Nürtingen, FH, Diplomarb., 2004. / Betreuer: Gerhard Schwarting.

No description available.

Não consta resumo na publicação. / Abstract not available.

Freie Universiẗat, Diss., 2005--Berlin. / Dateiformat: zip, Dateien im PDF-Format. Erscheinungsjahr an der Haupttitelstelle: 2005.

Zugl.: Hohenheim, Univ., Diss., 2009

The effects of feeding Master Graze (MG) on dairy cows productivity and nutrient digestibility were evaluated in experiment 1. Sixteen cows were divided into 4 groups and fed treatment diets for 4 consecutive periods. Cows on the control diet were fed a diet with corn silage and alfalfa hay as forage source (1:1; DM basis). For treatment groups, the MG substituted the forage mix at 16, 33 and 50%. The feeding of MG at the three tested levels had no effects on feed intake, milk production or milk composition. The apparent digestibility of DM, OM, NDF and CP were higher in cows fed the MG. In experiment 2, the effects of maturity and preservation method on MG nutrient composition and digestibility were evaluated. The MG was harvested at 3 maturity levels and then preserved using oven-dried, ensiled, or freeze dried. In general, the MG digestibility and nutritional quality was higher in the first cut and with the freeze dried preservation method.

Não consta resumo na publicação. / Abstract not available.

No description available.

Current feeding strategies aim to maximize efficiency at the pen level. However, feed intake varies across animals and in response to diet composition, making it difficult to capture these variations and control feeding effectively. A precision feeding system is required to feed animals individually, continuously monitor responses, and make timely adjustments to feed tailoring. Such a system would efficiently integrate dairy operations to enhance profitability and reduce their environmental footprint. Thus, the objectives of this dissertation were to build, test, and apply a precision feeding system able to tailor feeding strategies to animals more precisely and closely match their individual requirements. In Chapter 3, we describe the precision feeding system framework using directional data streams. The system integrates real-time farm data, segmented into data-analytic modules for independent testing and troubleshooting. It provides feeding instructions to automatic feeders and generates animal and financial monitoring reports. In Chapter 4, we describe the "Animal Performance" system module. This study developed a predictive model to estimate individual dry matter intake (DMI) by integrating markers, animal characteristics, dietary nutrient concentrations, and chewing sensor data. The performance of the developed model was then assessed and contrasted with the NASEM (2021) DMI equations. By incorporating covariates derived from short-term use of external and internal markers we demonstrated a greater accuracy of DMI predictions when using a fixed effects model, supporting its predictive capabilities for further application. In Chapter 5, we describe the "Diet Optimization" systems module, used to maximize profit by optimizing rations using a developed compact-vectorized version of NASEM (2021). The study aimed to simulate optimized diets, evaluate the economic impact of feeding individual diet, compare feed costs and income over feed cost (IOFC) for optimized group diet, and compare optimized diets against pen-averages (PEN). The results showed that IND diets had lower costs, higher milk production, and increased IOFC compared to CLU diets. Additionally, both IND and CLU diets outperformed PEN solutions. This work established methods for deriving efficient diet solutions for individual animals and using clustering techniques for more precise pen-level feeding. In Chapter 6, we describe the application of "Animal Performance", "Diet Optimization", and "Nutrient Titration" system modules. The former DMI model described in Chapter 4 was applied to the experimental data. The middle utilized optimized diets generated by the optimizer developed in Chapter 5, with additional algorithm updates. The latter aimed to investigate individual milk true protein production responses of dairy cows to varying levels of metabolizable protein (MP) and rumen-protected amino acids (RPAA) using automatic feeding systems and rank animals based on their individual gross milk protein efficiencies. Results demonstrated heterogeneous animal responses across MP and RPAA levels, ranging from linear, and quadratic to no response, emphasizing the necessity of addressing individual variability within a common pen. High-efficiency animals behaved consistently across MP treatments with lower variability, while low-efficiency animals showed high variability but consistently remained in the bottom efficiency rank. In conclusion, the precision feeding system underscores true capabilities to tailor nutrient delivery to individual cows, maximizing economic and environmental benefits, and sets the stage for future research focused on further refinement and automation of these technologies / Doctor of Philosophy / Feeding practices for dairy cattle have evolved significantly from manual grain mix offering to group feeding. While pen-level feeding has its benefits, it overlooks opportunities to maximize efficiency and minimize feed waste and nutrient excretion by not using individual animal variation to apply control feeding. With modern farms and increased technology adoption, feeding animals while being individually milked, even when group-housed, is now possible, leveraging this variability to apply precision feeding. In Chapter 3, we described the development of a precision feeding system that leverages technological advancements on dairy farms to gather and analyze data, supporting informed decision-making. This system includes various modules for testing and adjusting feeding strategies according to animal needs, providing feeding instructions to automatic feeders, and generating reports to help farmers monitor their animals and manage costs. Recognizing that precision feeding relies on quality data and accurate predictions of crucial metrics such as dry matter intake (DMI), Chapter 4 focused on developing a mathematical equation to predict DMI on an individual animal basis. This model demonstrated potential for commercial dairy operations due to its use of readily available farm-level predictors and its adequate performance compared to gold-standard field equations. Given the lack of efficient optimizers that incorporate individual animal data, in Chapter 5, we described the development of a new optimizer incorporated into the system to maximize profits. We simulated different feeding strategies, including optimized individual and group diets, and demonstrated that these tailored diets were more cost-effective and led to higher milk production compared to pen-average diets. To complete the development, testing, and application cycle, in Chapter 6, we applied the precision feeding system to determine the metabolizable protein (MP) requirements of dairy cows and assess milk protein production responses to different levels of MP and rumen-protected amino acids (RPAA). The results indicated varied responses among cows, highlighting the importance of individualized feeding to account for animal-to-animal differences within the same pen. Top-efficient animals were consistent in their responses across treatments, whereas bottom-efficient animals exhibited greater variability and consistently underperformed. In conclusion, the precision feeding system demonstrated significant potential to improve the efficiency of dairy farming by more accurately meeting the specific needs of dairy cattle. Future research will focus on refining this system and further automating the process for broader farm applications.

