A glimpse of the future in animal nutrition science. 1. Past and future challenges

ABSTRACT If the world population continues to increase exponentially, wealth and education inequalities might become more pronounced in the developing world. Thus, offering affordable, high-quality protein food to people will become more important and daunting than ever. Past and future challenges will increasingly demand quicker and more innovative and efficient solutions. Animal scientists around the globe currently face many challenging issues: from ensuring food security to prevent excess of nutrient intake by humans, from animal welfare to working with genetic-engineered animals, from carbon footprint to water footprint, and from improved animal nutrition to altering the rumen microbiome. Many of these issues are most likely to continue (or to exacerbate further) in the coming years, but animal scientists have many options to surmount the obstacles posed to the livestock industry through tools that are presently available. The frequency, interval, and intensity of livestock impacts, however, differ across regions, production systems, and among livestock species. These differences are such that the generalization of these issues is impossible and dangerous. For instance, when we discuss domesticated ruminant nutrition in the human food context, we look for the most efficient ruminant feeds that complement, rather than compete with, grains grown for direct human nutrition. Greater scrutiny and standardization are needed when developing and validating methodologies to assess short- and long-term impacts of livestock production. Failure in correctly quantifying these impacts may lead to disregard and disbelief by the livestock industry, increased public confusion, and the development of illusionary solutions that may amplify the impacts, thereby invalidating its original intent

Nutritional requirements of Nelore cows and calves, from birth to weaning

O experimento foi conduzido com o objetivo de determinar as exigências nutricionais (energia, proteína e macrominerais) de vacas de corte em lactação e de suas respectivas crias do nascimento aos seis meses de idade. Foram utilizados 40 animais Nelore, sendo 20 vacas e 20 bezerros, com pesos médios iniciais de 362 ± 25 e 30 ± 3kg, respectivamente. Os bezerros foram alimentados individualmente por períodos de 90 a 180 dias após o parto das vacas. As vacas foram divididas em mantença (4) e desempenho (12) até os 90 dias e igualmente dos 90 aos 180 dias pós-parto. Os bezerros foram distribuídos em 90 e 180 dias, sem a restrição alimentar. Foram utilizados oito animais como referência (quatro vacas e quatro bezerros). A dieta foi composta por silagem de milho (SM) e concentrado, com relação volumoso:concentrado de 70:30 para as vacas, sendo a SM fornecida ad libitum juntamente com 0,5 kg/dia de concentrado para os bezerros. Os consumos de matéria seca e dos nutrientes foram calculados semanalmente a partir da análise laboratorial dos alimentos fornecidos e das sobras. A produção de leite foi determinada semanalmente pelo método de pesagem dos bezerros antes e após a mamada. Ensaios de digestibilidade foram feitos a cada período de 28 dias (vacas) e outros dois para os bezerros. A excreção fecal foi determinada utilizando a fibra em detergente neutro indigestível (FDNi) como indicador. Pesagens dos animais foram efetuadas a cada 28 dias. Foi realizada ordenha manual a cada período de 28 dias para mensuração dos teores de gordura, proteína e lactose do leite. A concentração de energia expressa em NDT foi calculada a partir das disgestibilidades dos nutrientes. A concentração de energia digestível foi obtida pela equação ED (Mcal/Kg) = 5,65 x PBD + 9,39 x EED + 4,15 x FDND + 4,15 CNFD. Os conteúdos corporais de proteína, energia e minerais foram estimados pelo equação Y = a . Xb, sendo X o peso de corpo vazio (PCVZ) e a e b os parâmetros da equação alométrica. Foram obtidas ix relações médias de 0,894 para PCVZ/PC e de 0,936 para GPCVZ/GPC das vacas e 0,9622 e 0,958 para PVCZ/PC e GPCVZ/GPC, para os bezerros, respectivamente. As exigências líquidas de energia para mantença das vacas (ELm) foram de 97,84 kcal/PCVZ0,75 e as de energia metabolizável para mantença (EMm) foram de 140,17 kcal/PCVZ0,75. As eficiências