Investigation of Methods to Enhance the Efficiency of Canola Meal Use in Pelleted Calf Starter Mixtures and Comparisons with Other High-Protein by-Products*
Notice bibliographique
Résumé
Abstract It was hypothesized that the efficiency of canola meal (CM; also known as 00 rapeseed meal) utilization in pelleted starter mixtures for calves can be increased with the use of feed additives and additional processing. Additionally, it was hypothesized that CM would yield greater feed intake, growth, and improved fecal scores compared to wheat bran and DDGS when included as a high-protein by-product in a pelleted starter mixture. In order to verify the hypotheses, four studies were conducted to determine whether lysine (Lys) inclusion, feed enzyme inclusion, and CM extrusion improve the efficiency of CM utilization in pelleted calf starter mixtures, and to compare effects of CM to that when other high-protein by-products are fed. In study 1, 45 female Holstein calves (44.7±4.2 kg, 24.2±2.8 days of age) were allocated to one of three treatments and fed a pelleted starter mixture containing: 1) soybean meal (SBM) as the main source of protein (TSBM); 2) CM as the main source of protein (TCM); or 3) CM as the main source of protein with supplemental rumen-unprotected Lys (TCML). Final body weight (BW), average daily gain (ADG), starter intake, and fecal score did not differ among treatments (P≥0.20) but the gain to feed ratio was greater for TSBM than for TCM and TCML (P<0.01). No differences between TCM and TCML were found. In study 2, 100 female Holstein calves (44.3±4.8 kg, 17.7±2.1 days of age) were assigned to one of four treatments and fed pelleted starter mixtures with: 1) low CM inclusion (10%; LOW); 2) low CM inclusion supplemented with feed enzymes (xylanase, glucanase, invertase, protease, cellulase, amylase, and mannanase; LOW+); 3) high CM inclusion (32%; HIGH); and 4) high CM inclusion supplemented with the same feed enzymes (HIGH+) as for LOW+. In treatments that included feed enzymes, final BW, ADG, and starter intake were greater while the number of days with diarrhea was lower (P≤0.05). The number of days with diarrhea was also lower for high CM treatments (P<0.01). In study 3, 120 female Holstein calves (42.6±4.4 kg, 17.2±2.1 days of age) were allocated to one of four treatments and fed a pelleted starter mixture: 1) containing SBM as a main source of protein (CTRL), or diets where: 2) SBM was partially replaced by wheat bran and corn DDGS (TRBP); 3) SBM was partially replaced by CM (TRCM); and 4) SBM was partially replaced by CM with feed enzymes (the same used in study 2; TRCM+). Feed intake and the gain to feed ratio did not differ among treatments. Final BW tended (P=0.10) to be higher for CTRL than for TRBP and TRCM, but the CTRL group had a higher fecal score, a greater number of days with diarrhea, and more episodes of diarrhea compared to TRBP and TRCM (P≤0.05). No differences between TRCM and TRCM+ were detected. In study 4, 120 female Holstein calves (44.1±4.9 kg, 18.3±1.9 days of age) were allocated to one of four treatments and fed a pelleted starter mixture with: 1) moderate CM inclusion (24%; MC); 2) high CM inclusion (34%; HC); 3) moderate inclusion of extruded CM (MEC); and 4) high inclusion of extruded CM (HEC). Fecal score tended to be (P=0.10) and the number of days with diarrhea was (P<0.01) reduced when extruded CM was used in the starter mixture but BW, ADG, and the gain to feed ratio were not different among treatments. In conclusion, rumen-unprotected lysine supplementation in a pelleted starter mixture containing CM as the main source of protein does not improve the performance of calves although inclusion of enzymes may improve feed intake and ADG of calves. Extrusion of CM improves fecal score of calves but does not affect feed intake or growth. Canola meal should be considered at least as valuable source of protein as wheat bran and DDGS.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».