Article
Computer Science, Information Systems
Lili Zhu, Petros Spachos
Summary: Food quality and safety are crucial for human health and social stability. This study proposed a mobile visual system to grade bananas, achieving high accuracy rates in the grading process. The complex process of ensuring food quality involves all stages from cultivation to consumption.
INTERNET OF THINGS
(2021)
Article
Food Science & Technology
Lili Zhu, Petros Spachos, Erica Pensini, Konstantinos N. Plataniotis
Summary: The quality and safety of food is essential for human health and social stability. Machine vision, along with image processing incorporating machine learning and deep learning models, plays a crucial role in improving food processing efficiency and addressing issues related to food grading and defect detection. This paper presents an overview of traditional and deep learning methods in machine vision applied to food processing, discussing current approaches, challenges, and future trends.
CURRENT RESEARCH IN FOOD SCIENCE
(2021)
Review
Food Science & Technology
Hanieh Amani, Katalin Badak-Kerti, Amin Mousavi Khaneghah
Summary: The smartphone has gained attention in food quality assessment due to its high-resolution cameras and programmability. It shows potential as a nondestructive technique for quality control, but challenges in implementation and industrialization remain.
CRITICAL REVIEWS IN FOOD SCIENCE AND NUTRITION
(2022)
Article
Agriculture, Multidisciplinary
Henry O. Velesaca, Patricia L. Suarez, Raul Mira, Angel D. Sappa
Summary: This manuscript provides a comprehensive survey of recent computer vision based food grain classification techniques, analyzing different processing stages and image types considered, as well as strategies for generating ground truth data. Conclusions on future needs and challenges are also presented.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2021)
Article
Environmental Sciences
William Yamada, Wei Zhao, Matthew Digman
Summary: An automatic method using monovision un-crewed aerial vehicle imagery was developed to obtain geographic coordinates of bales, with YOLOv3 algorithm identified as the best option in terms of accuracy and speed. Lowering image quality resulted in decreased performance.
Article
Computer Science, Artificial Intelligence
Lucas D. C. de Castro, Leonardo Scabini, Lucas C. Ribas, Odemir M. Bruno, Osvaldo N. Oliveira Jr
Summary: This study proposes a computer vision system based on mechanochromic sensors for real-time strain prediction. By applying image processing and machine learning algorithms, the relationship between strain and reflected color can be learned and used for monitoring real-time strain variations. The ElasticNet regression model shows the highest accuracy and can also estimate the applied tensile force on the sensors.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Engineering, Multidisciplinary
Mengchao Zhang, Dongyue Zhang, Chao Yuan, Meixuan Li, Luxuan Liu, Mingyuan Xue, Nini Hao, Yuan Zhang
Summary: The paper proposes a point-by-point interpolation method named PPIM for connecting breakpoints and broken lines on conveyor belts. The method improves the step of traversing the entire image when searching for breakpoints and lines, reducing the search area and improving real-time detection.
Article
Agriculture, Multidisciplinary
Rongqiang Zhao, Jun Fu, Zhi Chen, Lei Tian, Luquan Ren
Summary: A low-rank-constraint-based sieve clogging recognition (LSCR) algorithm is proposed in this study to accurately estimate the position and shape of meshes and determine the clogging areas based on relative reflectance difference. Experimental results demonstrate that the algorithm achieves significantly higher recognition accuracy at the pixel level compared to existing algorithms.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
Article
Computer Science, Information Systems
Xiao Lin, Lizhuang Ma, Bin Sheng, Zhi-Jie Wang, Wansheng Chen
Summary: This paper presents a novel solution to the challenging problem of rain removal from a single image, merging the merits of two-phase processing methods and the Fuzzy Broad Learning System. The experimental results demonstrate that the proposed solution outperforms several state-of-the-art algorithms in terms of effectiveness and efficiency.
