Article
Plant Sciences
Renan Falcioni, Joao Vitor Ferreira Goncalves, Karym Mayara de Oliveira, Caio Almeida de Oliveira, Amanda Silveira Reis, Luis Guilherme Teixeira Crusiol, Renato Herrig Furlanetto, Werner Camargos Antunes, Everson Cezar, Roney Berti de Oliveira, Marcelo Luiz Chicati, Jose Alexandre M. Dematte, Marcos Rafael Nanni
Summary: Reflectance hyperspectroscopy has the potential to elucidate biochemical changes in plants. This study used UV-VIS-NIR-SWIR spectral range to identify different biochemical constituents in Hibiscus and Geranium plants. Through the application of advanced algorithms, the most responsive wavelengths were discerned, and PLSR models consistently achieved high R2 values. These findings highlight the efficacy of spectroscopy coupled with multivariate analysis in evaluating biochemical compounds and indicate the promising potential of hyperspectroscopy in precision agriculture and plant phenotyping.
Article
Chemistry, Analytical
Min-Jee Kim, Hye-In Lee, Jae-Hyun Choi, Kyoung Jae Lim, Changyeun Mo
Summary: This study investigated the spectral characteristics of topsoil from four major rivers in the Republic of Korea and developed a machine learning-based model to predict soil organic matter (SOM) content using spectroscopic techniques. The results identified the important wavelength of SOM in topsoil and confirmed the predictability of SOM content, which could be used for the construction of a national topsoil database.
Article
Agronomy
Min-Jee Kim, Jae-Eun Lee, Insuck Back, Kyoung Jae Lim, Changyeun Mo
Summary: This study developed a machine and deep learning-based model using hyperspectral imaging to rapidly measure the total nitrogen (TN) content in topsoil. By collecting 139 soil samples and developing prediction models, it was found that the hyperspectral imaging-based model had high accuracy in predicting TN content. This method can be used to establish a topsoil database and design conservation strategies.
Article
Chemistry, Analytical
Siyu Yao, Christopher Ball, Gonzalo Miyagusuku-Cruzado, M. Monica Giusti, Didem P. Aykas, Luis E. Rodriguez-Saona
Summary: A novel approach using FT-NIR was developed for rapid detection and quantification of predominant cannabinoids in hemp, with excellent correlation and low standard error of prediction. This method can be used as an alternative for in-situ assessment of hemp quality.
Article
Geochemistry & Geophysics
Shilan Felegari, Alireza Sharifi, Mohammad Khosravi, Sergei Sabanov
Summary: Remote sensing technology integrated with machine learning is an effective and low-cost approach for environmental and earth sciences studies. This study aimed to accurately map cadmium concentration using different regression models, including SVR, PLSR, and ANNs. Multitemporal images were found to be more suitable for monitoring heavy metal concentrations compared to single-date images. Among the investigated features, the original band was identified as the most appropriate for regression analysis. The SVR model with the original band as input provided the most accurate estimation of cadmium concentration in the range of 8-26 mg/kg.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2023)
Article
Food Science & Technology
Maninder Meenu, Yaqian Zhang, Uma Kamboj, Shifeng Zhao, Lixia Cao, Ping He, Baojun Xu
Summary: In this study, near-infrared (NIR) spectroscopy combined with Chemometrics was used to predict the beta-glucan content in oats rapidly and non-destructively. The results showed that the wavelength region 700-1300 nm is sufficient for predicting beta-glucan content accurately.
Article
Soil Science
Hasan Mozaffari, Ali Akbar Moosavi, Yaser Ostovari, Mohammad Amin Nematollahi, Mahrooz Rezaei
Summary: Spectroscopy in visible and near-infrared regions is a rapid, non-destructive, and cost-effective method for analyzing soil samples. This study used PLSR and SMLR approaches to predict soil properties and developed STFs models. The results showed that PLSR models performed better overall, while STFs models had good accuracy in predicting certain soil properties. The use of STFs models is recommended for predicting properties of calcareous soils.
Article
Plant Sciences
Lahcen Hssaini, Rachid Razouk, Yassine Bouslihim
Summary: Mid-infrared spectroscopy combined with partial least squares regression was used to predict the distribution of phenolic acids and flavonoids in fig. The results showed high accuracy and significant differences between peel and pulp extracts.
FRONTIERS IN PLANT SCIENCE
(2022)
Article
Chemistry, Multidisciplinary
Natalia Leone, Valeria Ancona, Ciro Galeone, Carmine Massarelli, Vito Felice Uricchio, Antonio Pasquale Leone
Summary: This study evaluated the application of visible-near infrared reflectance spectroscopy in conjunction with partial least square regression analysis in soil reclamation from polychlorinated biphenyls. The preliminary results showed that this method can rapidly and cost-effectively predict the presence of PCBs in soil.
