Article
Food Science & Technology
Morad Mousazadeh, Mohammad Mousavi, Zahra Emam-Djomeh, Salar Ali Ahmed, Mehri Hadinezhad, Hamed Hassanzadeh
Summary: Principal component analysis (PCA) was used to investigate the effects of different ingredients on the sensory descriptors of a spread based on pistachio oil. PCA revealed that adhesiveness, hardness, oiliness, and fluidness were the most significant factors. The power law model was found to be more accurate in fitting the samples. The optimum combination of variables (15% pistachio oil, 7.5% cocoa butter, 0.3% xanthan gum, and 1% distilled monoglyceride) produced desirable spreads that mimic commercial spreads.
FOOD SCIENCE & NUTRITION
(2023)
Article
Food Science & Technology
Yuan-Hui Wang, Yue-Ying Yang, Fei Xu, Qi-Dong Zhang, Xiao-Kang Wang, Hang Xu
Summary: Instrumental analysis revealed differences in aroma components of Chinese steamed breads made with traditional sourdoughs from different origins. However, studies on the flavor characteristics of these breads using human olfactory perception are lacking. This study collected eleven Chinese steamed breads made with different traditional sourdoughs to develop a lexicon and a quantitative descriptive analysis (QDA) method for sensory evaluation. The QDA method accurately evaluated the intensities of flavor attributes, and cluster analysis categorized the breads into four groups based on their flavor characteristics.
JOURNAL OF CEREAL SCIENCE
(2023)
Article
Food Science & Technology
J. C. Castura, P. Varela, T. Naes
Summary: This paper proposes an approach for investigating paired comparisons between products and their uncertainties in the principal components using the truncated total bootstrap procedure. Theoretical contributions are provided to justify the proposal. A new matrix operator and a procedure called crossdiff-unfolding are introduced to facilitate the proofs and analysis. The practical advantages of the proposed methods for practitioners are described.
FOOD QUALITY AND PREFERENCE
(2023)
Article
Biochemical Research Methods
Kuangnan Fang, Rui Ren, Qingzhao Zhang, Shuangge Ma
Summary: Dimension reduction techniques like PCA, PLS, and CCA are extensively used in the analysis of high-dimensional omics data. Integrative analysis, which outperforms meta-analysis and individual-data analysis, has been developed for multiple datasets with compatible designs. We developed the R package iSFun to facilitate integrative dimension reduction analysis, offering comprehensive analysis options under different models and penalties.
Article
Food Science & Technology
J. C. Castura, P. Varela, T. Naes
Summary: This study proposes and evaluates numerical and visual methods for analyzing paired comparisons after PCA. These methods provide a screening tool for evaluating PCA results rapidly and can be applied to various data sets from sensory evaluation and other domains.
FOOD QUALITY AND PREFERENCE
(2023)
Article
Food Science & Technology
J. C. Castura, P. Varela, T. Naes
Summary: Principal component analysis (PCA) is commonly used to summarize and explore multivariate data sets, including sensory evaluation data sets. This study proposes a method to conduct PCA on a results matrix where only a subset of paired comparisons is of interest. The proposed approach is illustrated with two data sets from trained sensory panels. The results show that the PCA conducted with the proposed method extracts more variance from the relevant paired comparisons and better separates the relevant pairs compared to conventional PCA.
FOOD QUALITY AND PREFERENCE
(2023)
Article
Computer Science, Artificial Intelligence
Pei Li, Wenlin Zhang, Chengjun Lu, Rui Zhang, Xuelong Li
Summary: A novel robust kernel principal component analysis method with optimal mean (RKPCA-OM) is proposed to enhance the robustness of KPCA by automatically eliminating the optimal mean. The theoretical proof guarantees the convergence of the algorithm and the obtained optimal subspaces and means. Exhaustive experimental results validate the superiority of the proposed method.
Article
Chemistry, Analytical
Xiang Fu, Li-min Zhong, Yong-bing Cao, Hui Chen, Feng Lu
Summary: This article presents a method for identifying drug compositions using Raman spectra, and proposes combining deep learning and non-negative least squares for fast identification of lactose dominated drug formulations. Raman spectroscopy remains a cost-effective, rapid, and user-friendly method for this purpose.
ANALYTICAL METHODS
(2021)
Article
Chemistry, Applied
Jizhong Wu, Qin Ouyang, Bosoon Park, Rui Kang, Zhen Wang, Li Wang, Quansheng Chen
Summary: The study proposed a PCA comprehensive evaluation model based on selected key physicochemical indicators to assess the sensory quality of matcha. The results showed that the model achieved superior performance with high correlation coefficients in both calibration and prediction sets for overall sensory quality. This work demonstrated the potential of LASSO-PCA comprehensive evaluation as an objective protocol for predicting matcha sensory quality.
