Article
Food Science & Technology
Lilija Duckena, Reinis Alksnis, Ieva Erdberga, Ina Alsina, Laila Dubova, Mara Duma
Summary: In this study, visible and near-infrared (Vis-NIR) spectroscopy was used to analyze the internal quality attributes of tomatoes. The results showed that Vis-NIR spectroscopy can accurately predict the taste index, lycopene, flavonoids, beta-carotene, total phenols, and dry matter content of tomatoes.
Article
Spectroscopy
Dongyan Zhang, Yi Yang, Gao Chen, Xi Tian, Zheli Wang, Shuxiang Fan, Zhenghua Xin
Summary: The study applied Vis/NIR spectroscopy to evaluate the soluble solids content (SSC) of tomatoes and developed a method for predicting SSC effectively. By measuring tomato samples at different maturity stages and using spectral data from different wavelength ranges, the study established the best prediction model through preprocessing and model building steps.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2021)
Article
Green & Sustainable Science & Technology
Khadija Najjar, Nawaf Abu-Khalaf
Summary: The study demonstrated the potential of VIS/NIR spectroscopy in distinguishing between different varieties of tomatoes and predicting their quality parameters. It showed high correlation coefficients and performance deviation ratios for most quality parameters, indicating the effectiveness of the spectroscopy technique.
Article
Environmental Sciences
S. Hamed Javadi, Abdul M. Mouazen
Summary: Visible-near-infrared (vis-NIR) and X-ray fluorescence (XRF) technologies are commonly used in proximal soil sensing (PSS) and their fusion shows potential to improve accuracy. This study evaluated different data fusion methods for predicting soil attributes, finding that least squares (LS) was a robust method for improving prediction accuracy.
Article
Automation & Control Systems
Zhonghao Xie, Xi'an Feng, Xiaojing Chen
Summary: This paper proposes a robust method for PLS based on the idea of least trimmed squares (LTS), which effectively deals with high-dimensional regressors. By formulating the LTS problem as a concave maximization problem, the complexity of solving LTS is simplified. The results from simulation and real data sets demonstrate the effectiveness and robustness of the proposed approach.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
(2022)
Article
Automation & Control Systems
Matteo Stocchero, Martino De Nardi, Bruno Scarpa
Summary: PLS regression is a technique for multivariate responses in the presence of multicollinearity, and efforts have been made to extend it to classification problems. A new technique called PLS for classification has been introduced to address the general G-class problem, estimating conditional probabilities and using score vectors for model interpretation.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
(2021)
Article
Multidisciplinary Sciences
M. Mamouei, K. Budidha, N. Baishya, M. Qassem, P. A. Kyriacou
Summary: The use of linear models in spectroscopy applications is valid, however, nonlinear effects may exist in high concentrations and scattering media, justifying the use of complex nonlinear models.
SCIENTIFIC REPORTS
(2021)
Article
Multidisciplinary Sciences
Emilio Gomez-Gonzalez, Alejandro Barriga-Rivera, Beatriz Fernandez-Munoz, Jose Manuel Navas-Garcia, Isabel Fernandez-Lizaranzu, Francisco Javier Munoz-Gonzalez, Ruben Parrilla-Giraldez, Desiree Requena-Lancharro, Pedro Gil-Gamboa, Cristina Rosell-Valle, Carmen Gomez-Gonzalez, Maria Jose Mayorga-Buiza, Maria Martin-Lopez, Olga Munoz, Juan Carlos Gomez-Martin, Maria Isabel Relimpio-Lopez, Jesus Aceituno-Castro, Manuel A. Perales-Esteve, Antonio Puppo-Moreno, Francisco Jose Garcia-Cozar, Lucia Olvera-Collantes, Raquel Gomez-Diaz, Silvia de los Santos-Trigo, Monserrat Huguet-Carrasco, Manuel Rey, Emilia Gomez, Rosario Sanchez-Pernaute, Javier Padillo-Ruiz, Javier Marquez-Rivas
Summary: This study demonstrates the feasibility of using hyperspectral image analysis in the visible and near-infrared range for primary screening of SARS-CoV-2. By applying spectral feature descriptors, partial least square-discriminant analysis, and artificial intelligence, information can be extracted from fluid samples and analyzed quantitatively and descriptively. The proposed technology is reagent-free, fast, scalable, and could significantly reduce the number of molecular tests required for COVID-19 mass screening, even in resource-limited settings.
