The objective of this study was to measure the water disappearance in the drinker and the pattern of daily water intake and estimate the amount of water wasted in pig production. The study will also generate information about the daily behaviour of water intake of pigs in the growing and finishing phases. Sixty male pigs with an average initial weight of 44.43 kg subjected to immunocastration were used. Animals received feed and water ad libitum. The animal-performance data, temperature and humidity, and feed and water intake behaviour were collected in real time during the entire experimental period, while water volume consumed was measured daily. The average water disappearance (WD) was 7.98 L, which increased during the studied period, and 29.07% of this corresponds to the estimated water wasted. The daily WD behaviour revealed an increasing pattern throughout the day for growing and finishing periods, with the registered peak at 16:00 and 15:00 h and intake of 6.24 and 9.48 L, respectively. The time spent drinking (TSD) and number of drinker visits (NDV) also showed a peak in the afternoon: 13:00 and 17:00 h for growing and finishing phases, respectively. The TSD was 282.73 and 268.36 s, and the NDV values were 16.13 and 13.84 for growing and finishing phases, respectively. The results demonstrated an increasing pattern during the animal housing period in WD that is proportional to dry matter intake and body weight, and the water wasted represents a significant portion of WD. The daily pattern of WD, TSD, and NDV increase during the total and growing periods, presenting peak activity at 13:00 h. During the finishing phase, TSD and NDV present a pattern similar to the growing phase, but the peak occurs in the last hour of the day.
The hatchery is one of the most important segments of the poultry chain, and generates an abundance of data, which, when analyzed, allow for identifying critical points of the process. The aim of this study was to evaluate the applicability of the data mining technique to databases of egg incubation of broiler breeders and laying hen breeders. The study uses a database recording egg incubation from broiler breeders housed in pens with shavings used for litters in natural mating, as well as laying hen breeders housed in cages using an artificial insemination mating system. The data mining technique (DM) was applied to analyses in a classification task, using the type of breeder and house system for delineating classes. The database was analyzed in three different ways: original database, attribute selection, and expert analysis. Models were selected on the basis of model precision and class accuracy. The data mining technique allowed for the classification of hatchery fertile eggs from different genetic groups, as well as hatching rates and the percentage of fertile eggs (the attributes with the greatest classification power). Broiler breeders showed higher fertility (> 95 %), but higher embryonic mortality between the third and seventh day post-hatching (> 0.5 %) when compared to laying hen breeders' eggs. In conclusion, applying data mining to the hatchery process, selection of attributes and strategies based on the experience of experts can improve model performance.
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 o efeito da inclusão de grãos de destilaria com solúveis em variáveis de desempenho e características de carcaça de suínos em crescimento e terminação por meio de uma meta-análise. A base de dados consistiu em 32 estudos presentes em 19 artigos, envolvendo 17.106 suínos. As características de carcaça incluídas foram peso de carcaça quente, rendimento de carcaça, espessura de toucinho, área de lombo, profundidade de lombo e rendimento de carne. Conversão alimentar foi a única variável que apresentou diferença para desempenho com à adição de DDGS, em relação ao controle, a estatística I2 para conversão alimentar foi de 48% (P= 0,001). Peso da carcaça quente, o rendimento da carcaça, área do lombo, espessura de toucinho e profundidade do músculo apresentaram diferença com a inclusão de grãos de destilaria com solúveis em relação ao controle. A inclusão de DDGS como substituto parcial do milho ou farelo de soja em dietas de suínos nas fases de crescimento e terminação interfere a conversão alimentar, peso de carcaça quente, rendimento de carcaça, espessura de toucinho, profundidade de músculo e área do lombo.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.