Le système INRA d’alimentation des Ruminants prédit les réponses de l’animal à des variations d’apports d’aliments ingérés. Toutefois, il évalue mal l’influence de l’alimentation sur la qualité des productions, et en particulier la qualité de la carcasse de bovins dont dépend le paiement des animaux aux producteurs. Pour un type d’animal donné, les poids et composition de la carcasse en lipides et protéines sont prédits par le modèle MECSIC (Hoch et Agabriel, 2004) à partir de l’énergie métabolisable ingérée calculée selon le système INRA de valeur énergétique des aliments et des rations. Or une étude bibliographique suggère que la composition des dépôts dépend aussi pour partie de la composition des rations qui détermine la nature des produits terminaux issus de la digestion des rations et le devenir métabolique des nutriments. Pour tester cette hypothèse, l’objectif fut d’étudier l’effet de la nature de la ration à même quantité énergie métabolisable (EM) ingérée sur la composition des dépôts et de la carcasse. Cet objectif est ciblé sur les bovins mâles en croissance. Les étapes principales de la thèse ont consisté à i) construire une base des données à partir des publications internationales traitant des effets de la variation des rations ingérées sur la composition de la carcasse chez les jeunes bovins, ii) explorer les relations entre la composition de la carcasse et la composition de la ration et sa métabolisabilité. La constitution de la base de données a montré que la composition de la carcasse n’est mesurée que dans 20% des publications, les 80% restantes l’ayant évalué par des mesures indirectes (index USA de rendement de viande, épaisseur de gras sous cutané, persillé, surface de muscle…) qui ne sont pas reliées entre elles. Une étape de recherche préliminaire a été mise en place pour quantifier par méta-analyse les relations entre mesures directes et indirectes de la composition de la carcasse dans le but d’utiliser le maximum de publications pour la suite de la thèse. Nous avons montré que seuls deux indicateurs (index USA de rendement de viande et épaisseur de gras sous-cutané) reflètent correctement la composition de la carcasse et peuvent être utilisés pour établir les lois de variation de sa qualité selon les conditions d’alimentation. Une autre méta-analyse a permis d’explorer à niveaux d’ingestion d’EM similaires, les réponses marginales des dépôts de lipides et protéines dans la carcasse, à des variations strictes de teneurs de la ration en EE, PDI, NDF ou du rapport Amidon/NDF, tout en considérant sa métabolisabilité (q=EM/EB). L’accroissement du rapport Amidon/NDF augmente la teneur en lipides des carcasses mais en deçà d’un seuil de métabolisabilité de la ration de 0,65, i.e. si les rations ont plus de 36% de fourrages. Au-delà de ce seuil, qui correspond à un rapport Amidon/ NDF minimal voisin de 2, il n’y a plus d’effet. Ainsi à même EMI, la composition du gain (et donc l’énergie nette déposée) ne varierait pas linéairement avec la métabolisabilité q de la ration. De plus la teneur en PDI augmente significativement la proportion de lipides de la carcasse (et réduit celle des protéines), surtout si le niveau global d’apports de PDI est limité et ne dépasse pas 2,5 fois les besoins d’entretien en PDI. La teneur en EE a peu d’effets. Ces caractéristiques de ration conduisent à des profils de nutriments (rapport entre nutriments glucogéniques et cétogéniques, azote-alpha-aminé) qui sont aussi discriminants pour la composition de la carcasse. Nos résultats suggèrent qu’il faut considérer