Can Grassland Chemical Quality Be Quantified Using Transform Near-Infrared Spectroscopy?

NIRS botanical composition forage quality meadows quantification

Journal

Animals : an open access journal from MDPI
ISSN: 2076-2615
Titre abrégé: Animals (Basel)
Pays: Switzerland
ID NLM: 101635614

Informations de publication

Date de publication:
31 Dec 2021
Historique:
received: 09 11 2021
revised: 18 12 2021
accepted: 21 12 2021
entrez: 11 1 2022
pubmed: 12 1 2022
medline: 12 1 2022
Statut: epublish

Résumé

Near-infrared spectroscopy (NIRS) and closed spectroscopy methods have been applied to analyse the quality of forage and animal feed. However, grasslands are linked to variability factors (e.g., site, year, occurring species, etc.) which restrict the prediction capacity of the NIRS. The aim of this study is to test the Fourier transform NIRS application in order to determine the chemical characteristics of fresh, undried and unground samples of grassland located in north-central Apennine. The results indicated the success of FT-NIRS models for dry matter (DM), crude protein (CP), acid detergent fibre (ADF), neutral detergent fibre (NDF) and acid detergent lignin (ADL) on fresh grassland samples (R2 > 0.90, in validation). The model can be used to quantitatively determine CP and ADF (residual prediction deviation-RPD > 3 and range error ratio- RER > 10), followed by DM and NDF that maintain a RER > 10, and are sufficient for screening for the lignin fraction (RPD = 2.4 and RER = 8.8). On the contrary, models for both lipid and ash seem not to be usable at a practical level. The success of FT-NIRS quantification for the main chemical parameters is promising from the practical point of view considering both the absence of samples preparation and the importance of these parameters for diet formulation.

Identifiants

pubmed: 35011192
pii: ani12010086
doi: 10.3390/ani12010086
pmc: PMC8749596
pii:
doi:

Types de publication

Journal Article

Langues

eng

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Auteurs

Silvia Parrini (S)

Department of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence, 50144 Florence, Italy.

Nicolina Staglianò (N)

Department of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence, 50144 Florence, Italy.

Riccardo Bozzi (R)

Department of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence, 50144 Florence, Italy.

Giovanni Argenti (G)

Department of Agriculture, Food, Environment and Forestry (DAGRI), University of Florence, 50144 Florence, Italy.

Classifications MeSH