de utilização da energia para mantença e ganho de peso foram, respectivamente, 0,70 e 0,44. Os conteúdos corporais de proteína e minerais, exceto cálcio, diminuíram com o aumento do PC enquanto os de energia aumentaram. O leite das vacas Nelore apresentou teores médios de 3,71, 3,88 e 4,74%, respectivamente, para proteína bruta, gordura e lactose. Conclui-se que as exigências de ELm para lactação de vacas Nelore são de 97,84 kcal/PCVZ0,75 , enquanto que as de EMm são de 140,17 kcal/PCVZ0,75, que as exigências de proteína metabolizável são de 52,8 g/kg de leite e que para produzir 1 kg de leite com 4% de gordura,vacas Nelore necessitam de 0,300 kg de NDT. Para os bezerros, as exigências líquidas de proteína e energia aumentaram com o aumento do peso corporal, enquanto as de cálcio diminuíram. As exigências de proteína metabolizável para ganho de 1 kg de PC foram de 216,96 e 261,98g para bezerros de 100 e 200 kg, respectivamente. Recomenda-se utilizar as seguintes equações para estimar os conteúdos corporais de bezerros Nelore lactentes: Proteína (g/dia) = 0,135 x PCVZ1,0351; Energia (Mcal/dia) = 1,1798 x PCVZ1,1805 ; Ca (g/dia) = 0,091 x PCVZ0,6019; P (g/dia) = 0,00894 x PCVZ0,9629 ; Na (g/dia) = 0,00126 x PCVZ0,9791; Mg (g/dia) = 0,000405 x PCVZ0,9827; K (g/dia) = 0,00165 x PCVZ0,9364.The experiment was conducted to determine the nutritional requirements (energy, protein, macro minerals) of Nellore cows and their calves from birth to six months of age. A total of 40 Nellore, 20 cows and 20 calves, with average initial weight of 362 ± 25 and 30 ± 3 kg, respectively, were used. The calves were fed individually for periods of 90 to 180 days after calving cows. The cows were divided into maintenance (4) and performance (12) up to 90 days and also from 90 to 180 days postpartum. The calves were divided into 90 and 180 days, without food restriction. Eight animals were used as reference (four cows and four calves) The diet consisted of corn silage (CS) and concentrated with forage to concentrate ratio of 70:30 for the cows, and the CS provided ad libitum together with 0, 5 kg / day of concentrate to calves. The intake of dry matter and nutrients were calculated weekly from the laboratory analysis of food provided and leftovers were computed and discounted. Milk production was determined weekly by the method of weigh-suckle-weigh . Digestibility trials were carried out every 28 days (cattle) and another two for the calves. Fecal excretion was determined using the neutral detergent fiber indigestible (iNDF) as an indicator. Animals weights were taken every 28 days. Milking was performed every 28 days to measure the levels of fat, protein and lactoses in milk. The energy concentration, expressed in TDN was calculated from the nutrients disgestibilities. The diet energy concentration was obtained by the equation DE (Mcal / kg) = 5.65 x CPD + 9.39 x EED + 4.15 NDFD + 4.15 x DNFC. The content of protein, energy and minerals were estimated by the equation Y = a. Xb, where X is the empty body weight (EBW) and, a and b are the parameters of the allometric equation. Relations were obtained for average 0.894 (EBW / BW) and 0.936 (EBW / BWG) for cows and 0.9622 (EBW / BW) and 0.958 (EBW / BWG) for calves, respectively. The net energy for maintenance of cows (NEm) were 97.84 kcal/EBW0, 75 and the metabolizable energy for maintenance (EMm) were 140.17 kcal/EBW0, 75. The efficiencies of energy uses for xi maintenance and weight gain were respectively 0.70 and 0.44. The content of protein and minerals, except calcium, decreased with the increase in BW while the energy increased. The milk of cows had average contents of 3.71, 3.88 and 4.74%, respectively, for crude protein, fat and lactoses. We conclude that the requirements for NEm lactation of cows are 97.84 kcal/PCVZ0,75, while MEm are 140.17 kcal/PCVZ0, 75, the metabolizable protein requirements are 52, 8 g / kg of milk and to produce 1 kg of milk with 4% fat, nursing Nellore cows needs of 0.300 kg of TDN. For calves, the net requirements of protein and energy increased with increasing body weight, while the calcium decreased. The metabolizable protein requirements for gain of 1 kg BW were 216.96 and 261.98 g for calves with100 and 200 kg respectively. It is recommended to use the following equations to estimate the body content of Nelore infants: Protein (g / day) = 0.135 x PCVZ1, 0351; Energy (Mcal / day) = 1.1798 x PCVZ1, 1805; Ca (g / day ) = 0.091 x PCVZ0, 6019, P (g / day) = 0.00894 x PCVZ0, 9629; Na (g / day) = 0.00126 x PCVZ0, 9791, Mg (g / day) = 0.000405 x PCVZ0 , 9827; K (g / day) = 0.00165 x PCVZ0, 9364

