Protein and energy for maintenance and gain of European quail fed different energy sources and housed at two temperatures

The objective of this study was to evaluate whether replacing corn starch (CS) energy with isolated soy protein (ISP) and soybean oil (SO) and the ambient temperature affect the protein and energy requirements for maintenance and gain of European quail. Thus, a total of 432 European quail from 10 to 30 days of age, distributed in a completely randomized design, were used to estimate the protein and energy requirements for maintenance through the comparative slaughter methodology. The treatments consisted of three diets formulated with the replacement of CS, corresponding to 15% of the metabolizable energy in the diet, with ISP and SO, two controlled temperatures (26 and 35 °C), and three levels of feed supply (ad libitum, and 70 and 40% of ad libitum intake), with four replicates of six birds. Protein and energy requirements for weight gain were determined from 160 European quail, slaughtered every five days at 10, 15, 20, 25, and 30 days of age. Birds were housed in four groups of 40 birds in a room with thermoneutral temperature (26 °C). The energy sources of the feed and temperatures studied affected protein and energy requirements for maintenance and gain of European quail. Replacing CS energy by 15% of dietary energy with SO results in lower protein and energy maintenance requirements for European quail at both temperatures. The protein and energy weight gain requirements of quail fed SO as an energy source is higher than CS and ISP.(AU)

Predictive Equations of Carcass Characteristics and Primal Cut Weights of Native Mexican Guajolotes Using Body Measurements

This study was conducted to develop predictive equations for carcass characteristics and primal cut weights of native Mexican guajolotes using body measurements (BM). For this study, a total of 36 male guajolotes (Meleagris gallopavogallopavo), aged 6 to 10 months, and mean slaughter body weight (SBW) of 4543.14 ± 656.60 g, were used. The birds were kept under traditional extensive conditions. ThefollowingBMswererecorded24 h before slaughter: thoracicperimeter (TP), body circumference (BC), body length (BL), wing length (WL), keel length (KL), shank length (SL) and shank diameter (SD). After slaughter, hot carcass weight (HCW), cold carcass weight (CCW), hot dressing percentage (HDP), cold dressing percentage (CDP), organs and viscera weight (VIS) and abdominal fat weight (AFW) were recorded. The carcasses were dissected in to five primal cut (breast, thigh, drumstick, back and wing). The SBW and BMs showed moderate to high positive correlations (p<0.01; 0.34≤r<0.97) with carcass characteristics and primal cut weights. In the equations generated to predict HCW, CCW, HDP, CDP, VIS and AFW, the R2 ranged from 0.40 to 0.96, and the predictor variables were SBW, KL, BC, WL and SL. Regarding the equations developed to predict the primal cut weights, R2 ranged from 0.58 to 0.91. In these models, SBW, BC, SD, WL and KL explained most of the observed variation. The prediction equations obtained in the study had moderate to high accuracy; therefore, they can be used by researchers, technicians and poultry producers to obtain information on the carcass composition of native Mexican guajolotes.(AU)

Prediction of live weight in growing hair sheep using the body volume formula / Predição do peso vivo de ovelhas deslanadas em crescimento usando a fórmula do volume corporal

Due to the conditions in which traditional sheep production systems operate, the evaluation of animal growth from live weight (LW) is limited by the high cost of the livestock scale as well as the sophisticated maintenance required. In this scenario, in recent years, biometric measurements have been investigated as an accurate indirect method to predict the LW of farm animals. Therefore, the present study was undertaken to examine different models for predicting the body weight of growing lambs using the body volume (BV) formula. Body volume, heart girth (HG) and body length (BL) data of 290 lambs aged between two and eight months were recorded. Body volume was calculated from HG and BL data using a formula that calculates the volume of a cylinder. The estimation of LW from the BV formula was achieved through regression equations using three mathematical models (linear, quadratic and exponential). The mean values of LW, HG, BL and BV of the lambs were 29.12±12.04kg, 70.00±11.69cm, 38.40±6.43cm and 23.93±9.90dm3, respectively. The correlation coefficient between LW and BV was r = 0.96 (P<0.001). The quadratic model showed the highest coefficient of determination (0.93) and the lowest prediction error (3.29kg). Under the experimental conditions adopted in this study, it is possible to predict the live weight of growing lambs using the body volume formula.

