Abstract
［［Objective ］］ Improve the accuracy and robustness of maturity detection of pitaya fruit.［［Methods ］］ Combining the YOLOv 8 object detection model with the PSP -Ellipse segmentation algorithm,an efficient and accurate automatic identification method for pitaya fruit maturity was proposed.First,the real -time target detection function of YOLOv 8 was used to locate and identify the pitaya fruit initially.Then the shape recognition capability of PSP -Ellipse was used to further fine classify the shape and maturity of the pitaya fruit.［［Results］］ The accuracy rate of maturity classification of pitaya fruit was 97.6%,and the robustness was strong.［［Conclusion ］］ This method can significantly improve the automatic classification efficiency of pitaya fruit under complex backgrounds and various lighting conditions.
Publication Date
2-18-2025
First Page
122
Last Page
128
DOI
10.13652/j.spjx.1003.5788.2024.60121
Recommended Citation
Xinpu, LIU; Chunlei, ZHAO; Zhifeng, LI; and Chao, FENG
(2025)
"Ripeness identification of pitaya fruit based on YOLOv 8 and PSP-Ellipse,"
Food and Machinery: Vol. 40:
Iss.
10, Article 18.
DOI: 10.13652/j.spjx.1003.5788.2024.60121
Available at:
https://www.ifoodmm.cn/journal/vol40/iss10/18
References
[1] 陈岚,谷会,李娅,等.赤霉素复合壳聚糖处理后火龙果贮藏品质及内源激素的变化 [J/OL ].现代食品科技.(2024 -03-09)
[2024 -08-26].https://doi.org/10.13982 /j.mfst.1673 -9078.2024.12.1451.CHEN L,GU H,LI Y,et al.Changes in storage quality and endogenous hormones of pitaya after gibberellin composite chitosan treatment [J/OL ].Modern Food Science and Technology.(2024 -03-09) [2024 -08-26].https://doi.org/10.13982 /j.mfst.1673 -9078.2024.12.1451.
[2] 梁英凯,商枫楠,陈桥,等.基于机器视觉与机器学习的火龙果重量估计 [J].食品与机械,2023,39(7):99-103.LIANG Y K,SHANG F N,CHEN Q,et al.Dragon fruit weight estimation based on machine vision and machine learning [J].Food & Machinery,2023,39(7):99-103.
[3] 王斌,袁晓,林冲,等.外源褪黑素处理对采后火龙果贮藏品质和活性氧清除能力的影响 [J].食品工业科技,2024,45(21):302-309.WANG B,YUAN X,LIN C,et al.Effects of exogenous melatonin treatment on storage quality and ROS scavenging capacity of harvested pitaya fruit [J].Science and Technology of Food Industry,2024,45(21):302-309.
[4] 白蓓蓓,郑燕萍,陈黎明,等.不同着色火龙果成熟过程中花青素代谢途径相关酶活分析 [J/OL ].分子植物育种.(2024 -02-22) [2024 -08-26].http://kns.cnki.net/kcms/detail/ 46.1068.S.20240222.1143.004.html.BAI B B,ZHENG Y P,CHEN L M,et al.Analysis of enzyme activity related to anthocyanin metabolism pathway in different colored pitaya fruit during ripening [J/OL ].Molecular Plant Breeding.(2024 -02-22) [2024 -08-26].http://kns.cnki.net/kcms/detail/ 46.1068.S.20240222.1143.004.html.
[5] 马瑞峻,何浣冬,陈瑜,等.基于改进 YOLOv 5的火龙果成熟度识别方法 [J].沈阳农业大学学报,2023,54(2):196-206.MA R J,HE H D,CHEN Y,et al.Recognition method for maturity of pitaya based on improved YOLOv 5[J].Journal of Shenyang Agricultural University,2023,54(2):196-206.
[6] 徐婷婷,宋亮,卢学鹤,等.基于 YOLO v 7-RA的火龙果品质与成熟度双指标检测方法 [J].农业机械学报,2024,55(7):405-414.XU T T,SONG L,LU X H,et al.Dual-index detection method of pitaya quality and maturity based on YOLO v 7-RA[J].Transactions of the Chinese Society for Agricultural Machinery,2024,55(7):405-414.
[7] NGUYEN H H C,JANA C,HEZAM I M,et al.Identification of dragon trees and fruits in ham Thuan Bac growing areas,Phan Thiet city,Binh Thuan province,Vietnam [J].Heliyon,2024,10(10):e31233.
[8] CHEN L B,HUANG X R,CHEN W H.Design and implementation of an artificial intelligence of things-based autonomous mobile robot system for pitaya harvesting [J].IEEE Sensors Journal,2023,23(12):13 220-13 235.
[9] VO H T,THIEN N N,MUI K C.A deep transfer learning approach for accurate dragon fruit ripeness classification and visual explanation using Grad-CAM [J].International Journal of Advanced Computer Science & Applications,2023,14(11):1 344-1 352.
