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It is of paramount importance in plant breeding to have methods dealing with large numbers of predictor variables and few sample observations, as well as efficient methods for dealing with high correlation in predictors and measured traits. This paper explores in terms of prediction performance the partial least squares (PLS) method under single-trait (ST) and multi-trait (MT) prediction of potato traits. The first prediction was for tested lines in tested environments under a five-fold cross-validation (5FCV) strategy and the second prediction was for tested lines in untested environments (herein denoted as leave one environment out cross validation, LOEO). There was a good performance in terms of predictions (with accuracy mostly > 0.5 for Pearson's correlation) the accuracy of 5FCV was better than LOEO. Hence, we have empirical evidence that the ST and MT PLS framework is a very valuable tool for prediction in the context of potato breeding data.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10279678 | PMC |
http://dx.doi.org/10.1038/s41598-023-37169-y | DOI Listing |
BMC Chem
December 2024
Pharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Cairo University, Cairo, Egypt.
A simple and green chemometrics-assisted spectrophotometric technique has beendeveloped and validated for the determination of antipyrine (ANT) and benzocaine HCl (BEN) along with the official impurity of ANT, antipyrine impurity A (ANT imp-A), and the degradation product of BEN, p-amino benzoic acid (PABA), in their quaternary mixture. Three models were developed and compared: partial least squares (PLS), artificial neural networks (ANN), and multivariate curve resolution-alternating least squares (MCR-ALS) where the four studied drugs were successfully quantified. The quantitative determination of the studied drugs was assessed using percentage recoveries, standard errors of prediction, and root mean square errors of prediction.
View Article and Find Full Text PDFSpectrochim Acta A Mol Biomol Spectrosc
December 2024
Department of Food Engineering, School of Food Engineering, University of Campinas, Campinas, SP, Brazil. Electronic address:
The unique fatty acid composition of BSF larvae oil makes it suitable for various applications, including use in animal feed, aquaculture, biodiesel production, biomaterials, and the food industry. Determination of BSF larvae composition usually requires analytical methods with chemicals, thus needing emerging techniques for fast characterization of its composition. In this study, Near Infrared Hyperspectral Imaging (NIR-HSI) (928 - 2524 nm) coupled with chemometrics was applied to predict the lipid content and fatty acid composition in intact black soldier fly (BSF) larvae.
View Article and Find Full Text PDFAnn Surg
December 2024
Department of Urology, University of Michigan, Ann Arbor, MI.
Objective: To assess the burden of ergonomic strain and to examine factors influencing intention to use wearable technology that may improve ergonomics during surgery.
Background: Surgical ergonomic strain leads to high rates of work-related musculoskeletal disorders (MSDs) and pain, contributing to early surgeon retirement and an epidemic of burnout.
Methods: A cross-sectional survey of surgeons at a single institution was conducted using two validated instruments, the Nordic Musculoskeletal Questionnaire and Unified Theory of Acceptance and Use of Technology (UTAUT2), assessing musculoskeletal strain and facilitators of wearable sensor use, respectively.
Front Plant Sci
December 2024
National Navel Orange Engineering Research Center, School of Life Sciences, Gannan Normal University, Ganzhou, China.
Gannan is the largest navel orange production area in China. Most studies have primarily focused on the effects of either soil or topographic factors on the quality of navel oranges. However, there has been a lack of research exploring the relationship between navel orange quality and multiple environmental factors (meteorological, topographic, and soil).
View Article and Find Full Text PDFFront Nutr
December 2024
Key Laboratory of Geriatric Nutrition and Health, Ministry of Education (Beijing Technology and Business University), Beijing, China.
Pea ( L.) is a nutrient-dense legume whose nutritional indicators influence its functional qualities. Traditional methods to identify these components and examine the relationships between their contents could be more laborious, hindering the quality assessment of the varieties of peas.
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