Article
Food Science & Technology
Ya-Qin Wang, Guang-Min Liu, Li-Ping Hu, Xue-Zhi Zhao, De-Shuang Zhang, Hong-Ju He
Summary: Purple Chinese cabbage (PCC) is a popular breeding trend due to its attractive color and high nutritional quality enriched with anthocyanidins. This study established a rapid quantitative detection method for anthocyanidins in PCC using Near Infrared Spectroscopy (NIR), which combined spectral data and chemometric results to predict anthocyanidins content. The developed NIR prediction models showed excellent performance, and this time-saving and convenient method can be applied in purple vegetable breeding practice.
Article
Environmental Sciences
Kensuke Kawamura, Tomohiro Nishigaki, Andry Andriamananjara, Hobimiarantsoa Rakotonindrina, Yasuhiro Tsujimoto, Naoki Moritsuka, Michel Rabenarivo, Tantely Razafimbelo
Summary: The study compared different models for predicting soil available phosphorus content, with the one-dimensional convolutional neural network (1D-CNN) model showing the highest accuracy. The results suggest that the 1D-CNN model can significantly improve the predictive ability for estimating soil available phosphorus from visible and near-infrared spectral data.
Article
Chemistry, Analytical
Baohua Tan, Wenhao You, Shihao Tian, Tengfei Xiao, Mengchen Wang, Beitian Zheng, Lina Luo
Summary: This study presents a method for rapid detection of nitrogen content in soil using near-infrared spectroscopy and random forest regression. The results show that the proposed method has higher prediction accuracy compared to other models and effectively reduces data redundancy.
Article
Soil Science
Zijin Bai, Songchao Chen, Yongsheng Hong, Bifeng Hu, Defang Luo, Jie Peng, Zhou Shi
Summary: This study collected 315 topsoil samples from the Alar Reclamation Area in South Xinjiang, China, and used visible near-infrared (Vis-NIR) spectroscopy and deep learning algorithms combined with variable selection algorithms to estimate soil inorganic carbon (SIC) concentration. The results showed that the combination of IRF and LSTM models achieved the highest estimation accuracy for SIC.
Article
Soil Science
Yongsheng Hong, Muhammad Abdul Munnaf, Angela Guerrero, Songchao Chen, Yaolin Liu, Zhou Shi, Abdul Mounem Mouazen
Summary: Spectral techniques, including the fusion of visible-to-near-infrared and mid-infrared absorbance, can improve the estimation of soil organic carbon. The use of continuous wavelet transform and optimal band combination strategies contribute to the accuracy of the prediction models. Among the investigated models, the combination of visible-to-near-infrared and mid-infrared using the optimal band combination fusion at a specific scale yielded the best prediction.
SOIL & TILLAGE RESEARCH
(2022)
Article
Agronomy
Yunfeng Li, Quanqing Feng, Dongwei Li, Mingfa Li, Huifeng Ning, Qisheng Han, Abdoul Kader Mounkaila Hamani, Yang Gao, Jingsheng Sun
Summary: This study used crop models to analyze the response of cotton in southern Xinjiang to different soil water content and salinity levels. Threshold values for water and salt and total irrigation amounts were determined, providing reference for regulating water and salt in arid saline-alkali regions.
Article
Environmental Sciences
Chengbiao Fu, Anhong Tian, Daming Zhu, Junsan Zhao, Heigang Xiong
Summary: Soil salinity in arid and semi-arid areas can be effectively monitored and estimated using VNIR-SWIR spectroscopy, feature band selection methods, and machine learning models. The Grunwald-Letnikov fractional-order derivative, combined with appropriate spectral bands, showed promising results in accurately estimating soil salinity in different zones with varying degrees of human interference. The study highlights the importance of spectral analysis techniques in improving the accuracy of soil salinity estimation.
Article
Geology
Guo Jiang, Kefa Zhou, Jinlin Wang, Guoqing Sun, Shichao Cui, Tao Chen, Shuguang Zhou, Yong Bai, Xi Chen
Summary: Rock geochemistry plays a crucial role in mineral resource exploration. This study collected rock samples and used chemical analysis and spectral analysis to estimate the Cu content. The results show that fractional-order derivatives can better highlight spectral details, and combining fractional-order derivatives with a random forest model performs best for the full sample data.