Avaliação e desenvolvimento de modelos matemáticos para explicar o crescimento de bovinos de corte, e sua relação com os requirementos nutricionais de animais F1 Nelore x Angus inteiros e castrados

O presente estudo foi realizado em cinco etapas interligadas da seguinte forma: primeiramente um experimento de abate comparativo foi realizado com 48 F1 Nelore x Angus machos inteiros (MNC) e castrados (MC), para avaliar as exigências líquidas de proteína e energia para o crescimento e manutenção desses animais. Os animais utilizados tinham 12.5 ± 0.51 meses de idade, e média massa corporal em jejum (MCJ) 233 ± 23.5 e 238 ± 24.6 kg de MNC e MC, respectivamente. Animals foram alimentados com proporção de 60:40 silagem de milho: concentrado. Oito animais foram abatidos no início do experimento e os restantes foram distribuídos aleatoriamente em delineamento inteiramente casualisado perfazendo um esquema fatorial 2 (classe sexual) x 3 (pesos de abate). Os animais restantes foram abatidos quando a média da massa corporal (MC) do grupo chegou a 380 (6MNC e 5MC), 440 (6MNC e 5MC), e 500 kg (5MNC e 5MC). O trato gastrointestinal foi esvaziado e limpo sendo órgãos, carcaças, cabeças de, couros, caudas, membros, sanguíneos, e tecidos posteriormente pesados para medir peso de corpo vazio (PCVZ). Estas peças foram moídas separadamente e sub-amostrados para análises químicas. Para cada animal dentro de um período, consumo de matéria seca foi medido diariamente e as amostras de fezes foram coletadas para determinar a digestibilidade da dieta. Não houve diferenças (P> 0,05) no requerimento de energia líquida exigidos para de manutenção (ELm) entre os as classes sexuais testadas. Os dados combinados indicaram uma ELm de 70 kcal/kg0.75 de PCVZ/d, com uma eficiência parcial de utilização da energia metabolizável para líquida de 0,72. Os requerimentos de energia metabolizável para mantença observados foram de 96,96 Mcal/kg0.75/d. A eficiência parcial de utilização do ME para NE para o crescimento foi de 0,41 para os touros e novilhos. As exigências de proteína metabolizável para mantença foram 2,14 g/BW0,75/d. As exigências líquidas de proteína (PLg) apresentaram coeficientes 'a' e 'b' para a equação alométrica, PLg (g/kgPCVZ/d) = a. PCVZb, variando de -0,722 a -0,6118 para 'a' e de 1,0047 a 0,9586 para 'b', para os MNC e MC, respectivamente. Em terceiro lugar, as equações desenvolvidas nos estudos de Hankins e Howe (1946), Marcondes et ai. (2010), Marcondes et al. (2012), e Valadares Filho et ai. (2006), foram avaliadas na tentativa de predizer a composição física e química do corpo de animais F1 Angus x Nelore e novilhos, assim como a de PCVZ e dos componentes não-carcaça, através do uso da secção de da 9 a 11a costelas (HH) e componentes não carcaça. Após o abate, o corte da HH foi dissecada nas frações músculo, gordura e osso. O restante da carcaça foi igualmente dissecado. As outras variáveis avaliadas como preditores parciais incluíram o peso do corpo vazio, o rendimento de carcaça, a percentagem de gordura visceral, o órgão e vísceras percentual e da composição dos componentes nãocarcaça. Os valores estimados com as equações de predição foram comparados com os valores observados e entre os modelos. No que diz respeito o composição da carcaça fisicamente separáveis apenas o modelo elaborado pela Marcondes et al. (2012) estimaram acurada e precisamente a quantidade de músculo e tecido adiposo presente na carcaça. Os modelos desenvolvidos por Valadares Filho et al. (2006) e Marcondes et al. (2010) estimaram com acurácia e precisão a quantidade de componentes químicos da carcaça, juntamente com o modelo elaborado por Hankins e Howe (1946), que só pôde explicar a quantidade ou teor de proteína bruta na carcaça. Os modelos de usados para predizer a composição química da carcaça falharam em estimar a quantidade correta dos componentes químicos no peso de corpo vazio, exceto para Valadares Filho et al. (2006), que podem ser usadas para a