SCIENTIFIC REPORTS
(2022)
Article
Geosciences, Multidisciplinary
Masoud Davari, Salah Aldin Karimi, Hossein Ali Bahrami, Sayed Mohammad Taher Hossaini, Soheyla Fahmideh
Summary: The study demonstrated that using spectroscopy for rapid estimation of soil engineering properties showed promising results in different soil samples, with good accuracy for some properties but room for improvement for others.
Article
Automation & Control Systems
Matteo Stocchero, Martino De Nardi, Bruno Scarpa
Summary: In this study, an alternative formulation of PLS2 based on gradient descent method is proposed and a new algorithm called gradient descent PLS2 is introduced to solve the least squares problem. The algorithm uses well-defined elements of linear algebra and is developed within the field of non-linear programming, showing equivalent performance to the standard eigenvalue PLS2 algorithm.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
(2022)
Article
Food Science & Technology
Xiao Wang, Carlos Esquerre, Gerard Downey, Lisa Henihan, Donal O'Callaghan, Colm O'Donnell
Summary: This study evaluated the potential of combining Vis-NIR and Raman spectral data fusion with chemometric models for commercial infant formula samples. The study found the best models for discriminating between storage temperatures and predicting storage time, demonstrating the application potential of Vis-NIR and Raman process analytical tools in quality assessment and process control of infant formula manufacture.
INNOVATIVE FOOD SCIENCE & EMERGING TECHNOLOGIES
(2021)
Article
Spectroscopy
Bo Yu, Changxiang Yan, Jing Yuan, Ning Ding, Zhiwei Chen
Summary: Visible and near-infrared (Vis-NIR) spectroscopy technique has been recognized as a cost-effective, rapid, non-destructive alternative to traditional soil physicochemical analysis to estimate soil properties. This study proposes a method to select characteristic wavelengths with optimal spectral resolution to improve the prediction performance. By using a 'two-step' wavelength selection method and the artificial bee colony (ABC) algorithm, a better prediction accuracy for soil properties was obtained compared to using full-spectra models.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2023)
Article
Chemistry, Applied
Hong-Ju He, Yangyang Wang, Mian Zhang, Yuling Wang, Xingqi Ou, Jingli Guo
Summary: This study aimed to predict the reducing sugar content of sweet potatoes using near-infrared reflectance and absorbance spectra. The results showed that the model built with optimal wavelengths had good performance in predicting the reducing sugar content.
JOURNAL OF FOOD COMPOSITION AND ANALYSIS
(2022)
Article
Environmental Sciences
Anna A. Paltseva, Maha Deeb, Erika Di Iorio, Luana Circelli, Zhongqi Cheng, Claudio Colombo
Summary: The successful use of visible and near-infrared reflectance spectroscopy analysis combined with principal component regression and partial least-square regression was applied to detect different forms of lead. Linear discriminant analysis was used to classify soil into different categories of lead contamination risks. Different models were used to predict and compare total and bioaccessible lead concentrations.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Soil Science
Najmeh Rasooli, Mohammad Hady Farpoor, Majid Mahmoodabadi, Isa Esfandiarpour-Boroujeni
Summary: This research aimed to ascertain the performance of visible and near-infrared spectroscopy (VisNIR) in detecting soil variations related to pedogenetic processes and pedoenvironmental conditions and to show the perspective of the most important variables changing spectral behavior in Lut Watershed.
SOIL & TILLAGE RESEARCH
(2023)
Review
Food Science & Technology
Yong He, Qinlin Xiao, Xiulin Bai, Lei Zhou, Fei Liu, Chu Zhang
Summary: Fruits are susceptible to damage during their growth, harvest, and storage, which can impact both food safety and economic benefits. To address this issue, there is a need for rapid and nondestructive detection methods for fruit damage. This paper summarizes various nondestructive techniques for detecting fruit damage, providing insights for future research and real-world applications.
