Abstract
Objective: Aiming to obtain the weight of fragrant pear quickly to provide a basis for developing the fragrant pear grading device. Methods: This method acquired RGB-D images of fragrant pear by Kinect camera and converted them into point cloud data. The point cloud data was pre-processed and interpolated to generate a fragrant pear model. Then calculated the size parameter of the fragrant pear model. Finally, using the fragrant pear's volume predicted its weight. Results: Experimental results showed that the average relative error of the volume was 2.8%. Then the volume of fragrant pears was calculated by the error-compensated measurement method of the body scale parameter, and its weight was predicted and compared with the actual weight. The experimental results showed that the average relative error of the predicted weight was 1.96%. Conclusion: The fragrant pear quality prediction method provides a reliable reference for developing fragrant pear grading equipment.
Publication Date
10-30-2023
First Page
77
Last Page
82,88
DOI
10.13652/j.spjx.1003.5788.2022.81098
Recommended Citation
Runzhi, ZHANG; Xiao, ZHANG; and Gang, WU
(2023)
"Prediction method of fragrant pear weight based on Kinect camera,"
Food and Machinery: Vol. 39:
Iss.
9, Article 12.
DOI: 10.13652/j.spjx.1003.5788.2022.81098
Available at:
https://www.ifoodmm.cn/journal/vol39/iss9/12
References
[1] 张峰, 蒋志琴, 陈小光, 等. 库尔勒香梨产业发展因素分析及对策建议[J]. 中国农学通报, 2021, 37（34）: 159-164.
ZHANG F, JIANG Z Q, CHEN X G, et al. The development factors of pyrus sinkiangensis 'Korla Xiangli' industry[J]. Chinese Agricultural Science Bulletin, 2021, 37（34）: 159-164.
[2] 马建江, 张萍, 薛根生. 新疆巴州库尔勒香梨发展分析与建议[J]. 北方园艺, 2016（5）: 191-194.
MA J J, ZHANG P, XUE G S. Analysis and suggestions for the development of korla fragrant pear in bazhou area of Xinjiang[J]. Northern Horticulture, 2016（5）: 191-194.
[3] 何天明, 黎秀丽, 吴玉霞, 等. 库尔勒香梨在疆内市场的商品分级与价格形成调查[J]. 新疆农业科学, 2010, 47（3）: 461-465.
HE T M, LI X L, WU Y X, et al. Investgation on commodity differentiation and price formation of kuerle fragrant pear[J]. Xinjiang Agricultural Sciences, 2010, 47（3）: 461-465.
[4] 陈於学, 宿磊, 杨丽, 等. 光学玻璃块滚筒式自动称重分拣机[J]. 仪表技术与传感器, 2011（11）: 31-33.
CHEN Y X, SU L, YANG L, et al. Auto weighting and sorting machine for optical glass blocks based on roller[J]. Instrument Technique and Sensor, 2011（11）: 31-33.
[5] 李光梅, 魏新华, 李法德, 等. 水果综合分选机称重模块的设计与实现[J]. 农业工程学报, 2009, 25（2）: 96-100.
LI G M, WEI X H, LI F D, et al. Design and implementation of weighing module for fruit integrative grader[J]. Transactions of the Chinese Society of Agricultural Engineering, 2009, 25（2）: 96-100.
[6] 孙凯, 闫学慧, 朱荣胜. 圆形水果自动分选和贴标签机的设计与应用[J]. 食品与机械, 2018, 34（8）: 79-84.
SUN K, YAN X H, ZHU R S. Design and application of round fruit sorting and labeling machine[J]. Food & Machinery, 2018, 34（8）: 79-84.
[7] 赵启明. 6GF-500型小杂果分级技术装备的开发[J]. 中国农机化学报, 2013, 34（1）: 142-145.
ZHAO Q M. 6GF-500 type of fruit grading technology and equipment development[J]. Journal of Chinese Agricultural Mechanization, 2013, 34（1）: 142-145.
[8] 王新亭. 电子称重式水果分选机微机测控系统的研究[D]. 北京: 中国农业大学, 2003: 16.
WANG X T. Research on the microcomputer control and measurement system of electronic weight sorter for fruit[D]. Beijing: China Agricultural University, 2003: 16.
[9] 王虎挺, 吴杰, 胡蓉, 等. 基于几何特性参数的库尔勒香梨质量预测的研究[J]. 石河子大学学报（自然科学版）, 2011, 29（3）: 370-373.
WANG H T, WU J, HU R, et al. Models for predicting the mass of korla fragrant pear by geometrical parameters[J]. Journal of Shihezi University （Natural Science）, 2011, 29（3）: 370-373.
[10] KHADIVI-KHUB A, NADERIBOLDAJI M. Predicting models for mass and volume of the sweet cherry （Prunus avium L.） fruits based on some physical traits[J]. Canadian Journal of Plant Science, 2013, 93（5）: 831-838.
[11] NADERI-BOLDAJI M, FATTAHI R, GHASEMI-VARNAMKHASTI M, et al. Models for predicting the mass of apricot fruits by geometrical attributes （cv. Shams, Nakhjavan, and Jahangiri）[J]. Scientia Horticulturae, 2008, 118（4）: 293-298.
[12] RASHIDI M, SEYFI K. Modeling of kiwifruit mass based on outer dimensions and projected areas[J]. Am Eur J Agric Environ Sci, 2008, 3: 26-29.
[13] RASHIDI M, SEYFI K, GHOLAMI M. Determination of kiwifruit volume using image processing[J]. J Agri Biol Sci, 2007, 2（6）: 17-22.
[14] TABATABAEEFAR A, RAJABIPOUR A. Modeling the mass of apples by geometrical attributes[J]. Scientia Horticulturae, 2005, 105（3）: 373-382.
[15] 刘忠超, 范灵燕, 盖晓华. 基于机器视觉的苹果重量检测研究[J]. 江苏农业科学, 2021, 49（21）: 201-205.
LIU Z C, FAN L Y, GAI X H. Study on apple weight detection based on machine vision[J]. Jiangsu Agricultural Sciences, 2021, 49（21）: 201-205.
[16] 陈炳舟. 基于多传感器信息融合的果实体尺参数测量方法[D]. 阿拉尔: 塔里木大学, 2022: 39.
CHEN B Z. Measurement method of fruit size based on multi-sensor information fusion[D]. Alar: Tarim University, 2022: 39.
[17] 陈炳舟, 孙万林, 陈立平. 基于超声波传感器阵列的空间感知方法[J]. 传感器与微系统, 2021, 40（12）: 40-43, 48.
CHEN B Z, SUN W L, CHEN L P. Spatial awareness method based on ultrasonic wave sensor array[J]. Transducer and Microsystem Technologies, 2021, 40（12）: 40-43, 48.
[18] 郑立华, 麦春艳, 廖崴, 等. 基于Kinect相机的苹果树三维点云配准[J]. 农业机械学报, 2016, 47（5）: 9-14.
ZHENG L H, MAI C Y, LIAO W, et al. 3D point cloud registration for apple tree based on kinect camera[J]. Transactions of the Chinese Society for Agricultural Machinery, 2016, 47（5）: 9-14.