Devido às condições dos sistemas tradicionais de produção de ovinos, a avaliação do crescimento animal a partir do peso vivo (PV) é limitada pelo alto custo da balança pecuária, bem como pela sofisticada manutenção necessária. Assim, nos últimos anos, as medidas biométricas (MB) têm sido avaliadas como um método indireto e preciso para predizer o PV de animais de criação. Portanto, o objetivo desta pesquisa foi avaliar diferentes modelos de predição do PV de cordeiros em crescimento utilizando-se a fórmula do volume corporal (VC). Foram registrados dados de PV, perímetro torácico (PT) e comprimento corporal (CC) de 290 cordeiros entre dois e oito meses de idade. O VC foi calculado com base nos dados PT e CC, sendo usada uma fórmula que calcula o volume de um cilindro. A previsão do PV a partir da fórmula VC foi estimada por meio de equações de regressão, utilizando-se três modelos matemáticos (linear, quadrático e exponencial). Os valores médios do PV, PT, CC e VC dos cordeiros foram 29,12±12,04kg, 70,00±11,69cm, 38,40±6,43cm e 23,93±9,90 (dm3), respectivamente. O coeficiente de correlação entre PV e VC foi r=0,96 (P<0,001). O modelo quadrático apresentou o maior coeficiente de determinação (0,93) e o menor erro de predição (3,29kg) Nas condições do presente estudo, conclui-se que é possível predizer o peso vivo de cordeiros em crescimento por meio da fórmula de volume corporal.

Prediction of Egg Weight from External Egg Traits of Guinea Fowl Using Multiple Linear Regression and Regression Tree Methods

The study was done to predict egg weight from the external traits of the Guinea fowl egg using the statistical methods of multiple linear regression (MLR) and regression tree analysis (RTA). A total of 110 eggs from a flock of 23-week-old Guinea fowl were evaluated. Egg weight (EW) and external traits: eggshell weight (ESW), egg polar diameter (EPD), egg equatorial diameter (EED), egg shape index (ESI), and egg surface area (ESA) were measured. Descriptive statistics, Pearson correlation coefficients, and regression equations using the MLR were obtained; additionally, a RTA was done using the CHAID algorithm with the SPSS software (IBM ver. 22). EW presented positive correlations (p<0.0001) with ESA (r = 0.72), EPD (r = 0.65), and EED (r = 0.49). EW can be predicted through MLR using ESA as a predictor variable (R2 = 72%). Predictive accuracy improves when adding EPD and EED traits to the model (R2 = 75%). The RTA built a diagram using ESA, EED, and EPD as significant independent variables; of these, the most important variable was ESA (F = 50,295, df1 = 4, and df2 = 105; Adj. p<0.000) and the variation explained for EW was 74%. Likewise, the RTA showed that the highest egg weight (41.818 g) is obtained from eggs with a surface area > 59.03 cm2 and a polar diameter > 5.10 cm. The proposed statistical methods can be used to reliably predict the egg weight of Guinea fowl.(AU)

Prediction of Egg Weight from External Egg Traits of Guinea Fowl Using Multiple Linear Regression and Regression Tree Methods

The study was done to predict egg weight from the external traits of the Guinea fowl egg using the statistical methods of multiple linear regression (MLR) and regression tree analysis (RTA). A total of 110 eggs from a flock of 23-week-old Guinea fowl were evaluated. Egg weight (EW) and external traits: eggshell weight (ESW), egg polar diameter (EPD), egg equatorial diameter (EED), egg shape index (ESI), and egg surface area (ESA) were measured. Descriptive statistics, Pearson correlation coefficients, and regression equations using the MLR were obtained; additionally, a RTA was done using the CHAID algorithm with the SPSS software (IBM ver. 22). EW presented positive correlations (p 59.03 cm2 and a polar diameter > 5.10 cm. The proposed statistical methods can be used to reliably predict the egg weight of Guinea fowl.

Modeling the weight gain of freshwater-reared rainbow trout ( Oncorhynchus mykiss ) during the grow-out phase

We used five nonlinear models to calculate the weight gain of rainbow trout (122.11±15.6 g) during the final grow-out phase of 98 days under three different feed types (two commercials diets, A and B, and one experimental diet, C) in triplicate groups. We fitted the von Bertalanffy growth function with allometric and isometric scaling coefficient, Gompertz, Logistic, and Brody functions to weight (g) at age data of 900 fish, distributed in nine tanks. The equations were fitted to the data based on the least squares method using the Marquardt iterative algorithm. The accuracy of the fitted models was evaluated using a model performance metrics, combining mean squared residuals (MSR), mean absolute error (MAE), and Akaike's Information Criterion corrected for small sample sizes (AICc). All models converged in all cases tested. The evaluation criteria for the Logistic model indicated the best overall fit (0.704) under all different feed types, followed by the Gompertz model (0.148), and the von Bertalanffy-I and von Bertalanffy-A with 0.074 each. The obtained asymptotic values are in agreement with the biological attributes of the species, except for the Brody model, whose values were massively exceeding the biologic traits of rainbow trout in 0.556 of tested cases. Additionally, ∆AICc results identify the Brody model as the only model not substantially supported by the data in any case. All other models are capable of reflecting the effects of various feed types; these results are directly applicable in farm management decisions.(AU)

Nonlinear regression analysis of length growth in cultured rainbow trout / [Análise não linear do crescimento em comprimento de truta-arco-íris de aquicultura ]

