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Study on the NIR Spectroscopy to Predict Energy Content of Hemp Flour (Cannabis sativa L.)

Academic Article
Publication Date:
2024
abstract:
Aims: The aim of this study was to evaluate the utility of NIRSfor predicting the energy content through the chemical characterization of the flour obtained after the cold pressing of Cannabis sativaL. seeds, as well as the possibility of predicting their energy content starting from the data obtained through the NIRs technique.Study Design:The chemical composition of 56 hemp flour samples was determined following the official protocols of the Association of Analytical Chemists and chemometric readings were conducted. GE, gross energy digestibility (GEd) and digestible energy (DE) were estimated using the equations proposed by INRA. A statistical analysis was performed to evaluate the potential use of NIR data to predict the energy content of hemp flour. Results:Data from laboratory and NIR assessments were 22.54 versus 20.44 for GE (MJ/kg DM), 90.72 versus 90.21 for GEd (MJ/kg DM), and 19.73 versus 20.13, respectively for the loss (%). The results indicated the feasibility of energy value prediction, although further studies are needed to refine the technique. NIR expands the calibration set, allowing increasingly accurate determinations, in the study of the chemical-nutritional characteristics of hemp sativa, even if further investigations are necessary.Conclusion:The study provides comprehensive insights into the chemical composition of hemp flour, explores its comparison with other seeds, evaluates different analysis methods, and establishes reliable prediction models for energy content.
Iris type:
01.01 Articolo in rivista
Keywords:
Gross energy; gross energy digestibility; digestible energy; hemp flour; near-infrared spectroscopy
List of contributors:
Auriemma, Giuseppe; Grazioli, Giuseppe; Pappalardo, Raffaele; Sarubbi, Fiorella
Authors of the University:
AURIEMMA GIUSEPPE
GRAZIOLI GIUSEPPE
PAPPALARDO RAFFAELE
SARUBBI FIORELLA
Handle:
https://iris.cnr.it/handle/20.500.14243/454761
Published in:
BRITISH JOURNAL OF APPLIED SCIENCE AND TECHNOLOGY
Journal
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URL

https://journalcjast.com/index.php/CJAST/article/view/4345/8650
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