Field asymmetric ion mobility spectrometry for pre-symptomatic rot detection in stored Ranger Russet and Russet Burbank potatoes

Kothawade, Gajanan S.; Chandel, Abhilash K.; Khot, Lav R.; Sankaran, Sindhuja; Bates, Austin A.; Schroeder, Brenda K.

doi:10.1016/j.postharvbio.2021.111679

Cited by 4 publications

(2 citation statements)

References 34 publications

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“…Particularly in post-harvest storage, where rot diseases can cause significant loss of potato tubers. For example, FAIMS system demonstrated the ability to detect soft rot at early stages in potatoes [16] , [17] , [18] , [19] , [20] . In onion, FAIMS system also demonstrated its applicability for onion sour skin detection under storage conditions [18] , [21] .…”

Section: Hardware In Contextmentioning

confidence: 99%

Development of a semi-automated volatile organic compounds (VOCs) sampling system for field asymmetric ion mobility spectrometry (FAIMS) analysis

Valencia-Ortiz

Sankaran

2022

HardwareX

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Section: Hardware In Contextmentioning

confidence: 99%

Development of a semi-automated volatile organic compounds (VOCs) sampling system for field asymmetric ion mobility spectrometry (FAIMS) analysis

Valencia-Ortiz

Sankaran

2022

HardwareX

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“…If not detected and promptly removed, this disease can severely affect the quality and sale of the entire potato batch. Therefore, detecting potato defects can not only help meet the different needs of end-consumers and maximize resource utilization but also allow potato producers and sellers to analyze the types of defects and adopt targeted strategies to improve production management ( Kothawade et al., 2021 ). Therefore, finding a method of early blackheart disease detection in potatoes is crucial.…”

Section: Introductionmentioning

confidence: 99%

Online inspection of blackheart in potatoes using visible-near infrared spectroscopy and interpretable spectrogram-based modified ResNet modeling

Guo,

Zhang,

et al. 2024

Front. Plant Sci.

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IntroductionBlackheart is one of the most common physiological diseases in potatoes during storage. In the initial stage, black spots only occur in tissues near the potato core and cannot be detected from an outward appearance. If not identified and removed in time, the disease will seriously undermine the quality and sale of theentire batch of potatoes. There is an urgent need to develop a method for early detection of blackheart in potatoes.MethodsThis paper used visible-near infrared (Vis/NIR) spectroscopy to conduct online discriminant analysis on potatoes with varying degrees of blackheart and healthy potatoes to achieve real-time detection. An efficient and lightweight detection model was developed for detecting different degrees of blackheart in potatoes by introducing the depthwise convolution, pointwise convolution, and efficient channel attention modules into the ResNet model. Two discriminative models, the support vector machine (SVM) and the ResNet model were compared with the modified ResNet model. Results and discussionThe prediction accuracy for blackheart and healthy potatoes test sets reached 0.971 using the original spectrum combined with a modified ResNet model. Moreover, the modified ResNet model significantly reduced the number of parameters to 1434052, achieving a substantial 62.71% reduction in model complexity. Meanwhile, its performance was evidenced by a 4.18% improvement in accuracy. The Grad-CAM++ visualizations provided a qualitative assessment of the model’s focus across different severity grades of blackheart condition, highlighting the importance of different wavelengths in the analysis. In these visualizations, the most significant features were predominantly found in the 650–750 nm range, with a notable peak near 700 nm. This peak was speculated to be associated with the vibrational activities of the C-H bond, specifically the fourth overtone of the C-H functional group, within the molecular structure of the potato components. This research demonstrated that the modified ResNet model combined with Vis/NIR could assist in the detection of different degrees of black in potatoes.

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Automatic detection of multi-type defects on potatoes using multispectral imaging combined with a deep learning model

Yang

Liu

Huang

et al. 2023

Journal of Food Engineering

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Field asymmetric ion mobility spectrometry for pre-symptomatic rot detection in stored Ranger Russet and Russet Burbank potatoes

Cited by 4 publications

References 34 publications

Development of a semi-automated volatile organic compounds (VOCs) sampling system for field asymmetric ion mobility spectrometry (FAIMS) analysis

Development of a semi-automated volatile organic compounds (VOCs) sampling system for field asymmetric ion mobility spectrometry (FAIMS) analysis

Online inspection of blackheart in potatoes using visible-near infrared spectroscopy and interpretable spectrogram-based modified ResNet modeling

Automatic detection of multi-type defects on potatoes using multispectral imaging combined with a deep learning model

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