Length growth as a function of time has a non-linear relationship, so nonlinear equations are recommended to represent this kind of curve. We used six nonlinear models to calculate the length gain of rainbow trout (Oncorhynchus mykiss) during the final grow-out phase of 98 days under three different feed types in triplicate groups. We fitted the von Bertalanffy, Gompertz, Logistic, Brody, Power Function, and Exponential equations to individual length-at-age data of 900 fish. Equations were fitted to the data based on the least square method using the Marquardt iterative algorithm. Accuracy of the fitted models was evaluated using a model performance metrics combining mean squared residuals (MSR), mean absolute error (MAE) and Akaike's Information Criterion corrected for small sample sizes (AICc). All models converged in all cases tested. Evaluation criteria for the Logistic model indicated the best overall fit (0.67 of combined metric MSR, MAE and AICc) under all different feeding types, followed by the Exponential model (0.185), and the von Bertalanffy and Brody model (0.074, respectively). Additionally, ∆AICc results identify the Logistic and Gompertz models as being substantially supported by the data in 100% of cases. The logistic model can be suggested for length growth prediction in aquaculture of rainbow trout.(AU)

O crescimento em comprimento em função do tempo tem uma relação não linear; por isso, funções não lineares são recomendáveis para descrever essa relação. Seis modelos não lineares foram usados para calcular o ganho em comprimento de truta-arco-íris (Oncorhynchus mykiss) durante 98 dias, na fase final da engorda, submetidas a três dietas diferentes em grupos triplicados. Foram ajustadas as equações de von Bertalanffy, Gompertz, logístico, Brody, função potencial e exponencial a dados individuais de comprimento-idade de 900 peixes. O ajuste foi feito pelo método dos mínimos quadrados, usando-se o algoritmo iterativo de Marquardt. A precisão do ajuste foi avaliada pelo uso de critérios combinados de ajuste: quadrado médio do resíduo (QMR), erro médio absoluto (EMA) e o critério de informação de Akaike corrigido para tamanhos amostrais pequenos (AICc). Todos os modelos atingiram a convergência para cada caso avaliado. Os critérios de avaliação do modelo logístico indicaram o melhor ajuste geral (0,67 vez dos critérios combinados MSR, MAE e AICc) para cada grupo de peixe avaliado, seguido pelo modelo exponencial (0,185) e os modelos von Bertalanffy e Brody, com 0,074, respectivamente. Similarmente, os resultados de ΔAICc identificaram-se ao modelo logístico e ao de Gompertz, com grande suporte das informações em 100% dos casos. Por fim, o modelo logístico pode ser sugerido na predição do crescimento em comprimento de truta-arco-íris cultivada.(AU)

Using near infrared spectroscopy to predict metabolizable energy of corn for pigs

ABSTRACT: The chemical composition of corn is variable and the knowledge of its chemical and energetic composition is required for an accurate formulation of the diet. This study aimed to determine the chemical composition, that is, dry matter (DM), mineral matter (MM), neutral detergent fiber (NDF), acid detergent fiber (ADF), ether extract (EE), crude protein (CP), gross energy (GE) and energetic values of different varieties (batches) of corn and validate mathematical models to predict the metabolizable energy values (ME) of corn for pigs using near infrared spectroscopy (NIRS). Corn samples were scanned in the spectrum range between 1,100 and 2,500 nm, the model parameters were estimated by the modified partial least squares (MPLS) method. Ten prediction equations were inserted into the NIRS and used to estimate the ME values. The first degree linear regression models of the estimated ME values in function of the observed ME values were adjusted. The existence of a linear ratio was evaluated by detecting the significance to posterior estimates of the straight line parameters. The values of digestible energy and ME ranged from 3,400 to 3,752 and 3,244 to 3,611 kcal kg1, respectively. The prediction equations, ME1 = 4334 8.1MM + 4.1EE 3.7NDF; ME2 = 4,194 9.2MM + 1.0CP + 4.1EE 3.5NDF; and ME7 = 16.13 9.5NDF + 16EE + (23CP × NDF) (138MM × NDF) were the most adequate to predict the ME values of corn by using NIRS.

Using near infrared spectroscopy to predict metabolizable energy of corn for pigs

The chemical composition of corn is variable and the knowledge of its chemical and energetic composition is required for an accurate formulation of the diet. This study aimed to determine the chemical composition, that is, dry matter (DM), mineral matter (MM), neutral detergent fiber (NDF), acid detergent fiber (ADF), ether extract (EE), crude protein (CP), gross energy (GE) and energetic values of different varieties (batches) of corn and validate mathematical models to predict the metabolizable energy values (ME) of corn for pigs using near infrared spectroscopy (NIRS). Corn samples were scanned in the spectrum range between 1,100 and 2,500 nm, the model parameters were estimated by the modified partial least squares (MPLS) method. Ten prediction equations were inserted into the NIRS and used to estimate the ME values. The first degree linear regression models of the estimated ME values in function of the observed ME values were adjusted. The existence of a linear ratio was evaluated by detecting the significance to posterior estimates of the straight line parameters. The values of digestible energy and ME ranged from 3,400 to 3,752 and 3,244 to 3,611 kcal kg1, respectively. The prediction equations, ME1 = 4334 8.1MM + 4.1EE 3.7NDF; ME2 = 4,194 9.2MM + 1.0CP + 4.1EE 3.5NDF; and ME7 = 16.13 9.5NDF + 16EE + (23CP × NDF) (138MM × NDF) were the most adequate to predict the ME values of corn by using NIRS.(AU)

