Identification of Ruminal Fermentation Curves of Some Legume Forages Using Particle Swarm Optimization
Makaleler > Tam Makale · 2023
Yazarlar: Valiollah PALANGI
Animals, SCI Expanded İndekslerine Giren Dergi, Uluslararası, Wos, 2023, cilt 13, ss 1339-1339
DOI: 10.3390/ani13081339
Özet
The modeling process has a wide range of applications in animal nutrition. The purpose of this work is to determine whether particle swarm optimization (PSO) could be used to explain the fermentation curves of some legume forages. The model suited the fermentation data with minor statistical differences (R2 > 0.98). In addition, reducing the number of iterations enhanced this method’s benefits. Only Models I and II could successfully fit the fermentability data (R2 > 0.98) in the vetch and white clover fermentation curve because the negative parameters (calculated in Models III and IV) were not biologically acceptable. Model IV could only fit the alfalfa fermentation curve, which had higher R values and demonstrated the model’s dependability. In conclusion, it is advised to use PSO to match the fermentation curves. By examining the fermentation curves of feed materials, animal nutritionists can obtain a broader view of what ruminants require in terms of nutrition.