IEEE TRANSACTIONS ON MULTIMEDIA
(2021)
Review
Agriculture, Multidisciplinary
Harsh Pathak, C. Igathinathane, Z. Zhang, D. Archer, J. Hendrickson
Summary: The use of unmanned aerial vehicles (UAV) and computer vision algorithms in evaluating plant stand count has been reviewed in this study. It is concluded that image acquisition at an appropriate stage and height, along with suitable color space and camera imagery, can improve the accuracy of plant stand count. Other findings include the effectiveness of deep learning models and the application of direct image processing and open-source platforms. This review provides valuable guidance for farmers, producers, and researchers in selecting and employing UAV-based algorithms for plant stand count evaluation.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
Article
Horticulture
Shekh Mukhtar Mansuri, Prem Veer Gautam, Dilip Jain, C. Nickhil, Pramendra
Summary: This study used image processing techniques to measure the physical properties of Thai apple ber at different stages of ripening. The developed models, including linear support vector machine and multilinear regression, were found to be suitable for predicting the mass and volume. The mass prediction model based on calculated volume showed a linear relationship.
SCIENTIA HORTICULTURAE
(2022)
Article
Computer Science, Information Systems
Chengxian Yao, Haifeng Zhang, Jia Zhu, Diqing Fan, Yu Fang, Lin Tang
Summary: This paper proposes an ORB feature matching algorithm based on multi-scale feature description fusion and feature point mapping error correction to improve the accuracy of feature extraction and description of various scales in traditional ORB feature matching algorithm. Experimental results show that the improved algorithm has excellent robustness when resisting interference, and the matching accuracy is improved by 19.2%.
Article
Chemistry, Multidisciplinary
Ning Zhang, Enxu Zhang, Fei Li
Summary: The effectiveness of a data-balancing method based on convolutional neural network is investigated in this study. Two balancing methods, over-sampling and loss function with assignable class weights, are used to expand the data set. Experimental results show that the new loss function can effectively improve classification accuracy and learning ability, while the use of data-augmentation method greatly reduces accuracy. Furthermore, it is verified that a neural network using a small convolution layer can improve classification accuracy by 1.52% using the data-augmentation data-balancing method.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Information Systems
Katiuscia Mannaro, Matteo Baire, Alessandro Fanti, Matteo Bruno Lodi, Luca Didaci, Alessandro Fedeli, Luisanna Cocco, Andrea Randazzo, Giuseppe Mazzarella, Giorgio Fumera
Summary: This paper addresses the problem of automatic image segmentation methods applied to the production process of traditional Sardinian flatbread. A machine learning algorithm based on support vector machines is proposed for the segmentation and measurement estimation of bread images. Experimental results demonstrate the accuracy and efficiency of the method in accurately segmenting bread sheet images and extracting representative dimensions.
Article
Computer Science, Software Engineering
Zhicheng Lu, Xiaoming Chen, Vera Yuk Ying Chung, Weidong Cai, Yiran Shen
Summary: This article proposes an event synthesis framework EV-LFV which utilizes one event camera and multiple traditional RGB cameras to generate full multi-subview event-based RGB-LFV. EV-LFV models various features of RGB-LFV through spatial-angular convolution, ConvLSTM, and Transformer for effective synthesis of event streams. Experimental results show that EV-LFV outperforms other methods and effectively alleviates motion blur in reconstructed RGB-LFV.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
(2023)
Article
Agricultural Engineering
Jiacheng Shen, C. Igathinathane, Manlu Yu, Anand Kumar Pothula
BIORESOURCE TECHNOLOGY
(2015)
Article
Agricultural Engineering
Anand Kumar Pothula, C. Igathinathane, S. Kronberg
INDUSTRIAL CROPS AND PRODUCTS
(2015)
Article
Agricultural Engineering
C. Igathinathane, J. S. Tumuluru, D. Keshwani, M. Schmer, D. Archer, M. Liebig, J. Halvorson, J. Hendrickson, S. Kronberg
BIOMASS & BIOENERGY
(2016)
Article
Agriculture, Multidisciplinary
S. Sunoj, C. Igathinathane, R. Visvanathan
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2016)
Article
Chemistry, Applied
Ugur Ulusoy, C. Igathinathane
FUEL PROCESSING TECHNOLOGY
(2016)
Article
Engineering, Chemical
C. Igathinathane, Ugur Ulusoy
Article
Agriculture, Multidisciplinary
S. Sunoj, S. N. Subhashree, S. Dharani, C. Igathinathane, J. G. Franco, R. E. Mallinger, J. R. Prasifka, D. Archer
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2018)
Article
Agronomy
S. Sunoj, C. Igathinathane, S. Jenicka
POSTHARVEST BIOLOGY AND TECHNOLOGY
(2018)
Article
Geography, Physical
S. Sunoj, C. Igathinathane, N. Saliendra, J. Hendrickson, D. Archer
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2018)
Article
Agricultural Engineering
Srinivasagan N. Subhashree, C. Igathinathane, M. Liebig, J. Halvorson, D. Archer, J. Hendrickson, S. Kronberg
Summary: The study found that the use of automatic bale picker (ABP) can significantly reduce fuel consumption by 72% and 53% compared to tractors when aggregating bales in field areas ranging from 8 to 259 hectares. The most influential variables affecting logistics distance were field area, biomass yield, and bales per trip (BPT), while operation time and fuel quantity were mainly affected by field area, biomass yield, BPT, and equipment speed. Prediction models based on these variables showed a high level of accuracy with R-2 values greater than or equal to 0.98.