Using near infrared spectroscopy to predict metabolizable energy of corn for pigs

ABSTRACT: The chemical composition of corn is variable and the knowledge of its chemical and energetic composition is required for an accurate formulation of the diet. This study aimed to determine the chemical composition, that is, dry matter (DM), mineral matter (MM), neutral detergent fiber (NDF), acid detergent fiber (ADF), ether extract (EE), crude protein (CP), gross energy (GE) and energetic values of different varieties (batches) of corn and validate mathematical models to predict the metabolizable energy values (ME) of corn for pigs using near infrared spectroscopy (NIRS). Corn samples were scanned in the spectrum range between 1,100 and 2,500 nm, the model parameters were estimated by the modified partial least squares (MPLS) method. Ten prediction equations were inserted into the NIRS and used to estimate the ME values. The first degree linear regression models of the estimated ME values in function of the observed ME values were adjusted. The existence of a linear ratio was evaluated by detecting the significance to posterior estimates of the straight line parameters. The values of digestible energy and ME ranged from 3,400 to 3,752 and 3,244 to 3,611 kcal kg1, respectively. The prediction equations, ME1 = 4334 8.1MM + 4.1EE 3.7NDF; ME2 = 4,194 9.2MM + 1.0CP + 4.1EE 3.5NDF; and ME7 = 16.13 9.5NDF + 16EE + (23CP × NDF) (138MM × NDF) were the most adequate to predict the ME values of corn by using NIRS.

Comparações entre o consumo observado e predito pelos sistemas nutricionais NRC e BR-Corte em novilhas Nelore confinadas no sistema GrowSafe® / Comparisons between observed and predicted consumption by NRC and BR-Court nutritional systems in Nelore heifers confined in the Grow Safe® system / Comparaciones entre el consumo observado y predicado por los sistemas nutricionales NRC y BR-Corte en novillas Nelore confinadas en el sistema Grow Safe®

Objetivou-se encontrar qual equação dos sistemas nutricionais BR-Corte (2010 e 2016) e NRC (2000 e 2016) melhor prediz o consumo de matéria seca (CMS) em novilhas de corte da raça Nelore em confinamento em sistema eletrônico de alimentação GrowSafe. Foram utilizadas 25 novilhas da raça Nelore, com idade entre 22 e 25 meses e peso médio corporal inicial 318 Kg. Comparou-se o CMS observado aos preditos segundo os sistemas nutricionais. O CMS médio observado das novilhas foi de 7,46 Kg/dia. A ingestão de matéria seca predita pelo NRC 2000 foi superestimada em 9,78% e pelo BR-Corte 2010, em 5,5%, já NRC 2016 e Br-Corte 2016 subestimaram o consumo das novilhas em 18,9% e 7,1%, respectivamente. Concluiu-se que os modelos para predição do CMS para novilhas da raça Nelore propostos pelos sistemas BR-Corte são mais adequados que os modelos do NRC.(AU)

The objective of this study was to find which equation of nutrition systems, BR-Corte (2010 and 2016) or NRC (2000 and 2016), better predict the dry matter intake (DMI) in heifers confinedin the electronic feeding system GrowSafe. Nellore heifers, aged 22 to 25 months and with an initial body weight of 318 kg, were sampled. It was compared the observed DMI with those predicted according to nutritional systems. The mean DMI of the heifers was 7.46 kg/day. The estimated dry matter intake in NRC 2000 was overestimated by 9.78% and BR-Corte 2010, by 5.5%, while NRC 2016 and Br-Corte 2016 underestimated heifer consumption by 18.9% and 7.1%, respectively. It was concluded that the models for predicting DMI for Nellore heifers proposed by the BR-Corte systems are more suitable than the NRC models.(AU)

En el presente trabajo se analizaron los resultados obtenidos por los sistemas nutricionales BR-Corte (2010 y 2016) y NRC (2000 y 2016), buscando encontrar el que mejor predice el consumo de materia seca (CMS) en novillas de corte de la raza Nelore en confinamiento en sistema electrónico de alimentación GrowSafe. Se utilizaron 25 novillas de la raza Nelore, con edades entre 22 y 25 meses y peso corporal inicial 318 Kg. Se comparó el CMS observado a los predichos según los sistemas nutricionales. El CMS medio observado de las novillas fue de 7,46 Kg/día. La ingesta de materia seca predicha por el NRC 2000 fueron superestimadas en 9,78% y por el BR-Corte 2010, en 5,5%, ya el NRC 2016 y el Br-Corte 2016 subestimaron el consumo de las novillas en 18,9% y 7,1%, respectivamente. Se concluyó que los modelos para predicción del CMS para novillas de la raza Nelore propuestos por los sistemas BR-Corte son más adecuados que los modelos del NRC.(AU)

