predict the firmness of crown pears. J Food Sci 90, e70391.

Chen N, Liu Z, Le DX, Lai QR, Jiang BN, Li B, Wu J, Song YF, Liu YD (2025b). Prediction of yellow flesh peach firmness using a novel device and data augmentation acoustic vibration multi—domain images array Swin Transformer (DA—AVMDIA—SwinT). Comput Electron Agric 235, 110402.

Chen N, Liu Z, Zhang TY, Lai QR, Zhang JS, Wei XL, Liu YD (2024). Research on prediction of yellow flesh peach firmness using a novel acoustic real—time detection device and Vis/NIR technology. LWT—Food Sci Technol 209, 116772.

Choe U, Kang H, Ham J, Ri K, Choe U (2022). Maturity assessment of watermelon by acoustic method. Sci Hortic 293, 110735.

Christopher CT, Fath Elbab AMR, Osueke CO, Ikua BW, Sila DN, Fouly A (2022). A piezoresistive dual—tip stiffness tactile sensor for mango ripeness assessment. Cogent Eng 9, 2030098.

Chu X, Miao P, Zhang K, Wei HY, Fu H, Liu HL, Jiang HZ, Ma ZY (2022). Green banana maturity classification and quality evaluation using hyperspectral imaging. Agriculture 12, 530.

Chuquimarca LE, Vintimilla BX, Velastin SA (2025). Assessing deep learning model robustness for banana ripeness classification under varying illumination conditions. Smart Agric Technol 12, 101333.

Feng SN, Shang J, Tan T, Wen QC, Meng QL (2023). Nondestructive quality assessment and maturity classification of loquats based on hyperspectral imaging. Sci Rep 13, 13189.

Garillos—Manliguez CA, Chiang JY (2021). Multimodal deep learning and visible—light and hyperspectral imaging for fruit maturity estimation. Sensors 21, 1288.

Hou JM, He ZH, Liu DY, Zhu ZA, Long ZH, Yue X, Wang W (2023). Mechanical damage characteristics and non—destructive testing techniques of fruits: a review. Food Sci Technol 43, e001823.

Huang ZB, Li XH, Fan ST, Liu Y, Zou H, He XC, Xu S, Zhao JH, Li WF (2025). ORD—YOLO: a ripeness recognition method for citrus fruits in complex environments. Agriculture 15, 1711.

Ibba P, Tronstad C, Moscetti R, Mimmo T, Cantarella G, Petti L, Martinsen ØG, Cesco S, Lugli P (2021). Supervised binary classification methods for strawberry ripeness discrimination from bioimpedance data. Sci Rep 11, 11202.

Islam M, Bijjahalli S, Fahey T, Gardi A, Sabatini R, Lamb DW (2024). Destructive and non—destructive measurement approaches and the application of AI models in precision agriculture: a review. Precis Agric 25, 1127-1180.

Jing XB, Wang YH, Li DX, Pan WH (2024). Melon ripeness detection by an improved object detection algorithm for resource constrained environments. Plant Methods 20, 127.

Kapoor L, Simkin AJ, Doss CGP, Siva R (2022). Fruit ripening: dynamics and integrated analysis of carotenoids and anthocyanins. BMC Plant Biol 22, 27.

Kaur S, Randhawa S, Malhi A (2021). An efficient ANFIS based pre—harvest ripeness estimation technique for fruits. Mult Tools Appl 80, 19459-19489.

Khan AA, Siddiqui Y, Tan GH, Ali A (2024). Application of electronic nose to monitor the quality and ripening stages of papaya during postharvest storage. ACS Food Sci Technol 4, 2550-2561.

Khumaidi A, Purwanto YA, Sukoco H, Wijaya SH (2022). Using fuzzy logic to increase accuracy in mango maturity index classification: approach for developing a portable near—infrared spectroscopy device. Sensors 22, 9704.

Lee JE, Kim MJ, Lee BY, Hwan LJ, Yang HE, Kim MS, Hwang IG, Jeong CS, Mo C (2025). Evaluating ripeness in post—harvest stored kiwifruit using VIS—NIR hyperspectral imaging. Postharvest Biol Technol 225, 113496.

Li YJ, Cao CH, Cao MK, Guo WC (2025). Transient sound signal analysis for watermelon ripeness detection using HHT and NMF. Comput Electron Agric 237, 110543.

Lin F, Chen DJ, Liu C, He JC (2024a). Non—destructive detection of golden passion fruit quality based on dielectric characteristics. Appl Sci 14, 2200.

Lin YF, Liang H, Tong JH, Shen HY, Fu XP, Wu CY (2024b). Design and feasibility analysis of a graded harvesting end—effector with the function of soluble solid content estimation. Int J Agric Biol Eng 17, 239-246.