estimativa do teor de proteína bruta em relação ao peso do corpo vazio. O modelo recomendado por Marcondes et al. (2010) não foi capaz de explicar a maioria da variação observada na composição química dos componentes não carcaça, podendo ser recomendado apenas para estimativa dos conteúdos de cinza a água no sangue e couro, e conteúdo de proteína bruta e cinzas presentes no órgãos e vísceras. O quarto passo foi realizado na tentativa de avaliar os modelos desenvolvidos para estimar a composição física e química da carcaça e do corpo vazio de bovinos por meio de mensurações biométricas (BM) coletadas ao longo do corpo do animal e secção HH. Foram utilizados de 40 dos 48 animais F1 Nelore x Angus MNC e MC. Antes do abate, os animais foram conduzidos através do tronco de contenção onde as BM foram tomadas, incluindo a largura de íleo (HBW), a largura de ísquio (PBW), arqueamento de costela (AW), comprimento corporal (BL), altura da garupa (RH), altura na cernelha (HW), comprimento de garupa (PGL), profundidade de costela (RD), perímetro toráxico (GC), profundidade de garupa (RuD), comprimento da diagonal do corpo (BDL), e largura do tórax (TW). Além disso, foram incluídos post mortem medições de: Superfície de total do corpo (TBS), volume corpo (BV), gordura subcutânea (SF), gordura interna (InF), intermuscular (FMI), gordura física da carcaça (CF), gordura física no corpo vazio do animal (EBF), gordura química na carcaça (CFch), gordura química no corpo vazio (EBFch), espessura de gordura na altura da 12 ª costela (FT), e gordura na secção entre a 9 - 11 ª costelas (HHF). Os valores obtidos pelas estimativas dos modelos foram comparados com os valores observados e entre modelos. Dentre todas as equações avaliadas para predizer a composição corporal e seus caminhos para o fazer, apenas equações [7] e [8], usadas para estimar o volume corporal, e equações [27] e [32], para estimativas da gordura fisicamente separável no corpo vazio pode ser recomendado para ser usado para estimar os seus conteúdo usando F1 Nellore x Angus MNC e MC. A quinta etapa foi uma tentativa de responder às perguntas geradas na avaliação de modelos da quarta etapa, e para isso foi realizado um estudo na tentativa de avaliar os teores físicos e químicos de gordura presentes na carcaça e no corpo e vazio por meio BM e medidas pós-morte tomadas em 40 touros (B) e novilhos (S) F1 Nelore x Angus. Os mesmos 40 animais foram usadas para desenvolver as equações preditivas. As equações foram desenvolvidas através de um processo passo a passo para selecionar as variáveis que devem entrar no modelo. O r2 e a raiz do quadrado médio do erro (RMSE) foram usadas para acessar a precisão e acurácia dos modelos. Para TBS r2 variou de 0,852 a 0,946 com RMSE variando de 0,06 a 0,100 kg, para BV r2 variou 0,942 a 0,998 e RMSE de 0,004 a 0,022 kg, para SF r2 variou 0,767 a 0,997 e RMSE 2,70 a 3,24 kg, para InF r2 variou de 0,816 a 0,900 e RMSE de 3,04 a 4,12 kg; para CF r2 variou de 0,830 a 0,988 e RMSE de 3,44 a 8,39 kg; para EBF r2 variou de 0,861 a 0,998 e RMSE 2,98 a 10,98 Kg; para CFch r2 variou de 0,825 a 0,985 e RMSE de 5,96 a 8,46 kg, e para EBFch r2 variou de 0,862 a 0,992 e RMSE de 5,54 a 12,19 kg. Nossos resultados indicaram que BM poderiam ser usadas para aumentar o ajuste dos modelos ou ainda como alternativa para predizer os diferentes depósitos de gordura de animais confinados F1 Nellore x Angus inteiros e castrados.This present study was performed in five interconnected steps as follows: first a comparative slaughter trial was conducted with 48 F1 Nellore x Angus bulls (B) and steers (S), to assess the net requirements of protein and energy for growth and maintenance. The animals used had 12.5±0.51 mo of age, and average shrunk BW (SBW) 233±23.5, and 238±24.6 kg for B and S respectively. Animals were fed 60:40 ratio of corn silage:concentrate. Eight animals were slaughtered at the beginning of the trial and the remaining animals were randomly assigned in a factorial 2 (genders) x 3 (slaughter weights) arrangement. The remaining animals were slaughtered when the average BW of de group reached 380 (6B and 5S), 440 (6B and 5S), and 500 kg (5B and 5S). The cleaned gastrointestinal tracts, organs, carcasses, heads, hides, tails, limbs, blood, and tissues were weighed to measure