APPLIED SCIENCES-BASEL
(2022)
Article
Plant Sciences
Renan Falcioni, Thaise Moriwaki, Werner Camargos Antunes, Marcos Rafael Nanni
Summary: This study proposes an efficient method for estimating photosynthetic performance and photosystem status using remote sensing hyperspectroscopy. The results show promising accuracy and precision in determining multiple attributes simultaneously, providing a better understanding of photosystem dynamics in tobacco plants.
Article
Food Science & Technology
Seyoung Ju, Sooji Song, Jeongnam Lee, Sungwon Hwang, Yoonmi Lee, Yongseok Kwon, Yuyoung Lee
Summary: This study examined the sensory characteristics and consumer acceptability of five different soy milk samples, finding that one sample outperformed the others in overall liking, flavor, taste, mouthfeel, sweetness, repeated consumption, and recommendation. Consumers preferred sweet, nutty, roasted soybean, and cooked soybean flavors, while disliking grayness, raw soybean flavor, and certain mouthfeel attributes. Sweetness was found to be closely linked to nutty and roasted soybean flavors.
Article
Chemistry, Analytical
Sulaymon Eshkabilov, John Stenger, Elizabeth N. Knutson, Erdem Kucuktopcu, Halis Simsek, Chiwon W. Lee
Summary: The influence of nitrogen, phosphorus, and potassium compounds on the growth dynamics of hydroponically grown lettuce was studied, and optimal wavebands were found for estimating the nutrient levels. The results showed a high correlation between hyperspectral imaging data and laboratory-measured data.
Article
Chemistry, Analytical
Shuo Wang, Xiaofang Liu, Takehiro Tamura, Nobuyuki Kyouno, Han Zhang, Jie Yu Chen
Summary: This study developed a rapid method for predicting the sensory qualities of miso products using visible/near-infrared spectroscopy combined with a partial least-square regression algorithm, demonstrating its effectiveness and feasibility. The best performing model utilized the first derivative pretreatment of the spectra, effectively classifying miso products and potentially serving as a low-cost and nondestructive quality assessment tool.
ANALYTICAL LETTERS
(2021)
Article
Plant Sciences
Shan Kothari, Rosalie Beauchamp-Rioux, Florence Blanchard, Anna L. Crofts, Alizee Girard, Xavier Guilbeault-Mayers, Paul W. Hacker, Juliana Pardo, Anna K. Schweiger, Sabrina Demers-Thibeault, Anne Bruneau, Nicholas C. Coops, Margaret Kalacska, Mark Vellend, Etienne Laliberte
Summary: Plant ecologists use reflectance spectroscopy to estimate leaf traits, but it is uncertain whether these models can accurately estimate traits across different functional groups and ecosystems. We built empirical models using partial least-squares regression (PLSR) based on leaf spectra and 22 traits. Our models accurately predicted traits such as leaf mass per area, but showed lower accuracy for chemical traits and micronutrients. Our study highlights the potential of spectroscopy in monitoring plant function globally.
Article
Chemistry, Multidisciplinary
Joel B. Johnson, Aimen El Orche, Janice S. Mani, Abderrahmane Ait-Kaddour, Kerry B. Walsh, Mani Naiker
Summary: The potential of handheld NIR and benchtop MIR spectroscopy for predicting antioxidant capacity, dry matter, and total phenolic contents in cayenne pepper was evaluated. The best-performing model for dry matter using NIR spectroscopy had high accuracy, exceeding previous results reported in the literature. The models for antioxidant capacity and total phenolic content did not perform well using NIR or MIR spectroscopy, indicating the need for further optimization in this area.