Liu SH, Xue JL, Zhang TY, Lv PF, Qin HH, Zhao TX (2024a). Research progress and prospect of key technologies of fruit target recognition for robotic fruit picking. Front Plant Sci 15, 1423338.

Liu T, Jiang H, Chen QS (2020). Qualitative identification of rice actual storage period using olfactory visualization technique combined with chemometrics analysis. Microchem J 159, 105339.

Liu WY, Tan ZH, Xie WG (2025). A hand—like gripper embedded with flexible gel sensor for tomato harvesting: soft contact and intelligent ripeness sensing. J Food Meas Charact 19, 3150-3161.

Liu WZ, Zhou XJ, Ping FJ, Su Y, Ju YL, Fang YL, Yang JH (2024). Detection of key indicators of ripening quality in table grapes based on visible—near—infrared spectroscopy. Trans Chin Soc Agric Mach 55(2), 372-383. (in Chinese) 刘文政, 周雪健, 平凤娇, 苏媛, 鞠延仑, 房玉林, 杨继红 (2024). 基于可见—近红外光谱的鲜食葡萄成熟品质关键指标检测. 农业机械学报 55(2), 372-383.

Liu Y, Wei CJ, Yoon SC, Ni XZ, Wang W, Liu YZ, Wang DR, Wang XR, Guo XH (2024b). Development of multimodal fusion technology for tomato maturity assessment. Sensors 24, 2467.

Ma XT, Luo X, Guo GG, Zhang QZ, Luo HP (2025). Study on the maturity detection method of winter jujube (Ziziphus jujuba ‘Dongzao’) based on near—infrared spectroscopy technology . J Food Compost Anal 147, 108097.

Majadi M, Barkó A, Varga—Tóth A, Maukenovna ZS, Batirkhanovna DZ, Dilora S, Lukacs M, Kaszab T, Mednyánszky Z, Kovacs Z (2024). Quality assessment of reconstructed cow, camel and mare milk powders by near—infrared spectroscopy and chemometrics. Molecules 29, 3989.

Mohsan MM, Hasanen BB, Hassan T, Seneviratne L, Hussain I (2025). A wearable thumb device for fruit firmness estimation with vision—based tactile sensing. Comput Electron Agric 237, 110593.

Ni P, Niu H, Tang YR, Zhang YB, Zhang WY, Liu Y, Lan HP (2023). Bibliometrics and visual analysis of non—destructive testing technology for fruit quality. Horticulturae 9, 1091.

Nie LC, Sun JS, Huang RH (2004). The biosynthesis and affecting factors of aroma in some fruits. Chin Bull Bot 21, 631-637. (in Chinese with English abstract) 乜兰春, 孙建设, 黄瑞虹 (2004). 果实香气形成及其影响因素. 植物学通报 21, 631-637.

Palumbo M, Cozzolino R, Laurino C, Malorni L, Picariello G, Siano F, Stocchero M, Cefola M, Corvino A, Romaniello R, Pace B (2022). Rapid and non—destructive techniques for the discrimination of ripening stages in candonga strawberries. Foods 11, 1534.

Pan LL, Li H, Zhao J (2023). Improvement of the prediction of a visual apple ripeness index under seasonal variation by NIR spectral model correction. Spectrochim Acta Part A Mol Biomol Spectrosc 302, 123075.

Peng ZZ, Liu GS, Li HL, Wang YX, Gao HY, Jemrić T, Fu DQ (2022). Molecular and genetic events determining the softening of fleshy fruits: a comprehensive review. Int J Mol Sci 23, 12482.

Qin LQ, Zhang JC, Stevan S, Xing SH, Zhang XS (2024). Intelligent flexible manipulator system based on flexible tactile sensing (IFMSFTS) for kiwifruit ripeness classification. J Sci Food Agric 104, 273-285.

Rizzo M, Marcuzzo M, Zangari A, Gasparetto A, Albarelli A (2023). Fruit ripeness classification: a survey. Artif Intell Agric 7, 44-57.

Sabzi S, Nadimi M, Abbaspour—Gilandeh Y, Paliwal J (2022). Non—destructive estimation of physicochemical properties and detection of ripeness level of apples using machine vision. Int J Fruit Sci 22, 628-645.

Shao YY, Wang YX, Xuan GT, Gao C, Wang KL, Gao ZM (2020). Visual detection of SSC and firmness and maturity prediction for Feicheng peach by using hyperspectral imaging. Trans Chin Soc Agric Mach 51(8), 344-350. (in Chinese) 邵园园, 王永贤, 玄冠涛, 高冲, 王凯丽, 高宗梅 (2020). 基于高光谱成像的肥城桃品质可视化分析与成熟度检测. 农业机械学报 51(8), 344-350.