CRITICAL REVIEWS IN FOOD SCIENCE AND NUTRITION
(2022)
Article
Agriculture, Multidisciplinary
Yufei Liu, Jichun Wang, Yachao Shi, Zhenni He, Fei Liu, Wenwen Kong, Yong He
Summary: The rapid development of new technologies such as automatic control, sensors, and AI has greatly contributed to the advancement of unmanned airboats (UA) and their applications in fields like environmental monitoring and agriculture. This review presents the challenges and potential solutions in the development of UA, along with its structure, comprehensive applications, and future prospects. It provides theoretical and technical support for the promotion of UA for automated operations.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
Article
Computer Science, Information Systems
Xiangyu Lu, Rui Yang, Jun Zhou, Jie Jiao, Fei Liu, Yufei Liu, Baofeng Su, Peiwen Gu
Summary: This study proposes an effective and accurate approach based on Ghost-convolution and Transformer networks for diagnosing grape leaf in the field. The results show that the proposed method achieves high accuracy and fast processing speed, making it suitable for diagnosing grape diseases and pests in vineyards.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Biochemistry & Molecular Biology
Mahamed Lamine Guindo, Muhammad Hilal Kabir, Rongqin Chen, Jing Huang, Fei Liu, Xiaolong Li, Hui Fang
Summary: This study investigated the combination of LIBS and Vis-NIR for fast detection of phosphorus (P) and potassium (K) in organic fertilizers. XAI was used to extract valuable features from both sensors, and the fusion of data was performed. The outcomes showed that the fusion method was more efficient in detecting P and K compared to single-sensor detection.
Article
Environmental Sciences
Jiyu Peng, Yifan Liu, Longfei Ye, Jiandong Jiang, Fei Zhou, Fei Liu, Jing Huang
Summary: Minerals in rice leaves are important indicators of plant health and are used to guide plant management. This study used LIBS to predict mineral content in rice leaves under Cr stress. PLSR achieved good performance in predicting Ca, Fe, Mg, K, Mn, and Na concentrations. The correlation between different spectral lines was also analyzed. This method provides a fast and accurate approach for predicting minerals in rice leaves under Cr stress, which is crucial for environmental protection and food safety.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Remote Sensing
Xiangyu Lu, Jun Zhou, Rui Yang, Zhiyan Yan, Yiyuan Lin, Jie Jiao, Fei Liu
Summary: This study presents a novel approach to extract and map phenological traits of rice directly from unmanned aerial vehicle (UAV) photographs. A multi-stage rice field segmentation dataset named PaddySeg was built, and an efficient Ghost Bilateral Network (GBiNet) was proposed to generate trait masks. The mapping of rice phenology was achieved by interpolation on trait value-location pairs.
Article
Engineering, Environmental
Wei Wang, Zun Man, Xiaolong Li, Rongqin Chen, Zhengkai You, Tiantian Pan, Xiaorong Dai, Hang Xiao, Fei Liu
Summary: This study investigated the effect of cadmium on root phenotypes by examining cadmium accumulation, adversity physiology, morphological parameters, and microstructure characteristics. The study found that cadmium had both a low-promotion and high-inhibition effect on root phenotypes. Additionally, rapid detection methods for cadmium accumulation and adversity physiology were developed using spectroscopic technology and chemometrics, significantly reducing the detection time compared to laboratory analysis.
JOURNAL OF HAZARDOUS MATERIALS
(2023)
Article
Engineering, Environmental
Xiaolong Li, Jing Huang, Rongqin Chen, Zhengkai You, Jiyu Peng, Qingcai Shi, Gang Li, Fei Liu
Summary: Rapid and accurate detection of agricultural soil chromium is crucial for soil pollution assessment. Laser-induced breakdown spectroscopy (LIBS) is a rapid and chemical-free method for hazardous metal analysis, but its detection is interfered by uncertainty and matrix effect. In this study, a strategy combining linear weighted network (LWNet) was proposed to reduce uncertainty, and the AWN-LWNet framework was proposed to reduce the matrix effect in two soil types. The results indicated that LWNet outperformed traditional machine learning and achieved an average relative error of 2.08% and 3.03% for yellow brown soil and lateritic red soil, respectively. AWN-LWNet was the optimal model to reduce matrix effect (ARE=4.12%). Besides, AWN-LWNet greatly reduced the number...
