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

被引:0
|
作者
Qiu, Guangjun [1 ,2 ]
Liu, Yuanyuan [2 ,3 ]
Wang, Ning [2 ]
Bennett, Rebecca S. [4 ]
Weckler, Paul R. [2 ]
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
来源
AGRONOMY-BASEL | 2023年 / 13卷 / 04期
基金
中国国家自然科学基金;
关键词
image processing; differential evolution; weight estimation; image segmentation; automation; DAMAGE;
D O I
10.3390/agronomy13041127
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
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.
引用
收藏
页数:12
相关论文
共 50 条
  • [1] Non-destructive evaluation of the edible rate for pomelo using X-ray imaging method
    Zhang, Yuchen
    Lin, Yangyang
    Tian, Hao
    Tian, Shijie
    Xu, Huirong
    FOOD CONTROL, 2023, 144
  • [2] Bonding wire characterization using non-destructive X-ray imaging
    Muss, D.
    Koch, R.
    MICROELECTRONICS RELIABILITY, 2023, 148
  • [3] Non-destructive Imaging of Buds Using X-ray Phase Contrast
    Kovaleski, Alisson Pacheco
    Londo, Jason
    Finkelstein, Kenneth D.
    HORTSCIENCE, 2017, 52 (09) : S235 - S236
  • [4] A Non-Destructive Method for Obtaining a Local Coat Weight Map Using X-Ray Imaging
    Azimi, Y.
    Kortschot, M. T.
    Farnood, R.
    JOURNAL OF PULP AND PAPER SCIENCE, 2009, 35 (01): : 11 - 16
  • [5] A non-destructive method for obtaining a local coat weight map using X-ray imaging
    Dept, Appl, Chem, Chem. Engin, Univ. Toronto, Toronto, ON M5S 3E5, Canada
    J Pulp Pap Sci, 2009, 1 (11-16):
  • [6] X-ray Imaging for Non-Destructive Microstructure Analysis at SSRF
    Chen, Rongchang
    Liu, Ping
    Xiao, Tiqiao
    Xu, Lisa X.
    ADVANCED MATERIALS, 2014, 26 (46) : 7688 - 7691
  • [7] X-ray imaging and digital processing application in non-destructive assessing of melon seed quality
    de Medeiros, Andre Dantas
    Martins, Maycon Silva
    da Silva, Laercio Junio
    Pereira, Marcio Dias
    Zavala Leon, Manuel Jesus
    dos Santos Dias, Denise Cunha Fernandes
    JOURNAL OF SEED SCIENCE, 2020, 42
  • [8] Non-destructive method to resolve the core and the coating on paperboard by spectroscopic x-ray imaging
    Reza, Salim
    Norlin, Borje
    Thim, Jan
    Frojdh, Christer
    NORDIC PULP & PAPER RESEARCH JOURNAL, 2013, 28 (03) : 439 - 442
  • [9] Non-destructive study of fruits using grating-based X-ray imaging
    Sheng-Xiang Wang
    Ren-Fang Hu
    Kun Gao
    Faiz Wali
    Gui-Bin Zan
    Da-Jiang Wang
    Zhi-Yun Pan
    Shi-Qiang Wei
    Nuclear Science and Techniques, 2017, 28 (02) : 57 - 60
  • [10] Non-destructive study of fruits using grating-based X-ray imaging
    Wang, Sheng-Xiang
    Hu, Ren-Fang
    Gao, Kun
    Wali, Faiz
    Zan, Gui-Bin
    Wang, Da-Jiang
    Pan, Zhi-Yun
    Wei, Shi-Qiang
    NUCLEAR SCIENCE AND TECHNIQUES, 2017, 28 (02)