Sinanoglou VJ, Tsiaka T, Aouant K, Mouka E, Ladika G, Kritsi E, Konteles SJ, Ioannou AG, Zoumpoulakis P, Strati IF, Cavouras D (2023). Quality assessment of banana ripening stages by combining analytical methods and image analysis. Appl Sci 13, 3533.

Su F, Zhao YP, Wang GH, Liu PZ, Yan YF, Zu LL (2022). Tomato maturity classification based on SE—YOLOv3—MobileNetV1 network under nature greenhouse environment. Agronomy 12, 1638.

Sui X, Zou JW, Geng ZL, Yang HJ, Hou JM, Feng LL (2025). Electrochemical impedance spectroscopy for pear ripeness detection and integration with robotic manipulators. Food Control 177, 111425.

Tang C, Chen D, Wang X, Ni XD, Liu YH, Liu YH, Mao X, Wang SM (2023). A fine recognition method of strawberry ripeness combining Mask R—CNN and region segmentation. Front Plant Sci 14, 1211830.

Teng XX, Zhang M, Mujumdar AS, Li CL (2025). 4D printed deformation labels with machine learning for monitoring and preservation of respiring climacteric fruits. Nat Commun 16, 11525.

Tian SP (2013). Molecular mechanisms of fruit ripening and senescence. Chin Bull Bot 48, 481-488. (in Chinese with English abstract) 田世平 (2013). 果实成熟和衰老的分子调控机制. 植物学报 48, 481-488.

Trebar M, Žalik A, Vidrih R (2024). Assessment of ‘Golden Delicious’ apples using an electronic nose and machine learning to determine ripening stages. Foods 13, 2530.

Vega Díaz JJ, Sandoval Aldana AP, Reina Zuluaga DV (2021). Prediction of dry matter content of recently harvested ‘Hass’ avocado fruits using hyperspectral imaging. J Sci Food Agric 101, 897-906.

Vega—Castellote M, Sánchez MT, Torres I, de la Haba MJ, Pérez—Marín D (2022). Assessment of watermelon maturity using portable new generation NIR spectrophotometers. Sci Hortic 304, 111328.

Wang DC, Li LL, Shi T, Cao J, Jiang XS, Jiang HZ, Feng Z, Zhou HP (2025a). Noncontact acoustic vibration method for firmness evaluation in multiple peach cultivars. Foods 14, 3899.

Wang F, Zhao CJ, Yang H, Jiang HZ, Li L, Yang GJ (2022a). Non—destructive and in—site estimation of apple quality and maturity by hyperspectral imaging. Comput Electron Agric 195, 106843.

Wang HG, Mei MW, Li JB (2023a). Research progress on non—destructive detection of internal quality of fruits with large size and thick peel: a review. Agriculture 13, 1838.

Wang P, Wang HF, Zou JL, Chen L, Chen HP, Hu Y, Wang F, Liu YP (2023b). Electronic nose and head space GC—IMS provide insights into the dynamic changes and regularity of volatile compounds in Zangju (Citrus reticulata cv. Manau Gan) peel at different maturation stages . Molecules 28, 5326.

Wang Q, Lu JZ, Wang YH, Miao FJ, Liu SP, Shui QY, Gao JF, Gao YW (2025b). In situ nondestructive identification of citrus fruit ripeness via hyperspectral imaging technology . Plant Methods 21, 77.

Wang W, Zhang YQ, Zhang J, Ou Y, Li MR (2021). A tactile—based maturity perception method for kiwifruit using harvesting robots. Sci Technol Innov (18), 59-60, 64—65. (in Chinese) 王雯, 张叶清, 张静, 欧月, 李梦茹 (2021). 基于采摘机器人触觉的猕猴桃成熟度感知方法. 科技与创新 (18), 59—60, 64— 65.

Wang YF, Jin XY, Huang WT, Wang X, Yu WY (2026). FDFR—Net: a fruit ripeness classification method using multimodal learning technique. Exp Syst Appl 299, 130126.

Wang YW, Acharya TP, Malladi A, Tsai HJ, NeSmith DS, Doyle JW, Nambeesan SU (2022b). Atypical climacteric and functional ethylene metabolism and signaling during fruit ripening in blueberry (Vaccinium sp.) . Front Plant Sci 13, 932642.

Xi XB, Ding JY, Weng XX, Wang Y, Han LJ, Zou YH, Tang ZH, Zhang RH (2025). Tomato maturity detection method based on lightweight YOLO v5s—MCA. Trans Chin Soc Agric Mach 56(3), 383—391, 436. (in Chinese) 奚小波, 丁杰源, 翁小祥, 王昱, 韩连杰, 邹贇涵, 唐子昊, 张瑞宏 (2025). 基于轻量化YOLO v5s—MCA的番茄成熟度检测方法. 农业机械学报 56(3), 383—391, 436.