ORE GEOLOGY REVIEWS
(2022)
Article
Polymer Science
Jihong Zhang, Quanjiu Wang, Yuyang Shan, Yi Guo, Weiyi Mu, Kai Wei, Yan Sun
Summary: The scientific use of sodium carboxymethyl cellulose (CMC) is crucial for improving the production capacity of saline-alkali soil and achieving green agriculture and sustainable land use. This study investigated the effects of different CMC dosages on the infiltration characteristics, water and salt distribution, and salt leaching of saline-alkali soil. The results showed that CMC can increase the cumulative infiltration, infiltration time, soil water holding capacity, and salt leaching efficiency. The study provides a theoretical basis for the rational application of CMC to improve saline-alkali soil in arid areas.
Article
Chemistry, Multidisciplinary
Jiangang Shen, Weiming Qiao, Huizhe Chen, Jun Zhou, Fei Liu
Summary: This study uses Vis/NIR spectroscopy to predict the content of nitrogen, phosphorus, and potassium in fertilizers. By selecting characteristic wavelengths, the spectral variables were reduced by 9/10, leading to improved model performance.
APPLIED SCIENCES-BASEL
(2021)
Article
Biochemistry & Molecular Biology
Soo-In Sohn, Subramani Pandian, Young-Ju Oh, John-Lewis Zinia Zaukuu, Yong-Ho Lee, Eun-Kyoung Shin
Summary: This study successfully differentiated four B. juncea varieties using visible near-infrared spectroscopy combined with multiple chemometric approaches, with the combination of standard normal variate and deep learning achieving the highest classification accuracy of 100%. Other chemometric methods such as support vector machine, generalized linear model, and random forest also achieved 100% classification accuracy.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Geosciences, Multidisciplinary
Gopal Ramdas Mahajan, Bappa Das, Bhaskar Gaikwad, Dayesh Murgaonkar, Ashwini Desai, Shaiesh Morajkar, Kiran Puna Patel, Rahul Mukund Kulkarni
Summary: The study aimed to estimate the properties of salt-affected soils using hyperspectral remote sensing. Results showed significant achievements in predicting soil properties, indicating the potential of visible near-infrared spectroscopy in predicting properties of salt-affected soils.
Article
Agronomy
Hao Zhang, Julin Gao, Xiaofang Yu, Daling Ma, Shuping Hu, Tianao Shen
Summary: This study investigated the effects of different tillage methods on soil improvement and maize growth in cropland with varying degrees of salinization. The results showed that deep straw return significantly improved soil nutrients and reduced salinity levels, leading to better growth and higher yield of maize, especially in moderately saline-alkali land.
Review
Soil Science
Yuchen Lin, Cailian Yu, Yuanbo Zhang, Liu Lu, Dan Xu, Xianlong Peng
Summary: The continuous population growth has increased the demand for food. Biochar (BC) has the potential to improve soil properties and crop yield, but the efficacy of unmodified BC in improving saline-alkali soil is still controversial. This paper summarizes the methods of modifying BC and the effects on salt-affected soil and soil properties. It also highlights the importance of using modified BC carefully according to the actual situation.
SOIL USE AND MANAGEMENT
(2023)
Article
Chemistry, Analytical
Yong Hao, Xiyan Li, Chengxiang Zhang, Zuxiang Lei
Summary: This study conducted online discriminant analysis on healthy Yali pears and those with different degrees of browning using visible-near infrared (Vis-NIR) spectroscopy. The results showed that the prediction accuracy of the original spectrum combined with a 1D-CNN deep learning model reached 100% for the test sets of browned pears and healthy pears. Features extracted by the 1D-CNN method were converted into images by Gramian angular field (GAF) for PCA visual analysis, showing that deep learning had good performance in extracting features. In conclusion, Vis-NIR spectroscopy combined with the 1D-CNN discriminant model can realize online detection of browning in Yali pears.