BIOMASS & BIOENERGY
(2021)
Article
Environmental Sciences
Oveis Hassanijalilian, C. Igathinathane, Sreekala Bajwa, John Nowatzki
Article
Agriculture, Multidisciplinary
Srinivasagan N. Subhashree, C. Igathinathane, J. Hendrickson, D. Archer, M. Liebig, J. Halvorson, S. Kronberg, D. Toledo, K. Sedivec, D. Peck
Summary: Economic analysis helps in decision-making related to forage production and handling by providing information on growing or buying forage, setting prices, and purchasing equipment. The web-based tool FECWT simplifies the complex and time-consuming process of economic calculations, generating results based on user inputs or default data. The tool calculates net return, break-even ratio, payback period, and return on investment, and has been shown effective through case studies using real-field data.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2023)
Review
Agronomy
Srinivasagan N. N. Subhashree, C. Igathinathane, Adnan Akyuz, Md. Borhan, John Hendrickson, David Archer, Mark Liebig, David Toledo, Kevin Sedivec, Scott Kronberg, Jonathan Halvorson
Summary: Farmers and ranchers rely on annual forage production for grassland livestock enterprises. Regression and machine learning models have been developed to understand the seasonal variability in grass and forage production. Decision support tools help farmers compare management practices and develop forecast scenarios. A systematic literature review was performed to synthesize current knowledge, identify research gaps, and inform stakeholders. High-resolution satellites, advanced ML models, and interactive, user-friendly tools should be further studied and applied in this field.
Article
Agricultural Engineering
Srinivasagan N. Subhashree, C. Igathinathane, Ganesh C. Bora, David Ripplinger, Leslie Backer
BIOMASS & BIOENERGY
(2017)
Article
Agricultural Engineering
S. Sunoj, S. Sivarajan, M. Maharlooei, S. G. Bajwa, J. P. Harmon, J. Nowatzki, C. Igathinathane
TRANSACTIONS OF THE ASABE
(2017)
Article
Food Science & Technology
Yonghong Ye, Songyan Zheng, Yuanxing Wang
Summary: In this study, the changes of aroma components in Gannan navel orange during growth were systematically studied using HS-SPME-GC-MS. Key aroma components and markers were identified. These findings contribute to a better understanding of the dynamic variation of aroma compounds during navel orange growth and have potential for industrial applications.
FOOD RESEARCH INTERNATIONAL
(2024)
Article
Food Science & Technology
Jia Xu, Yayuan Zhang, Mengke Zhang, Xinlin Wei, Yiming Zhou
Summary: This study evaluated the effects of glucosamine selenium on summer-autumn tea, showing that it can enhance nutritional quality, improve sensory characteristics, and increase plant adaptation to environmental changes and abiotic stresses.
FOOD RESEARCH INTERNATIONAL
(2024)
Article
Food Science & Technology
Yuanming Chu, Zhaoyang Ding, Jing Xie
Summary: This study investigated the use of ice glazing containing D-sodium erythorbate (DSE) and vacuum packaging to maintain the quality of large yellow croaker during frozen storage. The results showed that vacuum packaging effectively inhibited ice crystal growth and minimized water loss, while the combination of vacuum packaging and 0.3% DSE-infused ice glazing maintained freshness indicators at low levels throughout the 300-day storage period. This combination was considered the most effective in preserving the quality of the fish.