Comparações entre o consumo observado e predito pelos sistemas nutricionais NRC e BR-Corte em novilhas Nelore confinadas no sistema GrowSafe® / Comparisons between observed and predicted consumption by NRC and BR-Court nutritional systems in Nelore heifers confined in the Grow Safe® system / Comparaciones entre el consumo observado y predicado por los sistemas nutricionales NRC y BR-Corte en novillas Nelore confinadas en el sistema Grow Safe®

Objetivou-se encontrar qual equação dos sistemas nutricionais BR-Corte (2010 e 2016) e NRC (2000 e 2016) melhor prediz o consumo de matéria seca (CMS) em novilhas de corte da raça Nelore em confinamento em sistema eletrônico de alimentação GrowSafe. Foram utilizadas 25 novilhas da raça Nelore, com idade entre 22 e 25 meses e peso médio corporal inicial 318 Kg. Comparou-se o CMS observado aos preditos segundo os sistemas nutricionais. O CMS médio observado das novilhas foi de 7,46 Kg/dia. A ingestão de matéria seca predita pelo NRC 2000 foi superestimada em 9,78% e pelo BR-Corte 2010, em 5,5%, já NRC 2016 e Br-Corte 2016 subestimaram o consumo das novilhas em 18,9% e 7,1%, respectivamente. Concluiu-se que os modelos para predição do CMS para novilhas da raça Nelore propostos pelos sistemas BR-Corte são mais adequados que os modelos do NRC.

The objective of this study was to find which equation of nutrition systems, BR-Corte (2010 and 2016) or NRC (2000 and 2016), better predict the dry matter intake (DMI) in heifers confinedin the electronic feeding system GrowSafe. Nellore heifers, aged 22 to 25 months and with an initial body weight of 318 kg, were sampled. It was compared the observed DMI with those predicted according to nutritional systems. The mean DMI of the heifers was 7.46 kg/day. The estimated dry matter intake in NRC 2000 was overestimated by 9.78% and BR-Corte 2010, by 5.5%, while NRC 2016 and Br-Corte 2016 underestimated heifer consumption by 18.9% and 7.1%, respectively. It was concluded that the models for predicting DMI for Nellore heifers proposed by the BR-Corte systems are more suitable than the NRC models.

En el presente trabajo se analizaron los resultados obtenidos por los sistemas nutricionales BR-Corte (2010 y 2016) y NRC (2000 y 2016), buscando encontrar el que mejor predice el consumo de materia seca (CMS) en novillas de corte de la raza Nelore en confinamiento en sistema electrónico de alimentación GrowSafe. Se utilizaron 25 novillas de la raza Nelore, con edades entre 22 y 25 meses y peso corporal inicial 318 Kg. Se comparó el CMS observado a los predichos según los sistemas nutricionales. El CMS medio observado de las novillas fue de 7,46 Kg/día. La ingesta de materia seca predicha por el NRC 2000 fueron superestimadas en 9,78% y por el BR-Corte 2010, en 5,5%, ya el NRC 2016 y el Br-Corte 2016 subestimaron el consumo de las novillas en 18,9% y 7,1%, respectivamente. Se concluyó que los modelos para predicción del CMS para novillas de la raza Nelore propuestos por los sistemas BR-Corte son más adecuados que los modelos del NRC.

On the controlling of temperature: A proposal for a real-time controller in broiler houses

ABSTRACT: Environmental conditions in broiler houses, specifically temperature, are key factors that should be controlled to ensure appropriate environment for broiler rearing. In countries with tropical/subtropical climate, like Brazil, high temperatures produce heat stress to animals, affecting the production process. This research proposes a real-time model to control temperature inside broiler houses. The controller is a self-correcting model that makes real-time decisions on the ventilation system operation (exhaust fans) together with temperature prediction at the facility. The model involves partial differential equations (PDE) whose parameters are updated according to data registered in real-time. Some experiments were carried out at a pilot farm in the municipality of Jundiaí, São Paulo State, Brazil, for different periods during winter and summer. The results based on simulations in comparison with the current automatic ventilation system show that the model is consistent to keep temperature under control for an efficient production. The model achieved a bias of 0.6 °C on average in comparison with the ideal temperature, whereas the automatic controller measured a bias of 3.3 °C, respectively. Future lines suggest that this approach could be useful in many other situations that involve environmental control for livestock production.

