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Chen H, Chang Y, Chen Y, Liu C, Zhu Z, Liu S, Wang Q. Nondestructive testing of runny salted egg yolk based on improved ConvNeXt-T. J Food Sci 2024; 89:3369-3383. [PMID: 38720576 DOI: 10.1111/1750-3841.17010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 12/26/2023] [Accepted: 02/13/2024] [Indexed: 06/14/2024]
Abstract
Salted egg yolks from salted duck eggs are widely utilized in the domestic and international food industry as both raw materials and ingredients. When salted egg yolks are not fully cured and matured, they exist in a fluid state, with a mixture of solid and liquid internally. Due to this composition, they are susceptible to deterioration during storage and usage, necessitating their detection and classification. In this study, a dataset specifically for salted egg yolks was established, and the ConvNeXt-T model, employed as the benchmark model, underwent two notable improvements. First, a lightweight location-aware circular convolution (ParC) was introduced, utilizing a ParC-block to replace a portion of the original ConvNeXt-T block. This enhancement aimed to overcome the limitations of convolution in extracting global feature information while integrating the global sensing capability of vision transformer and the localization capability of convolution. Additionally, the activation function was modified through substitution. These improvements resulted in the final model. Experimental results indicate that the enhanced model exhibits faster convergence on the custom salted egg yolk dataset compared to the baseline model. Furthermore, a significant reduction of model parameters by a factor of 4 led to a 2.167 percentage point improvement in the accuracy of the test set. The ParC-ConvNeXt-SMU-T model achieved an accuracy of 96.833% with 26.8 million parameters. Notably, the improved model demonstrates exceptional effectiveness in recognizing salted egg yolks. PRACTICAL APPLICATION: This study can be widely applied in the process of salted egg yolk production and quality inspection, which can improve the actual sorting efficiency of salted egg yolks and reduce the labor cost at the same time. It can also be used for nondestructive testing of salted egg yolks by governmental enterprises and other regulatory authorities.
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Affiliation(s)
- Haoran Chen
- College of Engineering, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Yulong Chang
- College of Engineering, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Yuanzhe Chen
- College of Engineering, Huazhong Agricultural University, Wuhan, Hubei, China
| | - ChenKang Liu
- College of Engineering, Huazhong Agricultural University, Wuhan, Hubei, China
| | - ZhiHui Zhu
- College of Engineering, Huazhong Agricultural University, Wuhan, Hubei, China
| | - ShiWei Liu
- College of Engineering, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Qiaohua Wang
- College of Engineering, Huazhong Agricultural University, Wuhan, Hubei, China
- Key Laboratory of Agricultural Equipment in Mid-Lowe Yangtze River, Ministry of Agriculture, Wuhan, Hubei, China
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Liu X, Li N, Huang Y, Lin X, Ren Z. A comprehensive review on acquisition of phenotypic information of Prunoideae fruits: Image technology. FRONTIERS IN PLANT SCIENCE 2023; 13:1084847. [PMID: 36777535 PMCID: PMC9909479 DOI: 10.3389/fpls.2022.1084847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 12/21/2022] [Indexed: 06/18/2023]
Abstract
Fruit phenotypic information reflects all the physical, physiological, biochemical characteristics and traits of fruit. Accurate access to phenotypic information is very necessary and meaningful for post-harvest storage, sales and deep processing. The methods of obtaining phenotypic information include traditional manual measurement and damage detection, which are inefficient and destructive. In the field of fruit phenotype research, image technology is increasingly mature, which greatly improves the efficiency of fruit phenotype information acquisition. This review paper mainly reviews the research on phenotypic information of Prunoideae fruit based on three imaging techniques (RGB imaging, hyperspectral imaging, multispectral imaging). Firstly, the classification was carried out according to the image type. On this basis, the review and summary of previous studies were completed from the perspectives of fruit maturity detection, fruit quality classification and fruit disease damage identification. Analysis of the advantages and disadvantages of various types of images in the study, and try to give the next research direction for improvement.
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Affiliation(s)
- Xuan Liu
- College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding, China
| | - Na Li
- College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding, China
| | - Yirui Huang
- College of Information Engineering, Hebei GEO University, Shijiazhuang, China
| | - Xiujun Lin
- College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding, China
| | - Zhenhui Ren
- College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding, China
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Lazim SSR, Mat Nawi N, Bejo SK, Mohamed Shariff AR, Abdullah N. Prediction and classification of soluble solid contents to determine the maturity level of watermelon using visible and shortwave near infrared spectroscopy. INTERNATIONAL FOOD RESEARCH JOURNAL 2022. [DOI: 10.47836/ifrj.29.6.13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The present work investigated the potential application of a portable and low-cost spectroscopic technique to predict the soluble solid content (SSC) for determining the maturity level of watermelons. A total of 63 watermelon samples were used in the present work, representing three different maturity levels: unmatured, matured, and over-matured. Before spectral acquisition, each watermelon sample was cut into half, producing 126 fruit portions. Visible shortwave near infrared (VSNIR) spectrometer was used to record the spectral data from the skin surface of each portion. The SSC of each portion was measured using a digital refractometer. Partial least square (PLS) regression method was used to establish both calibration and prediction models to predict the SSC values from the watermelon samples. Support vector machine (SVM) classifier was used to categorise spectral data into the respective maturity levels. Results showed that the coefficient of determination (R2) values for calibration models of unmatured, matured, and over-matured were 0.65, 0.81, and 0.78, respectively. For the prediction model, the R2 values for unmatured, matured, and over-matured were 0.60, 0.74, and 0.76, respectively. The SVM yielded good classification accuracy of 85%. The present work demonstrated that the proposed spectroscopic method could be applied to predict and classify the maturity level of watermelons based on their skin condition.
