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Non-Destructive Method for Estimating Seed Weights from Intact Peanut Pods Using Soft X-ray Imaging

文献类型： 外文期刊

作者： Qiu, Guangjun 1 ; Liu, Yuanyuan 2 ; Wang, Ning 2 ; Bennett, Rebecca S. 4 ; Weckler, Paul R. 2 ;

作者机构： 1.Guangdong Acad Agr Sci, Inst Facil Agr, Guangzhou 510640, Peoples R China

2.Oklahoma State Univ, Dept Biosyst & Agr Engn, Stillwater, OK 74078 USA

3.Jilin Agr Univ, Coll Informat Technol, Changchun 130118, Peoples R China

4.Agr Res Serv, US Dept Agr, Peanut & Small Grains Res Unit, Stillwater, OK 74075 USA

关键词： image processing; differential evolution; weight estimation; image segmentation; automation

期刊名称：AGRONOMY-BASEL （ 影响因子：3.7； 五年影响因子：4.0 ）

ISSN：

年卷期： 2023 年 13 卷 4 期

页码：

收录情况： SCI

摘要： In the U.S., peanut farmers receive premium prices for crops with high seed grades. One component of seed grade is the proportion of seed weight to that of pod hulls and other matter. Seed weight and size are also important traits for food processors. Current methods for evaluating peanut seed grade require the opening of the pod and are time-consuming and labor-intensive. In this study, a non-destructive and efficient method to determine peanut seed weights was investigated. X-ray images of a total of 513 peanut pods from three commercial cultivars, each representing three market types, were taken using a soft X-ray imaging system. The region of interest of each image, the seeds, was extracted two ways, manually and with a differential evolution segmentation algorithm. The comprehensive attenuation index (CAI) value was calculated from the segmented regions of interest. Lastly, linear regression models were established between peanut seed weights and the CAI. The results demonstrated that the X-ray imaging technology, coupled with the differential evolution segmentation algorithm, may be used to estimate seed weights efficiently from intact peanut pods.

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