On the controlling of temperature: A proposal for a real-time controller in broiler houses

Environmental conditions in broiler houses, specifically temperature, are key factors that should be controlled to ensure appropriate environment for broiler rearing. In countries with tropical/subtropical climate, like Brazil, high temperatures produce heat stress to animals, affecting the production process. This research proposes a real-time model to control temperature inside broiler houses. The controller is a self-correcting model that makes real-time decisions on the ventilation system operation (exhaust fans) together with temperature prediction at the facility. The model involves partial differential equations (PDE) whose parameters are updated according to data registered in real-time. Some experiments were carried out at a pilot farm in the municipality of Jundiaí, São Paulo State, Brazil, for different periods during winter and summer. The results based on simulations in comparison with the current automatic ventilation system show that the model is consistent to keep temperature under control for an efficient production. The model achieved a bias of 0.6 °C on average in comparison with the ideal temperature, whereas the automatic controller measured a bias of 3.3 °C, respectively. Future lines suggest that this approach could be useful in many other situations that involve environmental control for livestock production.(AU)

On the controlling of temperature: A proposal for a real-time controller in broiler houses

ABSTRACT: Environmental conditions in broiler houses, specifically temperature, are key factors that should be controlled to ensure appropriate environment for broiler rearing. In countries with tropical/subtropical climate, like Brazil, high temperatures produce heat stress to animals, affecting the production process. This research proposes a real-time model to control temperature inside broiler houses. The controller is a self-correcting model that makes real-time decisions on the ventilation system operation (exhaust fans) together with temperature prediction at the facility. The model involves partial differential equations (PDE) whose parameters are updated according to data registered in real-time. Some experiments were carried out at a pilot farm in the municipality of Jundiaí, São Paulo State, Brazil, for different periods during winter and summer. The results based on simulations in comparison with the current automatic ventilation system show that the model is consistent to keep temperature under control for an efficient production. The model achieved a bias of 0.6 °C on average in comparison with the ideal temperature, whereas the automatic controller measured a bias of 3.3 °C, respectively. Future lines suggest that this approach could be useful in many other situations that involve environmental control for livestock production.

Digestibility and net energy prediction of rice by products determined with piglets / Digestibilidade e predição da energia líquida de subprodutos de arroz determinado com leitões

The aim of this study was to determine the chemical composition, digestibility, and net energy (NE) of broken rice (BRR), stabilized rice bran (SRB), and parboiled rice bran (PRB) for piglets. Two digestibility trials were performed with 12 and 18 male pigs with initial weights of 8 and 16kg, respectively. We performed total fecal collection using ferric oxide as fecal marker. The digestibility coefficients of organic matter, crude protein, and gross energy were higher (P<0.001) for the BRR compared to the SRB and PRB. The PRB presented a digestible energy 2% lower than that of BR and 5% higher than that of SRB. For BRR, average NE value was 3,228kcal/kg dry matter (DM), and the difference between the lower and higher value was 311kcal/kg DM. Average NE values of SRB and PRB were 2,896 and 3,293kcal/kgDM, respectively. The difference between the energy predicted by each equation reached 190kcal/kgDM for SRB and 285kcal/kgDM for PRB. In conclusion, BRR showed higher nutrient digestibility coefficients, except for EE and GE, which can be attributed to differences in the production processes. Regardless of the type of feedstuff tested, equations to predict NE values should be used carefully due to considerable differences in energy content.

O objetivo deste estudo foi determinar a composição química, a digestibilidade e a energia líquida (EL) da quirera (QR), farelo de arroz estabilizado (FAE) e farelo de arroz parboilizado (FAP) para leitões. Foram realizados dois ensaios de digestibilidade com 12 e 18 suínos machos com pesos iniciais de 8 e 16kg, respectivamente. A coleta fecal total foi realizada usando óxido férrico como marcador fecal. Os coeficientes de digestibilidade da matéria orgânica, proteína e energia bruta (EB) foram maiores (P<0,001) para o QR em comparação com o FAE e FAP. O FAP apresentou energia digestível 2% inferior à da QR e 5% maior que a da FAE. Para QR, o valor médio de EL foi de 3,228kcal/kg de matéria seca (DM), e a diferença entre o valor inferior e o valor superior foi de 311kcal/kg de MS. Os valores médios de EL de FAE e FAP foram de 2.896 e 3.293kcal/kgMS, respectivamente. A diferença entre a energia predita por cada equação atingiu 190kcal/kgMS para FAE e 285kcal/kgMS para FAP. Em conclusão, QR mostrou maiores coeficientes de digestibilidade dos nutrientes, exceto EE e EB, o que pode ser atribuído a diferenças nos processos de produção. Independentemente do tipo de alimento testado, as equações para prever os valores de EL devem ser usadas com cuidado devido a diferenças consideráveis no conteúdo energético.