FOOD RESEARCH INTERNATIONAL
(2024)
Review
Food Science & Technology
Md. Ashikur Rahman, Shirin Akter, Md. Ashrafudoulla, Md. Anamul Hasan Chowdhury, A. G. M. Sofi Uddin Mahamud, Si Hong Park, Sang-Do Ha
Summary: This comprehensive review aims to provide insights into the mechanisms and key factors influencing biofilm formation by A. hydrophila in the food industry. It explores the molecular processes involved in various stages of biofilm formation and investigates the impact of intrinsic factors and environmental conditions on biofilm architecture and resilience. The article also highlights the potential of bibliometric analysis in conceptualizing the research landscape and identifying knowledge gaps in A. hydrophila biofilm research.
FOOD RESEARCH INTERNATIONAL
(2024)
Article
Food Science & Technology
Chujing Wang, Wenni Tian, Zengliu Song, Qun Wang, Yong Cao, Jie Xiao
Summary: Solid lipid ratio in emulsions has significant effects on colloidal stability, mucus permeability, and bioavailability in vivo. Higher solid lipid ratio improves intestinal stability but reduces mucus permeability.
FOOD RESEARCH INTERNATIONAL
(2024)
Article
Food Science & Technology
Dacai Zhong, Liping Kang, Juan Liu, Xiang Li, Li Zhou, Luqi Huang, Zidong Qiu
Summary: In this study, a novel online extraction electrospray ionization mass spectrometry method was developed to comprehensively characterize complex foods. Meanwhile, a characteristic marker screening method and chemometrics modeling were used for the accurate authentication of highly-similar foods. This research has significant implications for ensuring food quality and safety.
FOOD RESEARCH INTERNATIONAL
(2024)
Article
Food Science & Technology
Qiannan Zhao, Jinyi Yang, Jiahui Li, Lei Zhang, Xiaohai Yan, Tianli Yue, Yahong Yuan
Summary: This study investigated the transport and hypoglycemic effects of phenolics in mulberry leaves using an in vitro digestion model. The results showed that digested phenolics had higher absorbability and could inhibit glucose digestion and absorption. Phenolics also regulated glucose metabolism. Luteoforol and p-coumaric acid were found to be the primary phenolics strongly correlated with the hypoglycemic ability of mulberry leaves.
FOOD RESEARCH INTERNATIONAL
(2024)
Article
Food Science & Technology
Yanyun Cao, Qingling Wang, Jinou Lin, Yin-Yi Ding, Jianzhong Han
Summary: This study investigated the effects of gallic acid (GA) and epigallocatechin gallate (EGCG) at different ratios on the gel properties of calcium induced-whey protein emulsion gel. It was found that GA and EGCG could promote gel formation, increase gel strength, and delay the release of emulsified oil droplets.
FOOD RESEARCH INTERNATIONAL
(2024)
Article
Food Science & Technology
Monique Martins Strieder, Vitor Lacerda Sanches, Mauricio Ariel Rostagno
Summary: This study proposed an integrated and automated procedure for extracting, separating, and quantifying bioactive compounds from coffee co-products. By optimizing the extraction, separation, and analysis method, real-time analysis was achieved. The results suggest that coupling different techniques can efficiently extract, separate, and analyze phenolic compounds, providing an integrated method to produce high-added value ingredients for various applications.
FOOD RESEARCH INTERNATIONAL
(2024)
Article
Food Science & Technology
Kyu Sang Sim, Hyoyoung Kim, Suel Hye Hur, Tae Woong Na, Ji Hye Lee, Ho Jin Kim
Summary: Geographical origin plays a crucial role in determining the quality and safety of agricultural products. In this study, ICP analysis was used to determine the inorganic elemental content of onions and identify their geographical origin. Chemometric methods were applied to analyze the ICP results, and the accuracy of distinguishing between Korean and Chinese onions was found to be excellent. The findings suggest that this method can be beneficial for identifying agricultural products.
FOOD RESEARCH INTERNATIONAL
(2024)