JOURNAL OF HAZARDOUS MATERIALS
(2023)
Article
Biochemistry & Molecular Biology
Zhengkai You, Xiaolong Li, Jing Huang, Rongqin Chen, Jiyu Peng, Wenwen Kong, Fei Liu
Summary: In this study, a novel liquid-solid conversion method based on agarose films was proposed for the detection of heavy metals in water. The method involved converting water samples into semi-solid hydrogels using agarose and drying them into agarose films to enhance the signal intensities. Calibration curves were constructed for Cd, Pb, and Cr, and the method was validated using standard heavy metal solutions and real water samples. The results demonstrated the effectiveness of the method, with high values of R-2 and low LOD values, as well as good recovery rates. The agarose film-based liquid-solid conversion method shows great potential for heavy metal monitoring in water.
Article
Biochemistry & Molecular Biology
Xinmeng Luo, Rongqin Chen, Muhammad Hilal Kabir, Fei Liu, Zhengyu Tao, Lijuan Liu, Wenwen Kong
Summary: In this study, laser-induced breakdown spectroscopy (LIBS) was used to detect the heavy metal content in Fritillaria thunbergii. Quantitative prediction models were established using a back-propagation neural network (BPNN) optimized using the particle swarm optimization (PSO) algorithm and sparrow search algorithm (SSA). The results showed that the optimized BPNN models had better accuracy than the unoptimized model. The SSA-BP model had the advantage of faster speed and higher prediction accuracy at low concentrations.
Article
Food Science & Technology
Muhammad Hilal Kabir, Mahamed Lamine Guindo, Rongqin Chen, Xinmeng Luo, Wenwen Kong, Fei Liu
Summary: This study used laser-induced breakdown spectroscopy coupled with variable selection and chemometrics to quickly and accurately detect heavy metals (Cd, Cu, and Pb) in Fritillaria thunbergii by analyzing selected variables. The results showed that this method can improve detection efficiency and accuracy.
Proceedings Paper
Computer Science, Artificial Intelligence
Fei Liu, Fengxu Zhou, Fei Zhang, Wujing Cao
Summary: This study proposes an innovative fall detection and alarm system for the elderly in the family environment based on deep learning. The system utilizes a camera and an edge device to detect and alert users to falls without touching their body. With the use of a lightweight object detection model and an inference engine, the system achieves high accuracy and comfort in fall detection.
INTELLIGENT ROBOTICS AND APPLICATIONS (ICIRA 2022), PT I
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Fei Liu, Wujing Cao, Qingmei Li
Summary: This study proposes a fast and efficient detection method based on image processing to improve the efficiency of packaging box sorting and reduce labor intensity. It involves pose estimation and transformation relationship solving from camera coordinate system to manipulator's base coordinate system. SIFT method is used for packaging feature points, FLANN method for matching, and EPnP method for pose solving. The nine-point calibration method is used to solve the transformation relationship. The test results show that the method achieves satisfactory results by weighing detection accuracy and speed.
INTELLIGENT ROBOTICS AND APPLICATIONS (ICIRA 2022), PT I
(2022)
Article
Environmental Sciences
Yuchao Zhu, Jun Zhou, Yinhui Yang, Lijuan Liu, Fei Liu, Wenwen Kong
Summary: The study proposes an improved YOLOv4 model, which combines Mobilenetv3 network, CBAM module, and ASFF module, and optimizes the detection and counting of fruit tree canopies using the K-means algorithm, linear scaling, and cosine annealing learning strategy. The results show that the improved model can achieve fast and accurate recognition and counting of fruit tree canopies in orchard environments, with high detection accuracy and counting precision.
Article
Remote Sensing
Jun Zhou, Xiangyu Lu, Rui Yang, Huizhe Chen, Yaliang Wang, Yuping Zhang, Jing Huang, Fei Liu
Summary: This study develops a novel yield index by fusing multiple indices based on unmanned aerial vehicle imagery, which shows great potential in crop yield monitoring.
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)
