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181.
Diarrhea is one of the most frequent diseases of neonatal calves in dairy herds. The aim of this study was to evaluate the effects of neonatal diarrhea and other conditions on subsequent first lactation milk production and reproductive performance of heifer calves up to the first calving. Seven hundred heifer calves (350 with and 350 without the history of diarrhea in first month of life) were monitored from birth until a year after calving. For each heifer, birth season, birth weight, ease of birth and occurrence of diseases from birth to the end of first lactation were recorded as independent variables. Interval from birth to first service, interval from birth to conception, interval from birth to first calving and 305-days milk yield in the first lactation were recorded as dependent variables. Effects of explanatory variables on productive and reproductive indices were evaluated by survival analysis and general linear model. Heifers with the history of diarrhea during the first month of their lives showed lower daily hazard of conception [Hazard ratio: 0.85 (95%CI: 0.73–0.99)] and calving [Hazard ratio: 0.84 (95%CI: 0.72–0.98)] than those of healthy heifers. Subsequent reproductive performance of heifer calves was also associated with birth season and ease of birth. Further, heifer calves born with birth weight of below 35 kg produced an average of 518 and 506 l less milk in their first lactation compared to calves with a birth weight 40–45 (p = 0.013) and greater than 45 kg (P = 0.033), respectively. These findings showed that occurrence of neonatal diarrhea and other neonatal parameters are associated with harmful effects on subsequent production and reproductive performance.  相似文献   
182.
Aflatoxin B1 (AFB1) is a common feed contaminant that adversely affects bird performance and product quality. A total of 600 7‐day‐old quail chicks were randomly allotted to eight experimental groups in a completely randomized design with five replicate pens and 15 quails per pen. Experimental treatments including two levels of AFB1 (0 and 2.5 mg/kg) and 4 levels of Nigella sativa (NS) (0, 0.5, 1.0 and 1.5% of diet) were offered from 7 to 35 days of age to quail chicks. Although feeding of AFB1 impaired gain (G) and feed conversion ratio, dietary NS increased G (p < 0.05). Relative weight of bursa of Fabricius increased with incremental levels of NS (p < 0.05). AFB1 decreased the size of heart, but incremental levels of NS increased the relative weight of heart (p < 0.05). The liver hypertrophy was observed in birds receiving AFB1 (p < 0.05). The birds in AFB1 group had smaller testes than other groups (p < 0.05). Hematocrit value in birds fed AFB1 was lower than that in other groups (p < 0.05) and incremental levels of NS increased blood hematocrit (p < 0.05). Amount of malondialdehyde (MDA) in meat samples of the birds fed AFB1 was higher than those did not receive toxin but incremental levels of NS decreased the MDA concentration in affected birds (p < 0.05). AFB1 suppressed the humoral immunity of the birds while NS augmented the antibody titres against sheep red blood cell and Newcastle disease virus antigens (p < 0.05). AFB1 decreased lactic acid bacteria (LAB) and spore‐forming bacteria (SFB) but increased Escherichia coli (E. coli; p < 0.05). However, NS increased LAB and SFB but decreased the E. coli populations (p < 0.05). This study revealed that NS as a biological detoxifier could relatively attenuate the negative effects of AFB1 in quails.  相似文献   
183.
Studying the status of agricultural soils is one of the most important concerns in the agricultural sector. The soil organic carbon (SOC) is one of the main parameters and it plays an important role in improving soil properties. Hence, knowing this parameter is important in soil science. This study applied the pattern recognition (PR) method in predicting the SOC. Also, the ability of this method was compared with different methods such as the Radial Basis Function Network (RBF), Multilayer Perceptron Neural Network (MLP), Multiple Linear Regression (MLR) and Support Vector Regression (SVR). To compare the results, four performance criteria, namely, root mean square errors (RMSE), the Nash–Sutcliffe efficiency (NS), Willmott’s Index of agreement (WI), mean absolute error (MAE) and Taylor diagrams were used. Results indicated that the PR model performed significantly better than the MLP, MLR, SVR, and RBF models for the estimation of the SOC.  相似文献   
184.
In this research, the influence of climate change on maize cultivation was investigated and then, the possible solutions for adopting this natural hazard in the coasts of Caspian Sea in Iran was assessed. Weather data were generated for the 2011–2100 period using a statistical downscaling model under different climatic scenarios. Reference evapotranspiration (ETo) was calculated using a Neuro-fuzzy inference system. Cop water requirement was calculated by multiplying ETo by crop coefficients. Increased cardinal temperatures during 2011–2100 led to shifting in the planting date backward by 10–26 days. In addition, the projected global warming has a considerable effect on the duration of the vegetative growth stage resulting in earlier harvesting. However, the duration of the reproductive stage is less affected. Despite the obvious reduction in the length of the growing season, crop water requirement will increase by 10.6–15.3% in the future due to 1.64–28.4% increase in ETo. However, changing the cultivation time may lead to 11.2–264.5 m3 ha?1 water saving during the whole cropping cycle through affecting both ETo and the crop growth cycle. This result demonstrates that management of the maize cropping calendar can be an effective way to achieve sustainable agriculture under future climate conditions in the study area.  相似文献   
185.
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