Article
Geochemistry & Geophysics
Ba Tuan Le, Dong Xiao, Yachun Mao, Dakuo He, Jialiu Xu, Liang Song
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2019)
Article
Optics
Yachun Mao, Ba Tuan Le, Dong Xiao, Dakuo He, Chongmin Liu, Longqiang Jiang, Zhichao Yu, Fenghua Yang, Xinxin Liu
OPTICS AND LASER TECHNOLOGY
(2019)
Article
Engineering, Multidisciplinary
Dong Xiao, Hongfei Xie, Longqiang Jian, Ba Tuan Le, Jichun Wang, ChongMin Liu, Hongzong Li
ENGINEERING APPLICATIONS OF COMPUTATIONAL FLUID MECHANICS
(2020)
Article
Chemistry, Analytical
Ba Tuan Le
VIBRATIONAL SPECTROSCOPY
(2020)
Article
Optics
Ba Tuan Le, Thai Thuy Lam Ha
Article
Instruments & Instrumentation
Yanhua Fu, Lushan Wan, Dong Xiao, Ba Tuan Le
INFRARED PHYSICS & TECHNOLOGY
(2020)
Article
Engineering, Electrical & Electronic
Vu Quoc Huy, Tran Ngoc Binh
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
(2020)
Article
Chemistry, Analytical
Dong Xiao, Ba Tuan Le
MICROCHEMICAL JOURNAL
(2020)
Article
Chemistry, Analytical
Dong Xiao, Xiwen Liu, Ba Tuan Le, Zhiwen Ji, Xiaoyu Sun
Article
Spectroscopy
Dong Xiao, Ba Tuan Le, Thai Thuy Lam Ha
Summary: A new iron ore identification method combining deep learning with visible-infrared reflectance spectroscopy was proposed and a high accuracy classification model was established.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2021)
Article
Engineering, Multidisciplinary
Jingyi Liu, Xinxin Liu, Chongmin Liu, Ba Tuan Le, Dong Xiao
Summary: The Extreme Learning Machine algorithm was originally proposed to overcome the challenges faced by the backpropagation algorithm, and has since been extended to multi-layered neural networks. The pruning multi-layered ELM algorithm proposed in this paper uses Cholesky factorization and Givens rotation to automatically find the optimal number of hidden nodes. The fast updating process during pruning ensures the stability and efficiency of the algorithm.
MATHEMATICAL PROBLEMS IN ENGINEERING
(2021)
Article
Spectroscopy
Dong Xiao, Thi Tra Giang Le, Trung Thanh Doan, Ba Tuan Le
Summary: This study combines spectroscopy with deep learning algorithms to propose a method for rapidly identifying coal types. The spectral features of coal are extracted through a convolutional neural network, and an extreme learning machine is used as a classifier to identify these features. Experimental results demonstrate that this method can rapidly and accurately identify coal types.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2022)
Article
Computer Science, Artificial Intelligence
Dong Xiao, Quoc Huy Vu, Ba Tuan Le, Thai Thuy Lam Ha
Summary: This research investigates a novel hyperspectral remote sensing processing method that utilizes a 3D convolutional neural network and fusion data to monitor and map changes in iron ore stopes. By combining remote sensing and ground data, the method provides a quick, accurate, and cost-effective approach.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Chemistry, Analytical
Michel Rocha Baqueta, Augusto Cesar Costa-Santos, Ana Paula Rebellato, Gisele Marcondes Luz, Juliana Azevedo Lima Pallone, Federico Marini, Alexsandro Lara Teixeira, Douglas N. Rutledge, Patricia Valderrama
Summary: This study reports the essential element composition of new Brazilian Canephora coffees and applies chemometric tools for analysis. The results demonstrate the suitability of this method for origin and species discrimination based on the inorganic fraction of coffee.