A thermodynamic paradigm for using satellite based geophysical measurements in public health applications / Um paradigma termodinâmico para o uso de medidas geofísicas baseadas em satélites e suas aplicações em saúde pública

A thermodynamic paradigm for studying disease vector’s habitats & life cycles using NASA’s remote sensing data is being proposed. NASA’s current and planned satellite missions provide measurements of the critical environmental measures environmental state functions important to vector & disease life cycles such as precipitation, soil moisture, temperature, vapor pressure deficits, wet/dry edges, and solar radiation. Satellite data provide landscape scale process functions represented by land use/cover mapping and actual measurements of ecological functions/structure: canopy cover, species, phenology, and aquatic plant coverage. These measurements are taken in a spatial context and provide a time series of data to track changes in time. Global public health is entering a new informational age through the use of spatial models of disease vector/host ecologies driven by the use of remotely sensed data to measure environmental and structural factors critical in determining disease vector habitats, distributions, life cycles, and host interactions. The vector habitat microclimates can be quantified in terms of the surface energy budget measured by satellites. The epidemiological equations (processes) can be adapted and modified to explicitly incorporate environmental factors and interfaces required by a specific disease and its vector/host cycle. Remote sensing can be used to measure or evaluate or estimate both environment (state functions) and interface (process functions). It is critical that the products of remote sensing must be expressed in a way they can be integrated directly into the epidemiological equations.

Um paradigma termodinâmico para estudar os habitats e ciclos de vida dos vetores de doenças utilizando dados de sensoriamento remoto da NASA está sendo proposto. As missões atuais e planejadas para os satélites da NASA fornecem medições das funções críticas ambientais e funções do estado ambiental, importantes para os ciclos de vida de vetores e doenças, como precipitação, umidade do solo, temperatura, déficits de pressão do vapor, bordas úmidas/secas e radiação solar. Os dados de satélite fornecem as funções dos processos na escala da paisagem, representada pelo mapeamento do uso/cobertura da terra e medições reais das funções/estruturas ecológicas: cobertura do dossel, espécies, fenologia e cobertura de plantas aquáticas. Essas medições são feitas em um contexto espacial e fornecem uma série temporal de dados para rastrear dinâmica das mudanças. A saúde pública global está entrando em uma nova era informacional através do uso de modelos espaciais para vetores/hospedeiros de doenças, impulsionados pelo uso de dados de sensoriamento remoto, para medir fatores ambientais e estruturais críticos na determinação de habitats de vetores de doenças, distribuições, ciclos de vida e interações com o hospedeiro. Os microclimas dos habitats vetoriais podem ser quantificados em termos do orçamento de energia superficial, medidos por satélites. As equações epidemiológicas (processos) podem ser adaptadas e modificadas para incorporar explicitamente fatores e interfaces ambientais requeridos por uma doença específica e o ciclo do seu vetor/hospedeiro. O sensoriamento remoto pode ser usado para medir ou avaliar, ou mesmo estimar tanto o ambiente (funções do seu estado) quanto a interface (funções de seus processos). É fundamental que os produtos de sensoriamento remoto sejam expressos de forma a integrá-los diretamente às equações epidemiológicas.

A thermodynamic paradigm for using satellite based geophysical measurements in public health applications / Um paradigma termodinâmico para o uso de medidas geofísicas baseadas em satélites e suas aplicações em saúde pública

A thermodynamic paradigm for studying disease vectors habitats & life cycles using NASAs remote sensing data is being proposed. NASAs current and planned satellite missions provide measurements of the critical environmental measures environmental state functions important to vector & disease life cycles such as precipitation, soil moisture, temperature, vapor pressure deficits, wet/dry edges, and solar radiation. Satellite data provide landscape scale process functions represented by land use/cover mapping and actual measurements of ecological functions/structure: canopy cover, species, phenology, and aquatic plant coverage. These measurements are taken in a spatial context and provide a time series of data to track changes in time. Global public health is entering a new informational age through the use of spatial models of disease vector/host ecologies driven by the use of remotely sensed data to measure environmental and structural factors critical in determining disease vector habitats, distributions, life cycles, and host interactions. The vector habitat microclimates can be quantified in terms of the surface energy budget measured by satellites. The epidemiological equations (processes) can be adapted and modified to explicitly incorporate environmental factors and interfaces required by a specific disease and its vector/host cycle. Remote sensing can be used to measure or evaluate or estimate both environment (state functions) and interface (process functions). It is critical that the products of remote sensing must be expressed in a way they can be integrated directly into the epidemiological equations.(AU)