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Multidisciplinary
Sanjeev Kumar, Arunangshu Ghosh, Bipan Tudu, Rajib Bandyopadhyay
Article
Engineering, Electrical & Electronic
Hemanta Naskar, Sudip Biswas, Bipan Tudu, Rajib Bandyopadhyay, Panchanan Pramanik
IEEE SENSORS JOURNAL
(2019)
Article
Engineering, Electrical & Electronic
Hemanta Naskar, Barnali Ghatak, Sudip Biswas, Prabal Pratap Singh, Bipan Tudu, Rajib Bandyopadhyay
IEEE SENSORS JOURNAL
(2020)
Article
Chemistry, Analytical
Sudip Biswas, Hemanta Naskar, Susmita Pradhan, Yang Wang, Rajib Bandyopadhyay, Panchanan Pramanik
Article
Engineering, Electrical & Electronic
Debangana Das, Trisita Nandy Chatterjee, Runu Banerjee Roy, Bipan Tudu, Ajanto Kumar Hazarika, Santanu Sabhapondit, Rajib Bandyopadhyay
IEEE SENSORS JOURNAL
(2020)
Article
Pharmacology & Pharmacy
Dilip Sing, Subhadip Banerjee, Shibu Narayan Jana, Ranajoy Mallik, Sudarshana Ghosh Dastidar, Kalyan Majumdar, Amitabha Bandyopadhyay, Rajib Bandyopadhyay, Pulok K. Mukherjee
Summary: Andrographis paniculata has been widely used in several countries for medicinal purposes. Near infrared reflectance spectroscopy can be a quick way to assess and grade the quality of the plant material, while a support vector machine model can effectively classify plant samples into three different grades.
FRONTIERS IN PHARMACOLOGY
(2021)
Article
Biochemical Research Methods
Dilip Sing, Shibu Narayan Jana, Subhadip Banerjee, Ranajoy Mallik, Kalyan Majumdar, Pallab Kanti Halder, Amitabha Bandyopadhyay, Nanaocha Sharma, Rajib Bandyoypadhyay, Pulok K. Mukherjee
Summary: This article presents a simple, rapid and green analytical method based on Raman spectroscopy for the quantitative assessment of piperine in black pepper. The study demonstrated the efficacy of the Raman technique for estimating piperine content in the dry fruit of Piper nigrum through vibrational characterisation and Raman prediction analysis.
PHYTOCHEMICAL ANALYSIS
(2022)
Article
Chemistry, Analytical
Dmitry Kirsanov, Subhankar Mukherjee, Souvik Pal, Koustuv Ghosh, Nabarun Bhattacharyya, Rajib Bandyopadhyay, Martin Jendrlin, Aleksandar Radu, Vladimir Zholobenko, Monireh Dehabadi, Andrey Legin
Summary: A simple and cost-effective potentiometric sensor array has been developed using pencils composed of graphite and various zeolites for manual drawing on a polymeric support. This sensor array shows distinct sensitivity towards inorganic ions in aqueous media and has been successfully applied to quantitative analysis of water quality parameters in real-life surface water samples. Partial least squares regression has been used to relate sensor responses to water quality values, demonstrating the array's capability to quantify total hardness, total alkalinity, and calcium content in samples with mean relative errors below 18%.
Article
Engineering, Electrical & Electronic
Barnali Ghatak, Sanjoy Banerjee, Sk Babar Ali, Nityananda Das, Bipan Tudu, Panchanan Pramanik, Soumyo Mukherji, Rajib Bandyopadhyay
Summary: This study presents a portable aroma detection system (Aroma e-Sense) for identifying naturally ripened mangoes, using a DHFIP-QCM sensor to detect important flavonoids. The system demonstrates good repeatability and stability, and has been validated for detecting carbide-treated mangoes.
SENSORS AND ACTUATORS A-PHYSICAL
(2021)
Article
Chemistry, Analytical
Nilava Debabhuti, Sumani Mukherjee, Swarnali Neogi, Prolay Sharma, Ugir Hossain Sk, Soumen Maiti, Mousumi Poddar Sarkar, Bipan Tudu, Nabarun Bhattacharyya, Rajib Bandyopadhyay
Summary: A quartz crystal microbalance (QCM) sensor using olive oil was developed to detect beta-pinene in Indian cardamom, showing high selectivity, low cost, and easy fabrication process.
Proceedings Paper
Computer Science, Artificial Intelligence
Amisha Srivastava, Chao Lu, Navnil Choudhury, Ayush Arunachalam, Kanad Basu
Summary: Quantum computers have shown exponential speedup in tasks like factorization, simulation, and machine learning compared to classical computers. Quantum compilation, the translation of a quantum circuit to adhere to quantum hardware constraints, is a challenging problem. Existing techniques fail to incorporate an optimal solution in the reduced search space, while our proposed PERM and SGO (PAS) strategy achieves a more optimal solution with significant reductions in search space and additional CNOT gates.
PROCEEDINGS OF THE GREAT LAKES SYMPOSIUM ON VLSI 2023, GLSVLSI 2023
(2023)
Article
Chemistry, Multidisciplinary
Sudip Biswas, Hemanta Naskar, Susmita Pradhan, Yuling Chen, Yang Wang, Rajib Bandyopadhyay, Panchanan Pramanik
NEW JOURNAL OF CHEMISTRY
(2020)