MICROCHEMICAL JOURNAL
(2024)
Article
Chemistry, Analytical
Mengjie Li, Jiapeng Wang, You Zhou, Yang Chen, Lingying Xia
Summary: A novel photoelectrochemical biosensor based on gold nanoparticles and specific structures was developed for highly sensitive detection of mercury ion. The multiple sandwich structures hindered electron supply and light harvesting, resulting in a weakened PEC signal, while the specific structures extinguished the PEC signal, enabling quantitative detection of Hg2+. The sensor exhibited high selectivity and stability, with potential applications in environmental detection, biological analysis, and medical research.
MICROCHEMICAL JOURNAL
(2024)
Article
Chemistry, Analytical
Mohamed A. Korany, Rasha M. Youssef, Marwa A. A. Ragab, Mostafa A. Afify
Summary: A stability-indicating fit-for-purpose method was developed for the determination of HC, TL, and PS in syrup dosage form. The method successfully separated CL from THY and quantified the analytes using HPLC-DAD. The robustness of the method was assessed through statistical analysis and self-validation.
MICROCHEMICAL JOURNAL
(2024)
Article
Chemistry, Analytical
Lingling Lin, Minyu Li, Ping Li, Chenqing Ye, Huanglong Zhuang, Shaohuang Weng, Feng Chen
Summary: This study developed a highly sensitive and selective electrochemical sensor for simultaneous detection of dopamine and uric acid. The sensor exhibited excellent anti-interference and stability, and could accurately measure dopamine and uric acid in human urine samples.
MICROCHEMICAL JOURNAL
(2024)
Article
Chemistry, Analytical
Peifang Chen, Caiyun Jiang, Zhouping Wang, Hong-zhen Lian, Xiaoyuan Ma
Summary: In this study, a high-performance SERS-active aptasensor was successfully developed for the quantitative analysis of AFB1 in cereal grains, which is of great significance in the field of food safety.
MICROCHEMICAL JOURNAL
(2024)
Article
Chemistry, Analytical
E. Abas, C. Marina-Montes, C. Perez-Marin, J. Puimedon, J. Anzano
Summary: This study conducted a comprehensive measurement of natural and anthropogenic radionuclides in soil, water, and air in different locations around Deception Island in Antarctica. The results revealed significant levels of 210Pb and anthropogenic 137Cs in soil samples near old human settlements and facilities, as well as detectable levels of 137Cs and 60Co in water samples from old hunting areas. The findings also suggested potential resuspension processes based on higher-than-expected air quality results.
MICROCHEMICAL JOURNAL
(2024)
Article
Chemistry, Analytical
Joao Franciso Allochio, Nayara A. dos Santos, Nathalia dos S. Conceicao, Clara S. D. Baptista, Keyller B. Borges, Valdemar Lacerda Jr, Wanderson Roma
Summary: This study developed a fiber spray ionization mass spectrometry (FSI-MS) method, which shows great potential in detecting illicit drugs. Compared with paper spray ionization mass spectrometry (PSI-MS), FSI-MS demonstrates higher sensitivity in COC detection.
MICROCHEMICAL JOURNAL
(2024)
Article
Chemistry, Analytical
Dina A. Ahmed, Ola G. Hussein, Mamdouh R. Rezk, Mohamed Abdelkawy, Yasmin Rostom
Summary: The main goal of this study was to develop two green chromatographic techniques, HPLC and TLC, for the determination of alcaftadine (ALF) in pharmaceutical formulation and biological samples. The developed HPLC technique showed high efficiency and minimal environmental impact, successfully identifying ALF in the presence of its degradate. The TLC method provided a stability indicating study for ALF and was determined to be safe, green, and eco-friendly.
MICROCHEMICAL JOURNAL
(2024)
Article
Chemistry, Analytical
Abdullah Taner Bisgin
Summary: A green, speedy, and handy method for separation and determination of four commonly used food colorants was established using vortex assisted sequential-simultaneous liquid phase micro-extraction (VA-SS-LPME). The method does not require any instrumental chromatographic techniques. The procedure includes sequential separation steps using different extractants and simultaneous UV-vis spectrophotometric determination steps. The method is environmentally friendly and applicable for determination of colorants in food and pharmaceuticals.