Xu TT, Song L, Lu XH, Zhang HD (2024). Dual—index detection method of pitaya quality and maturity based on YOLO v7—RA. Trans Chin Soc Agric Mach 55(7), 405-414. (in Chinese) 徐婷婷, 宋亮, 卢学鹤, 张海东 (2024). 基于YOLO v7—RA的火龙果品质与成熟度双指标检测方法. 农业机械学报 55(7), 405-414.

Yang L, Cui B, Wu JF, Xiao X, Luo Y, Peng QM, Zhang YL (2024). Automatic detection of banana maturity—application of image recognition in agricultural production. Processes 12, 799.

Ying YB, Rao XQ, Ma JF (2004). Methodology for nondestructive inspection of citrus maturity with machine vision. Trans Chin Soc Agric Eng 20(2), 144-147. (in Chinese) 应义斌, 饶秀勤, 马俊福 (2004). 柑橘成熟度机器视觉无损检测方法研究. 农业工程学报 20(2), 144-147.

You ZH, Zhao MM, Lu HZ, Chen HY, Wang YX (2024). Eye—readable and wearable colorimetric sensor arrays for in situ monitoring of volatile organic compounds . ACS Appl Mater Interfaces 16, 19359-19368.

Yu HL, Qian C, Chen ZY, Chen J, Zhao YX (2025). Ripe—detection: a lightweight method for strawberry ripeness detection. Agronomy 15, 1645.

Zhang H (2015). Research on fruit ripening boosts economic development—a profile of professor Shen Yuanyue from the college of plant science and technology, Beijing University of Agriculture. Technol Ind Across Straits 28(5), 107-108. (in Chinese) 张晗 (2015). 果实成熟研究助推经济发展——记北京农学院植物科学技术学院沈元月教授. 海峡科技与产业 28(5), 107-108.

Zhang L, Han AH, Huang YY, Wang RQ (2019). Electrical parameter variation during maturation of persimmon fruit. J Gansu Agric Univ 54(2), 199-204. (in Chinese) 张莉, 韩爱华, 黄云钰, 王瑞庆 (2019). 柿果实成熟期间电学参数变化. 甘肃农业大学学报 54(2), 199-204.

Zhang S, Shi L, Zhang BH (2011). The research of muskmelon maturity detection method based on acoustic characteristics. J Agric Mech Res 33(10), 126-129. (in Chinese) 张帅, 史磊, 张本华 (2011). 基于声学特性的香瓜成熟度检测方法. 农机化研究 33(10), 126-129.

Zhang W, Wang AC, Lv ZZ, Gao ZM (2020). Nondestructive measurement of kiwifruit firmness, soluble solid content (SSC), titratable acidity (TA), and sensory quality by vibration spectrum. Food Sci Nutr 8, 1058-1066.

Zhang YN, Chen YH, Bao YH, Wang XC, Xian JY (2024). Tomato maturity detection based on bioelectrical impedance spectroscopy. Comput Electron Agric 227, 109553.

Zhao MM, Lu HZ, You ZH, Chen HY, Wang X, Zhang YQ, Wang YX (2024a). Olfactory visualization sensing array made with CelluMOFs to predict fruit ripeness using deep learning. ACS Appl Mater Interfaces 16, 56623-56633.

Zhao MM, You ZH, Chen HY, Wang X, Ying YB, Wang YX (2024b). Integrated fruit ripeness assessment system based on an artificial olfactory sensor and deep learning. Foods 13, 793.

Zhao MR, Cang H, Chen HX, Zhang C, Yan TY, Zhang YF, Gao P, Xu W (2023). Determination of quality and maturity of processing tomatoes using near—infrared hyperspectral imaging with interpretable machine learning methods. LWT—Food Sci Technol 183, 114861.

Zhao XC (2017). Strengthen industrial development and enhance the competitiveness of China’s fruit industry. China Fruit News 34, 7. (in Chinese) 赵晓春 (2017). 加强产业化建设, 做强中国果业. 中国果业信息 34, 7.

Zhou JY, Sun R, Yu D, Lü YX, Han YL (2020). Identification of fig maturity based on near—infrared spectroscopy and partial least square—discriminant analysis. Food Mach 36(11), 107-111. (in Chinese) 周靖宇, 孙锐, 余多, 吕宇璇, 韩燕苓 (2020). 基于近红外技术和偏最小二乘判别法对无花果成熟度的快速判别. 食品与机械 36(11), 107-111.

Zhu KY, Li JJ, Zhang KX, Arunachalam C, Bhattacharya S, Lu RF, Li ZJ (2025). Foundation model—based apple ripeness and size estimation for selective harvesting. Comput Electron Agric 236, 110407.