les effets de la nature de la ration dans la modélisation de la composition de la carcasse des bovins selon l’EM ingérée. Cela pourra faire l’objet d’une modification significative du modèle de croissance (MECSIC) pour améliorer son pouvoir prédictif. / The INRA feeding system for Ruminants predicts the animal's responses to changes in feed intake. However, it poorly evaluates the influence of feed intake on the quality of productions, and in particular the quality of bovine carcass, on which the payment of animals to the producers depends. For a given type of animal, the carcass weight and its composition in lipids and proteins are predicted by the MECSIC model (Hoch and Agabriel, 2004) from the intake of metabolizable energy calculated from the INRA energy system. However, a literature review suggests that the composition of the depots also partly depends on the composition of the rations, which determines the nature of the digestion end products, and the metabolic fate of the nutrients. To test this hypothesis, the objective was to study the effects of the nature of the ration at similar metabolizable energy intake (MEI) on the composition of the carcass. This study is targeted to growing male cattle. The main steps of the thesis consisted of (i) building a database based on international publications on the effects of dietary intake on carcass composition in young cattle, (ii) exploring the relationships between carcass composition and the composition and metabolisability of the ration. The database showed that the composition of the carcass was measured in only 20% of the publications; the remaining 80% evaluated it by indirect measurements (USA yield grade, fat thickness, marbling, ribeye area ...). A preliminary research step was developed to quantify by meta-analysis the relationships between direct and indirect measurements of carcass composition in order to use the maximum number of publications for the rest of the thesis. We have shown that only two indicators (USA yield grade and fat thickness) correctly reflect the composition of the carcass and can be used to establish the response equations of carcass quality to dietary conditions. Another meta-analysis explored the marginal responses of lipid and protein depots in the carcass to strict variations in the dietary concentrations of EE, PDI, NDF or of the starch / NDF ratio, while considering its metabolisability (q = EM / EB). An increase in the starch / NDF ratio increases the lipid content of the carcasses but below a metabolizability threshold of 0.65, i.e. when rations contain more than 36% fodder. Beyond this threshold, which corresponds to a minimum starch / NDF ratio close to 2, there is no longer any effect. Thus, at similar MEI, the composition of the gain (and therefore the net energy deposited) does not vary linearly with the metabolisability q of the diet. Furthermore, the PDI content significantly increases the proportion of carcass lipids (and reduces that of proteins), especially if the overall level of PDI intake is limited and does not exceed 2.5 fold the maintenance requirements in PDI. The dietary EE content has little effect. These diet characteristics result in nutrient profiles (glucogenic / ketogenic ration, alpha-amino-N) which also discriminate carcass composition. Our results suggest that the effects of the nature of the ration should be considered when modeling the carcass composition of bovine animals from MEI. This should lead to significant changes in the MECSIC growth model to improve its predictive power.