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Abstract
The influence of simulated transport vibration and storage conditions for 10 days on tomato fruits quality (color, weight, firmness, total soluble solids, and headspace gases) were investigated. Better kinetic models for color changes, weight loss, and firmness of stored tomato fruits were selected. Tomato fruits were divided equally into two main groups where the first one was subjected to vibration at a frequency of 2.5 Hz for two hours and the other group was set as a control (with no vibration stress). Both tomato groups were stored for 10 days at 10 °C and 22 °C storage conditions. The results showed a reduction in total soluble solids, yellowness, weight, lightness in the tomato fruits subjected to vibration at 22 °C storage condition. Ethylene and carbon dioxide increased by 124.13% and 83.85% respectively on the same condition (22 °C). However, storage at 10 °C slowed down the investigated quality changes attributes of both tomato groups (vibrated and control) during storage. The weight loss change kinetics of both tomato groups at both storage temperatures were highly fitted with a zero-order kinetic model. Color and firmness kinetic changes of tomato groups stored at both conditions were described well by zero and first order kinetic models. To validate the appropriateness of the selected model, lightness, redness, yellowness, and firmness were taken as an example. The study revealed that the vibration occurrence and increasing storage temperature cause various changes in the quality attributes of tomatoes.
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Hongyang T, Daming H, Xingyi H, Aheto JH, Yi R, Yu W, Ji L, Shuai N, Mengqi X. Detection of browning of fresh‐cut potato chips based on machine vision and electronic nose. J FOOD PROCESS ENG 2021. [DOI: 10.1111/jfpe.13631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
- Tu Hongyang
- School of Food and Biological Engineering Jiangsu University Zhenjiang Jiangsu China
| | - Huang Daming
- School of Food and Biological Engineering Jiangsu University Zhenjiang Jiangsu China
| | - Huang Xingyi
- School of Food and Biological Engineering Jiangsu University Zhenjiang Jiangsu China
| | | | - Ren Yi
- School of Food and Biological Engineering Jiangsu University Zhenjiang Jiangsu China
- Suzhou Polytechnic Institute of Agriculture School of Smart Agriculture Suzhou China
| | - Wang Yu
- School of Food and Biological Engineering Jiangsu University Zhenjiang Jiangsu China
| | - Liu Ji
- School of Food and Biological Engineering Jiangsu University Zhenjiang Jiangsu China
| | - Niu Shuai
- School of Food and Biological Engineering Jiangsu University Zhenjiang Jiangsu China
| | - Xu Mengqi
- School of Food and Biological Engineering Jiangsu University Zhenjiang Jiangsu China
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Sanchez PDC, Hashim N, Shamsudin R, Mohd Nor MZ. Applications of imaging and spectroscopy techniques for non-destructive quality evaluation of potatoes and sweet potatoes: A review. Trends Food Sci Technol 2020. [DOI: 10.1016/j.tifs.2019.12.027] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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Li J, Fan S, Huang W. Assessment of multiregion local models for detection of SSC of whole peach (
Amygdalus persica
L.) by combining both hyperspectral imaging and wavelength optimization methods. J FOOD PROCESS ENG 2018. [DOI: 10.1111/jfpe.12914] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
Affiliation(s)
- Jiangbo Li
- Beijing Research Center of Intelligent Equipment for Agriculture Beijing China
- College of Mechanical and Electrical EngineeringShihezi University Shihezi China
| | - Shuxiang Fan
- Beijing Research Center of Intelligent Equipment for Agriculture Beijing China
| | - Wenqian Huang
- Beijing Research Center of Intelligent Equipment for Agriculture Beijing China
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Comparison and Optimization of Models for Determination of Sugar Content in Pear by Portable Vis-NIR Spectroscopy Coupled with Wavelength Selection Algorithm. FOOD ANAL METHOD 2018. [DOI: 10.1007/s12161-018-1326-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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Flores D, Colnago L, Ferreira M, Spoto M. Prediction of Orange juice sensorial attributes from intact fruits by TD-NMR. Microchem J 2016. [DOI: 10.1016/j.microc.2016.04.009] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Application of Long-Wave Near Infrared Hyperspectral Imaging for Measurement of Soluble Solid Content (SSC) in Pear. FOOD ANAL METHOD 2016. [DOI: 10.1007/s12161-016-0498-2] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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Abstract
The main food quality traits of interest using non-invasive sensing techniques are sensory characteristics, chemical composition, physicochemical properties, health-protecting properties, nutritional characteristics and safety. A wide range of non-invasive sensing techniques, from optical, acoustical, electrical, to nuclear magnetic, X-ray, biosensor, microwave and terahertz, are organized according to physical principle.
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Affiliation(s)
- Zou Xiaobo
- Agricultural Product Processing and Storage Lab
- School of Food and Biological Engineering
- Key Laboratory of Modern Agriculture Equipment and Technology
- Jiangsu University
- Zhenjiang
| | - Huang Xiaowei
- Agricultural Product Processing and Storage Lab
- School of Food and Biological Engineering
- Key Laboratory of Modern Agriculture Equipment and Technology
- Jiangsu University
- Zhenjiang
| | - Malcolm Povey
- School of Food Science and Nutrition
- the University of Leeds
- Leeds LS2 9JT
- UK
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12
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Mahajan S, Das A, Sardana HK. Image acquisition techniques for assessment of legume quality. Trends Food Sci Technol 2015. [DOI: 10.1016/j.tifs.2015.01.001] [Citation(s) in RCA: 48] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
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