一种葡萄果穗凸包体积的近似计算方法
An Approximate Method for Calculating the Volume of the Convex Hull of Grape Spikes
摘要: 果穗紧实度是评价葡萄外观、葡萄酒品质形成的一个重要指标,是反应果实颗粒之间松紧程度的一个抽象指标。由于葡萄颗粒之间缝隙变化,其凸包体积难以准确计算。本文从三个视角120˚来拍摄葡萄果穗,采用图像处理分割,获取果穗区域参数,以投影面积法、横切面累加法来分别近似计算果穗的凸包体积。结果表明,采用投影面积法得到的凸包体积偏差在1%~7%之间,而横切面累加法得到的凸包体积偏差分布较小,在0.76%~5.86%,且平均偏差仅为2.48%。因此,横切面积累加法可以为后续果穗紧实度的凸包体积计算提供了一种可行的参考方法。
Abstract: The compactness of grape clusters is an important indicator for evaluating grape appearance and the formation of wine quality, reflecting an abstract measure of the tightness between fruit particles. Due to variations in the gaps between grape particles, accurately calculating their convex hull volume is challenging. This study captures images of grape clusters from three 120˚ perspectives, employs image processing segmentation to obtain regional parameters of the clusters, and uses the projection area method and cross-sectional accumulation method to approximate the convex hull volume of the grape clusters. The results showed that the convex hull volume obtained using the projection area method had a deviation of 1% to 7%, while the deviation of the convex hull volume obtained using the cross-sectional accumulation method was smaller, ranging from 0.76% to 5.86%, with an average deviation of only 2.48%. Therefore, the cross-sectional accumulation method provides a viable reference approach for subsequent calculations of the convex hull volume related to the compactness of grape clusters.
文章引用:罗艳, 徐文轩, 左小玉, 郑博文, 许卓尔, 孙一叶, 黄睿岑, 杨伊婷. 一种葡萄果穗凸包体积的近似计算方法[J]. 仪器与设备, 2024, 12(4): 593-601. https://doi.org/10.12677/iae.2024.124078

参考文献

[1] 张燕, 朱济义. 中国葡萄酒行业现状、存在的问题及发展趋势[J]. 酿酒科技, 2009(11): 128-131.
[2] Moro, J.T. and Marcos, J.I. (2014) Evaluation of Indexes for the Quantitative and Objective Estimation of Grapevine Bunch Compactness. Journal of Grapevine Research, 53, 9-16.
[3] Hed, B., Ngugi, H.K. and Travis, J.W. (2009) Relationship between Cluster Compactness and Bunch Rot in Vignoles Grapes. Plant Disease, 93, 1195-1201. [Google Scholar] [CrossRef] [PubMed]
[4] Vail, M.E. (1991) Grape Cluster Architecture and the Susceptibility of Berries to Botrytis cinerea. Phytopathology, 81, 188-191. [Google Scholar] [CrossRef
[5] Molitor, D., Behr, M., Hoffmann, L. and Evers, D. (2016) Research Note: Benefits and Drawbacks of Pre-Bloom Applications of Gibberellic Acid (GA3) for Stem Elongation in Sauvignon Blanc. South African Journal of Enology and Viticulture, 33, 198-202. [Google Scholar] [CrossRef
[6] Tello, J. and Ibáñez, J. (2017) What Do We Know about Grapevine Bunch Compactness? A State-of-the-Art Review. Australian Journal of Grape and Wine Research, 24, 6-23. [Google Scholar] [CrossRef
[7] Tello, J., Aguirrezábal, R., Hernáiz, S., Larreina, B., Montemayor, M.I., Vaquero, E., et al. (2015) Multicultivar and Multivariate Study of the Natural Variation for Grapevine Bunch Compactness. Australian Journal of Grape and Wine Research, 21, 277-289. [Google Scholar] [CrossRef
[8] Cubero, S., Diago, M.P., Blasco, J., Tardaguila, J., Prats-Montalbán, J.M., Ibáñez, J., et al. (2015) A New Method for Assessment of Bunch Compactness Using Automated Image Analysis. Australian Journal of Grape and Wine Research, 21, 101-109. [Google Scholar] [CrossRef
[9] 陈英, 廖涛, 林初靠, 等. 基于计算机视觉的葡萄检测分级系统[J]. 农业机械学报, 2010, 41(3): 169-172.
[10] 陈英, 李伟, 张俊雄. 基于图像轮廓分析的堆叠葡萄果粒尺寸检测[J]. 农业机械学报, 2011, 42(8): 168-172.
[11] 罗陆锋, 邹湘军, 熊俊涛, 等. 自然环境下葡萄采摘机器人采摘点的自动定位[J]. 农业工程学报, 2015, 31(2): 14-21.
[12] 罗陆锋, 邹湘军, 卢清华, 等. 采摘机器人作业行为虚拟仿真与样机试验[J]. 农业机械学报, 2018, 49(5): 34-42.
[13] Yuan, L., Cai, J., Sun, L. and Ye, C. (2015) A Preliminary Discrimination of Cluster Disqualified Shape for Table Grape by Mono-Camera Multi-Perspective Simultaneously Imaging Approach. Food Analytical Methods, 9, 758-767. [Google Scholar] [CrossRef