MICROCHEMICAL JOURNAL
(2024)
Article
Chemistry, Analytical
Yifan Zhang, Tong Zhang, Wenjing Ba, Li Liu, Yuan Rao, Xiaodan Zhang, Hanhan Zhang, Xiu Jin
Summary: This paper proposes a novel spectral transfer modelling method based on neural network architecture searching for the asymptomatic prediction of Akizuki pear cork spot disorder. The experiments show that the model by this method is more effective, achieving an accuracy of 82.61%.
MICROCHEMICAL JOURNAL
(2024)
Article
Chemistry, Analytical
Krzysztof Greda, Maja Welna, Anna Szymczycha-Madeja, Pawel Pohl
Summary: For the first time, a dispersive micro-solid phase extraction (D-mu SPE) based on graphene oxide was used for the ultrasensitive determination of Cd. With this method, Cd can be efficiently extracted from a mixture of alkali and alkaline earth metals without the need for an elution step. The combination of D-mu SPE and SAGD OES significantly reduces matrix effects and improves the tolerance of Cd to alkali metals. The method shows simplicity in the measurement system and the commercially available nanosorbent used.
MICROCHEMICAL JOURNAL
(2024)
Article
Chemistry, Analytical
P. K. Fathima Anjila, G. R. Tharani, Anand Sundaramoorthy, Venkat Kumar Shanmugam, Karthikeyan Subramani, Shanmugavel Chinnathambi, Ganesh N. Pandian, Vimala Raghavan, Andrews Nirmala Grace, Singaravelu Ganesan, Mangaiyarkarasi Rajendiran
Summary: This work proposes a rapid and sensitive spectroscopic method for detecting melamine in food products using rare-earth Terbium-doped Graphene Quantum Dots (Tb-GQDs) synthesized by microwave and simple chemical conjugation methods. The synthesized Tb-GQDs show a spherical shape with a size of approximately 6 nm and a quantum yield of 52%. The maximum detection limit for melamine concentration in milk and milk products is found to be 0.31 μM. The dual emitting Tb-GQDs provide a sensitive and effective platform for real-time detection of melamine in food samples, particularly in milk, and show promising potential in the food industry.
MICROCHEMICAL JOURNAL
(2024)
Review
Chemistry, Analytical
Piyush Dey, Mandeep Kaur, Akhil Khajuria, Dilmeet Kaur, Manpreet Singh, Hema Kumari Alajangi, Neha Singla, Gurpal Singh, Ravi Pratap Barnwal
Summary: Environmental issues, such as the uncontrolled release of dangerous pollutants, have significant impacts on human health. Traditional methods for detecting pollutants require specialized personnel and equipment, but nanotechnology has improved the performance of biosensors. This article discusses the use of nanotechnology in pollutant detection and the associated techniques.
MICROCHEMICAL JOURNAL
(2024)
Article
Chemistry, Analytical
Sa Dong, Qiuyun Shi, Lingjun Guan, Yulong Wang, Pengyan Liu, Cunzheng Zhang, Jianguo Feng
Summary: In this study, a highly sensitive indirect competitive chemiluminescence enzyme immunoassay (icCLEIA) method was developed for the determination of sodium pentachlorophenolate (PCP-Na) and its metabolite pentachlorophenol (PCP). The method showed high specificity and affinity with a detection limit of 0.0032 ng/mL for PCP-Na and 0.0192 ng/mL for PCP. The method had no cross reaction with other chlorophenols compounds except for PCP. The average recoveries in chicken, pork and fish samples were 81.3-105.8% with low coefficient of variation (CV).
MICROCHEMICAL JOURNAL
(2024)
Article
Chemistry, Analytical
Palaniappan Ilayaraja, Murugan Manivannan, Paramasivam Parthiban
Summary: Nirmatrelvir, an antiviral drug used for the treatment of COVID-19, has been recommended by the World Health Organization. We developed an optimized analytical method for the quantification of Nirmatrelvir and its products, with high sensitivity and a wide linear range. The method also meets the requirements for greenness evaluation.
MICROCHEMICAL JOURNAL
(2024)