[10] QIU Z,HUANG Z Y,MO D Y,et al.GSE-YOLO:a lightweight and high-precision model for identifying the ripeness of pitaya (dragon fruit ) based on the YOLOv 8n improvement [J].Horticulturae,2024,10(8):852.
[11] WANG X G,CHEN J Y,LUO D L,et al.Advances in the understanding of postharvest physiological changes an d the storage and preservation of pitaya [J].Foods,2024,13(9):1 307.
[12] CARMEN F,FRANCES C,BARTHE L.Trends on valorization of pitaya fruit biomass through value-added and green extraction technology:a critical review of advancements and processes [J].Trends in Food Science & Technology,2023,138:339-354.
[13] ILHAN G.Analysis of sensory,morphological and biochemical characteristics in fruits of different red-fleshed Pitaya (Hylocereus polyrhizus ) accessions [J].Erwerbs-Obstbau,2023,65(5):1 803-1 810.
[14] 孔凡国,李志豪,仇展明,等.基于改进 YOLOv 5-s的火龙果多任务识别与定位 [J].电子测量技术,2023,46(18):155-162.KONG F G,LI Z H,CHOU Z M,et al.Multitasking recognition and positioning of pitaya based on improved YOLOv 5-s[J].Electronic Measurement Technology,2023,46(18):155-162.
[15] 朱立学,赖颖杰,张世昂,等.基于改进 U-Net的火龙果采摘图像分割和姿态估计方法 [J].农业机械学报,2023,54(11):180-188.ZHU L X,LAI Y J,ZHANG S A,et al.Image segmentation and pose estimation method for pitaya picking robot based on enhanced U-Net [J].Transactions of the Chinese Society for Agricultural Machinery,2023,54(11):180-188.
[16] LI H,GU Z,HE D,et al.A lightweight improved YOLOv 5s model and its deployment for detecting pitaya fruits in daytime and nighttime light-supplement environments [J].Computers and Electronics in Agriculture,2024,220:108914.
[17] 唐兴萍,王白娟,杨红欣,等.基于 YOLOv 8的水果外观检测与分类方法 [J].食品与机械,2024,40(7):103-110.TANG X P,WANG B J,YANG H X,et al.Research on fruit appearance detection and classification method based on YOLOv 8[J].Food & Machinery,2024,40(7):103-110.
[18] 岳有军,漆潇,赵辉,等.基于改进 YOLOv 8的果园复杂环境下苹果检测模型研究 [J/OL ].南京信息工程大学学报.(2024 -07-15) [2024 -08-26].https://doi.org/10.13878 /j.cnki.jnuist.20240410002.YUE Y J,QI X,ZHAO H,et al.Research on apple detection model in complex orchard environments based on improved YOLOv 8[J/OL ].Journal of Nanjing University of Information Science & Technology.(2024 -07-15) [2024 -08-26].https://doi.org/10.13878 /j.cnki.jnuist.20240410002.
[19] 漆海霞,冯发生,尹选春,等.轻量级多场景群养猪只行为识别模型研究与部署 [J/OL ].农业机械学报.(2024 -08-20)
[2024 -08-26].http://kns.cnki.net/kcms/detail/ 11.1964.s.20240816.1947.014.html.QI H X,FENG F S,YIN X C,et al.Research and deployment of lightweight multi-scene group pig behavior recognition model [J/OL ].Transactions of the Chinese Society for Agricultural Machinery.(2024 -08-20) [2024 -08-26].http://kns.cnki.net/kcms/detail/ 11.1964.s.20240816.1947.014.html.
[20] WANG L,ZHENG H,YIN C,et al.Dense papaya target detection in natural environment based on improved YOLOv 5s[J].Agronomy,2023,13(8):2 019.
[21] 王卓,瞿绍军.基于注意力机制与多尺度池化的实时语义分割网络 [J].计算机工程,2023,49(10):222-229,238.WANG Z,QU S J.Real-time semantic segmentation network based on attention mechanism and multi-scale pooling [J].Computer Engineering,2023,49(10):222-229,238.
[22] CHEN X D,QIAN C,ZHAO M,et al.Improving ellipse fitting via multi-scale smoothing and key-point searching [J].Pattern Recognition,2024,151:110432.
[23] 刘国权,陈尚良,李跃忠,等.基于 SGD和余弦退火算法改进YOLOv 3的高压电力设备目标检测方法 [J].东华理工大学学报(自然科学版 ),2024,47(3):294-300.LIU G Q,CHEN S L,LI Y Z,et al.An Improved YOLOv 3 target detection method for high voltage power equipment based on SGD and cosine annealing algorithm [J].Journal of East China University of Technology (Natural Science ),2024,47(3):294-300.
[24] 张家棋,李觉友.一类自适应梯度裁剪的差分隐私随机梯度下降算法 [J].运筹学学报 (中英文 ),2024,28(2):47-57.ZHANG J Q,LI J Y.A class of differential privacy stochastic gradient descent algorithm with adaptive gradient clipping [J].Operations Research Transactions,2024,28(2):47-57.