empty BW (EBW). These parts were ground separately and sub-sampled for chemical analyses. For each animal within a period, DMI was measured daily and samples of feces were collected to determine diet digestibility. There were no differences (P > 0.05) in net energy required for maintenance (NEm) among genders. The combined data indicated a NEm of 70 kcal/kg0.75 of EBW/d, with a partial efficiency of use of ME to NE for maintenance of 0.72. The MEm observed was 96.96 Mcal/kg0.75/d. The partial efficiency of use of ME to NE for growth was 0.41 for bulls and steers. The metabolizable protein requirements for maintenance were 2.14 g/BW0, 75/d. The net requirements had coefficients a and b for the allometric equation NPg (g/kg EBW/d) = a. EBWb, ranging from -0.722 to -0.6118 for a and from 1.0047 to 0.9586 for b , for bulls and steers, respectively. Thirdly, equations developed in the studies of Hankins and Howe (1946), Marcondes et al. (2010), Marcondes et al. (2012), and Valadares Filho et al. (2006) were evaluated in attempt to predict the body physically separable and chemical composition of F1 Angus x Nellore bulls and steers, as wells for empty body and non-carcass components, through the use of the 9-11th Rib section and non-carcass measurements. After slaughter, the 9 11th Rib cut was dissected into muscle, fat and bone fractions. The remaining carcass was similarly dissected. The others variables evaluated as partial predictors included the empty body weight, the dressing percentage, the visceral fat percentage, the organ and viscera percentage and the composition of the non-carcass components. The values estimated with prediction equations were compared to the observed values and among models. Regarding the physically separable carcass composition only the model devised by Marcondes et al. (2012) estimated precisely and accurately the amount of muscle and fat tissue present in the carcass. The models devised by Valadares Filho et al. (2006) and Marcondes et al. (2010) estimated accurately and precisely the amount of carcass chemical components, along with the model devised by Hankins and Howe (1946) which could only explain the amount of crude protein content in the carcass. The models used to predict carcass chemical composition failure in estimate the correct amount of chemical contents present in the empty body weight, except for Valadares Filho et al. (2006) that can be used for the estimation of the crude protein content in the empty body weight. The model devised by Marcondes et al. (2010) was not able to explain most of the chemical composition variation present in the non-carcass components, being recommended only for ashes and water contents in the blood and hide, and furthermore crude protein and ashes content in the organs and viscera. The fourth step was conducted in an attempt to evaluate current devised models to estimate the body and empty body physically separable fat, and chemical composition through biometric (BM) and 9-11th rib section measurements taken in 40 out of the 48 F1 Nellore x Angus bulls (B) and steers (S). Before the slaughter, the animals were lead through a squeeze chute in which BM were taken, including hook bone width (HBW), pin bone width (PBW), abdomen width (AW), body length (BL), rump height (RH), height at withers (HW), pelvic girdle length (PGL), rib depth (RD), girth circumference (GC), rump depth (RuD), body diagonal length (BDL), and thorax width (TW). Additionally, post mortem measurements were included: total body surface (TBS), body volume (BV), subcutaneous fat (SF), internal fat (InF), intermuscular fat (ImF), carcass physical fat (CF), empty body physical fat (EBF), carcass chemical fat (CFch), empty body chemical fat (EBFch), fat thickness in the 12th rib (FT), and 9 11th rib section fat (HHF). The values estimated with prediction equations were compared to the observed values and among models. Among all evaluated equations to predict the body composition and its paths to do so, only equations [7] and [8], for body volume prediction, and [27] and [32], for empty body physically separable fat prediction can be devised to be used while estimating their contents using F1 Nellore x Angus bulls and steers. The fifth step was an attempt to answer the questions generated at the fourth step