Um paradigma termodinâmico para estudar os habitats e ciclos de vida dos vetores de doenças utilizando dados de sensoriamento remoto da NASA está sendo proposto. As missões atuais e planejadas para os satélites da NASA fornecem medições das funções críticas ambientais e funções do estado ambiental, importantes para os ciclos de vida de vetores e doenças, como precipitação, umidade do solo, temperatura, déficits de pressão do vapor, bordas úmidas/secas e radiação solar. Os dados de satélite fornecem as funções dos processos na escala da paisagem, representada pelo mapeamento do uso/cobertura da terra e medições reais das funções/estruturas ecológicas: cobertura do dossel, espécies, fenologia e cobertura de plantas aquáticas. Essas medições são feitas em um contexto espacial e fornecem uma série temporal de dados para rastrear dinâmica das mudanças. A saúde pública global está entrando em uma nova era informacional através do uso de modelos espaciais para vetores/hospedeiros de doenças, impulsionados pelo uso de dados de sensoriamento remoto, para medir fatores ambientais e estruturais críticos na determinação de habitats de vetores de doenças, distribuições, ciclos de vida e interações com o hospedeiro. Os microclimas dos habitats vetoriais podem ser quantificados em termos do orçamento de energia superficial, medidos por satélites. As equações epidemiológicas (processos) podem ser adaptadas e modificadas para incorporar explicitamente fatores e interfaces ambientais requeridos por uma doença específica e o ciclo do seu vetor/hospedeiro. O sensoriamento remoto pode ser usado para medir ou avaliar, ou mesmo estimar tanto o ambiente (funções do seu estado) quanto a interface (funções de seus processos). É fundamental que os produtos de sensoriamento remoto sejam expressos de forma a integrá-los diretamente às equações epidemiológicas.(AU)

Digestibility and net energy prediction of rice by products determined with piglets / Digestibilidade e predição da energia líquida de subprodutos de arroz determinado com leitões

The aim of this study was to determine the chemical composition, digestibility, and net energy (NE) of broken rice (BRR), stabilized rice bran (SRB), and parboiled rice bran (PRB) for piglets. Two digestibility trials were performed with 12 and 18 male pigs with initial weights of 8 and 16kg, respectively. We performed total fecal collection using ferric oxide as fecal marker. The digestibility coefficients of organic matter, crude protein, and gross energy were higher (P<0.001) for the BRR compared to the SRB and PRB. The PRB presented a digestible energy 2% lower than that of BR and 5% higher than that of SRB. For BRR, average NE value was 3,228kcal/kg dry matter (DM), and the difference between the lower and higher value was 311kcal/kg DM. Average NE values of SRB and PRB were 2,896 and 3,293kcal/kgDM, respectively. The difference between the energy predicted by each equation reached 190kcal/kgDM for SRB and 285kcal/kgDM for PRB. In conclusion, BRR showed higher nutrient digestibility coefficients, except for EE and GE, which can be attributed to differences in the production processes. Regardless of the type of feedstuff tested, equations to predict NE values should be used carefully due to considerable differences in energy content.(AU)

O objetivo deste estudo foi determinar a composição química, a digestibilidade e a energia líquida (EL) da quirera (QR), farelo de arroz estabilizado (FAE) e farelo de arroz parboilizado (FAP) para leitões. Foram realizados dois ensaios de digestibilidade com 12 e 18 suínos machos com pesos iniciais de 8 e 16kg, respectivamente. A coleta fecal total foi realizada usando óxido férrico como marcador fecal. Os coeficientes de digestibilidade da matéria orgânica, proteína e energia bruta (EB) foram maiores (P<0,001) para o QR em comparação com o FAE e FAP. O FAP apresentou energia digestível 2% inferior à da QR e 5% maior que a da FAE. Para QR, o valor médio de EL foi de 3,228kcal/kg de matéria seca (DM), e a diferença entre o valor inferior e o valor superior foi de 311kcal/kg de MS. Os valores médios de EL de FAE e FAP foram de 2.896 e 3.293kcal/kgMS, respectivamente. A diferença entre a energia predita por cada equação atingiu 190kcal/kgMS para FAE e 285kcal/kgMS para FAP. Em conclusão, QR mostrou maiores coeficientes de digestibilidade dos nutrientes, exceto EE e EB, o que pode ser atribuído a diferenças nos processos de produção. Independentemente do tipo de alimento testado, as equações para prever os valores de EL devem ser usadas com cuidado devido a diferenças consideráveis no conteúdo energético.(AU)

Parametrization of the Davis Growth Model using data of crossbred Zebu cattle

The system of differential equations proposed by Oltjen et al. [1986, named Davis Growth Model (DGM)] to represent cattle growth has been parameterized with data from Bos taurus (British) and Bos indicus (Nellore) breeds. The DGM has been successfully used for simulation and decision support in the United States. However, the effect of about 30 years of genetic improvement and the use of different breeds may affect the model parameter values, which also may need to be re-estimated for crossbred animals. The aim of this study was to estimate parameter values and confidence intervals for the DGM with growth and body composition data from Zebu crossbred animals. Confidence intervals and asymptotic distribution were generated through nonparametric bootstrap with data from a field experiment conducted in Brazil. The parameters showed normal probability distribution for most scenarios. The rate constant for deoxyribonucleic acid (DNA) synthesis had a minimum increase of 156 % and the maximum of 389 %, compared to the original values and the maintenance requirement had a minimum increase of 126 % and maximum of 160 % compared to the original values. Lower limits of 95 % confidence intervals for the parameters related to maintenance and protein accretion rates were higher than the original estimates of the DGM, evidencing genetic differences of the Zebu crossbred animals in relation to the original DGM parameters.