Article
Agricultural Engineering
Zhichao Deng, Ao Xia, Yun Huang, Xianqing Zhu, Xun Zhu, Qiang Liao
Summary: This study investigated the relationship between the physicochemical properties and enzymatic hydrolyzability of hydrothermal pretreated lignocellulose through correlation analysis and principal component analysis. The results showed that cellulose content was the major factor affecting carbohydrate conversion, and the initial hydrolysis rate and carbohydrate conversion could be well predicted using principal component analysis.
BIORESOURCE TECHNOLOGY
(2022)
Article
Food Science & Technology
Yaqi Zhao, Yingyu Zeng, Xusheng Li, Kailan Yuan, Yue Li, Lingmin Tian, Jianxia Sun, Weibin Bai
Summary: In this study, a comprehensive quality evaluation method for blueberry wine was established by analyzing eleven physicochemical indexes. Principal component analysis showed that the first three principal components accounted for 85.73% of the total quality variability. The consistent ranking between the quality evaluation model and sensory evaluation test verified the reliability of the model. Additionally, ultrasonic treatment of blueberry wine resulted in higher scores, indicating changes in sensory quality with high sensitivity. This study provides a theoretical basis for the comprehensive quality evaluation of blueberry wines and guidance for consumer choices.
CURRENT RESEARCH IN FOOD SCIENCE
(2023)
Article
Agriculture, Dairy & Animal Science
Ripudaman Singh, Kaushik Khamrui, Writdhama Prasad, Bhopal Singh, Ritika Puri
Summary: Consumption of vegetarian pizza is on the rise worldwide due to the increasing popularity of vegetarian diets, yet a proper description of its sensory attributes is lacking in the existing scientific literature. This study objectively characterized the sensory attributes of vegetarian pizza using statistical tools, identifying five principal components that explained 93% of the variation in sensory data. These findings provide valuable information for product evaluation and process improvement.
INDIAN JOURNAL OF DAIRY SCIENCE
(2021)
Article
Spectroscopy
Syeda Shafaq, Muhammad Irfan Majeed, Haq Nawaz, Nosheen Rashid, Maria Akram, Nimra Yaqoob, Ayesha Tariq, Samra Shakeel, Anwar ul Haq, Mudassar Saleem, Muhammad Zaman Nawaz, Rana Zaki Abdul Bari
Summary: Raman spectroscopy has been investigated for its potential in analyzing solid dosage forms of Losartan potassium in the pharmaceutical field. The spectral data showed a gradual change in Raman spectral features associated with the active pharmaceutical ingredient (API) of Losartan potassium as the concentration changed. Principal Component Analysis (PCA) was used for classification, and Partial Least Square Regression (PLSR) analysis was performed for quantitative analysis. The results demonstrated that Raman spectroscopy can be used for quick and reliable quantitative analysis of pharmaceutical solids.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2022)
Article
Chemistry, Analytical
Hao Cao, Youlin Gu, Jiajie Fang, Yihua Hu, Wanying Ding, Haihao He, Guolong Chen
Summary: This study proposes a rapid nondestructive detection method for the activity of biomaterials based on infrared spectroscopy. It uses a stacking ensemble learning model to accurately detect the activity ratio of biomaterials by analyzing the infrared absorption peaks and changes in surface functional groups. The results show that the stacking ensemble learning model has high prediction accuracy and generalization ability.
MICROCHEMICAL JOURNAL
(2022)
Article
Agriculture, Multidisciplinary
Adriana Muniz, Xiaofen Du, Marcus Shanks
Summary: The study found that mushrooms can enhance the sensory quality of roasted and steamed egg whites by introducing characteristic sensory attributes from mushrooms. Mushroom variety and proportion with egg whites have significant impacts on egg white sensory properties. The research contributes to understanding the impact of mushrooms on egg white sensory profile and serves as a guide in incorporating mushrooms in product development.
JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE
(2022)
Article
Food Science & Technology
Sara de Fraga Silva, Daiane Einhardt Blank, Carlos Roberto Peixoto, Jane de Jesus da Silveira Moreira, Neusa Fernandes de Moura
INTERNATIONAL JOURNAL OF FOOD PROPERTIES
(2016)
Article
Chemistry, Multidisciplinary
Deyvid. G. M. Oliveira, Clarissa H. Rosa, Bruna P. Vargas, Diego S. Rosa, Marcia V. Silveira, Neusa F. de Moura, Gilber R. Rosa
JOURNAL OF CHEMICAL EDUCATION
(2015)
Article
Chemistry, Multidisciplinary
Diego S. Rosa, Francine Antelo, Toni J. Lopes, Neusa F. de Moura, Gilber R. Rosa
Article
Chemistry, Analytical
Carlos Roberto de Menezes Peixoto, Sara Fraga, Juliano da Rosa Justim, Mariana Silva Gomes, Debora Goncalves Carvalho, Joao Andre Jarenkow, Neusa Fernandes de Moura
JOURNAL OF ELECTROANALYTICAL CHEMISTRY
(2017)
Article
Chemistry, Applied
Juliano Antonio Sebben, Juliana da Silveira Espindola, Lucas Ranzan, Neusa Fernandes de Moura, Luciane Ferreira Trierweiler, Jorge Otavio Trierweiler
Article
Engineering, Chemical
Daiane Einhardt Blank, Mariana Bellaver, Sara Fraga, Toni Jefferson Lopes, Neusa Fernandes de Moura
JOURNAL OF FOOD PROCESS ENGINEERING
(2018)
Article
Biochemistry & Molecular Biology
Desiree Magalhaes dos Santos, Camila Valesca Jardim Rocha, Elita Ferreira da Silveira, Marcelo Augusto Germani Marinho, Marisa Raquel Rodrigues, Nichole Osti Silva, Ailton da Silva Ferreira, Neusa Fernandes de Moura, Gabriel Jorge Sagrera Darelli, Elizandra Braganhol, Ana Paula Horn, Vania Rodrigues de Lima
JOURNAL OF MEMBRANE BIOLOGY
(2018)
Article
Chemistry, Medicinal
A. Dal Piva, R. Ferronato, A. Flach, L. A. M. A. da Costa, D. Cabrera, G. R. Rosa, N. F. de Moura
CHEMISTRY OF NATURAL COMPOUNDS
(2014)
Article
Chemistry, Multidisciplinary
Caroline E. Mendes, Adriana Flach, Luiz A. M. A. da Costa, Rosiane B. N. Denardin, Neusa F. de Moura
JOURNAL OF THE BRAZILIAN CHEMICAL SOCIETY
(2014)
Article
Chemistry, Applied
D. C. Cabrera, G. L. S. Gomes, A. Flach, L. A. M. A. da Costa, G. R. Rosa, N. F. de Moura
NATURAL PRODUCT RESEARCH
(2015)
Article
Biology
M. Teixeira, T. Altmayer, F. Bruxel, C. R. Orlandi, N. F. de Moura, C. N. Afonso, E. M. Ethur, L. Hoehne, E. M. de Freitas
BRAZILIAN JOURNAL OF BIOLOGY
(2019)
Article
Food Science & Technology
Zabelita Fardin Folharini, Carla Roberta Orlandi, Maira Cristina Martini, Fernanda Bruxel, Tacielen Altmayer, Debora Tairini Brietzke, Tamara Engelmann Goncalves, Jordana Finatto, Eduardo Miranda Ethur, Neusa Fernandes de Moura, Lucelia Hoehne, Elisete Maria de Freitas
FOOD SCIENCE AND TECHNOLOGY
(2019)
Article
Chemistry, Applied
Debora Goncalves Carvalho, Juliano Antonio Sebben, Neusa Fernandes de Moura, Jorge Otavio Trierweiler, Juliana da Silveira Espindola
Article
Biochemistry & Molecular Biology
Matheus H. O. de Sousa, Jessica M. S. Morgan, Karina Cesca, Adriana Flach, Neusa F. de Moura
CHEMISTRY & BIODIVERSITY
(2020)
Article
Biochemistry & Molecular Biology
Christchellyn Klegin, Neusa Fernandes de Moura, Matheus Henrique Oliveira de Sousa, Rafaele Frassini, Mariana Roesch-Ely, Alessandra Nejar Bruno, Thais Cardoso Bitencourt, Adriana Flach, Jucara Bordin
Summary: The study aimed to determine the chemical composition and biological activity of the essential oil from Phyllogonium viride Brid., with major compounds found being beta-bazzanene, beta-caryophyllene, beta-chamigrene, and germacrene B. Treatment with the essential oil did not induce toxicity in most tested cell lines. The data contributes to new scientific information about this plant species and its biotechnological potential.
CHEMISTRY & BIODIVERSITY
(2021)