and for that a study was conducted in attempt to assess the body and empty body fat physical and chemical composition through biometric (BM) and postmortem measurements taken in 40 F1 Nellore x Angus bulls (B) and steers (S). The same 40 animals within its biometrical measurements were used to develop the predictive equations. The equations were developed using a stepwise procedure to select the variables that should enter in the model. The r2 and root mean square error (RMSE) were used to account for precision and accuracy. For TBS r2 ranged from 0.852 to 0.946 and RMSE from 0.06 to 0.100 kg; for BV r2 ranged from 0.942 to 0.998 and RMSE from 0.004 to 0.022 kg; for SF r2 ranged from 0.767 to 0.997 and RMSE from 2.70 to 3.24 kg kg; for InF r2 ranged from 0.816 to 0.900 and RMSE from 3.04 to 4.12 kg; for CF r2 ranged from 0.830 to 0.988 and RMSE from 3.44 to 8.39 kg; for EBF r2 ranged from 0.861 to 0.998 and RMSE from 2.98 to 10.98 kg; for CFch r2 ranged from 0.825 to 0.985 and RMSE from 5.96 to 8.46 kg; and for EBFch r2 ranged from 0.862 to 0.992 and RMSE from 5.54 to 12.19 kg. Our results indicated that the BM could be used to either increase the goodness of fit or as alternative to predict the different fat depots of confined F1 Nellore x Angus bulls and steers

Models of protein and amino acid requirements for cattle

Protein supply and requirements by ruminants have been studied for more than a century. These studies led to the accumulation of lots of scientific information about digestion and metabolism of protein by ruminants as well as the characterization of the dietary protein in order to maximize animal performance. During the 1980s and 1990s, when computers became more accessible and powerful, scientists began to conceptualize and develop mathematical nutrition models, and to program them into computers to assist with ration balancing and formulation for domesticated ruminants, specifically dairy and beef cattle. The most commonly known nutrition models developed during this period were the National Research Council (NRC) in the United States, Agricultural Research Council (ARC) in the United Kingdom, Institut National de la Recherche Agronomique (INRA) in France, and the Commonwealth Scientific and Industrial Research Organization (CSIRO) in Australia. Others were derivative works from these models with different degrees of modifications in the supply or requirement calculations, and the modeling nature (e.g., static or dynamic, mechanistic, or deterministic). Circa 1990s, most models adopted the metabolizable protein (MP) system over the crude protein (CP) and digestible CP systems to estimate supply of MP and the factorial system to calculate MP required by the animal. The MP system included two portions of protein (i.e., the rumen-undegraded dietary CP - RUP - and the contributions of microbial CP - MCP) as the main sources of MP for the animal. Some models would explicitly account for the impact of dry matter intake (DMI) on the MP required for maintenance (MPm; e.g., Cornell Net Carbohydrate and Protein System - CNCPS, the Dutch system - DVE/OEB), while others would simply account for scurf, urinary, metabolic fecal, and endogenous contributions independently of DMI. All models included milk yield and its components in estimating MP required for lactation (MPl) and calf birth weight and some form of an empirical, exponential equation to compute MP for pregnancy (MPp). The MP required for growth (MPg) varied tremendously among the original models and their derivative works mainly due to the differences in computing growth pattern and the composition of the gain. The calculation of MCP differs among models; some rely on the total digestible nutrient (TDN; e.g., NRC, CNCPS level 1) intake to estimate MCP, while others use fermentable organic matter (FOM; e.g., INRA, DVE/OEB), fermentable carbohydrate (e.g., CNCPS level 2, NorFor), or metabolizable energy (ME; e.g., ARC, CSIRO, Rostock). Most models acknowledged the importance of ruminal recycled N, but not all accounted for it. Our Monte Carlo simulation indicated the prediction of most models for required MPl overlapped, confirming uniformity among models when predicting requirements for lactating animals, but a large variation in required MPg for growing animals exists