PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
February 12, 20260 citationsOpen Access

Nutzbarkeit von NIRS zur TS- und Proteingehaltserfassung bei frischem Luzernegras

APAnna Hilda PrasunFBFrank Beneke

Key Points

  • Assess the effectiveness of near-infrared spectroscopy (NIRS) for analyzing protein content and dry matter in fresh alfalfa grass.
  • Tested NIRS models on two alfalfa-grass sites in Germany
  • Compared NIRS results with Dumas-analysis for protein content
  • Measured dry matter using laboratory techniques
  • NIRS provided good dry matter results with RMSE up to 2% DM
  • Failed to create distinct DM zones due to insufficient heterogeneity
  • R² for NIRS protein predictions against Dumas reached a maximum of 0.346, underestimating protein content

Abstract

Livestock wellbeing and output are dependent on the feed and its composition. But yields as well as product quality are varying because of heterogenous sites. Therefore, it is favorable to know quality parameters of forage. Near-infrared spectroscopy (NIRS) is a cost-effective and fast analysis method. It is already available for different scopes in agriculture, but there is a lack for fresh, not wilted material e.g., on grazing land. In 2024, NIRS models of the VDLUFA were tested on two alfalfa-grass sites near Kassel, Germany, in comparison with Dumas-analysis for protein content and laboratory DM (dry matter) measurement. NIRS achieved good results for DM with RMSE up to 2 % DM, but there was no sufficient heterogeneity and correlation to divide the field into DM-zones. Protein contents differed much more within the field, but the R² of NIRS compared to Dumas only reached a maximum of 0.346 and very much underestimated the protein content.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Prasun et al. (2026) studied this question.

synapsesocial.com/papers/698d6e3c5be6419ac0d53bfehttps://doi.org/10.18420/giljt2026_51
Ask AI
Helpful
Bookmark
Share
View Full Paper