Resumo O arroz é um alimento básico amplamente consumido por grande parte da população humana mundial. Aproximadamente 90% do arroz do mundo é cultivado no continente asiático e constitui um alimento básico para 2,7 bilhões de pessoas em todo o mundo. O crestamento bacteriano das folhas (BLB) causado por Xanthomonas oryzae pv. oryzae é uma das doenças devastadoras do arroz. Um experimento de campo foi realizado durante os anos de 2016 e 2017 para investigar a influência de diferentes parâmetros meteorológicos no desenvolvimento do BLB, bem como o cálculo de um modelo preditivo para prever a doença bem antes de seu aparecimento em campo. O conjunto de dados sazonais de incidência de doenças e fatores ambientais foi usado para avaliar cinco variedades/cultivares de arroz (Basmati-2000, KSK-434, KSK-133, Super Basmati e IRRI-9). O efeito acumulado de dados ambientais de dois anos; temperatura máxima e mínima, umidade relativa do ar, velocidade do vento e precipitação pluviométrica foram estudados e correlacionados com a incidência da doença. A temperatura média (máxima e mínima) apresentou correlação significativa negativa com a doença BLB e todas as outras variáveis; umidade relativa, precipitação e velocidade do vento tiveram uma correlação positiva com o desenvolvimento da doença BLB em variedades individuais. A análise de regressão stepwise foi realizada para indicar variáveis preditoras potencialmente úteis e para descartar parâmetros incompetentes. Os dados ambientais das safras de julho a outubro de 2016 e 2017 revelaram que, com exceção da temperatura mais baixa, todos os fatores ambientais contribuíram para o desenvolvimento da doença ao longo da safra. Um modelo de regressão múltipla de previsão de doença foi desenvolvido com base em dados de dois anos (Y = 214,3-3,691 Max T-0,508 Min T + 0,767 RH + 2,521 RF + 5,740 WS), que explicou 95% de variabilidade. Este modelo de previsão de doenças não só ajudará os agricultores na detecção precoce e gestão atempada da doença bacteriana das folhas do arroz, mas também pode ajudar a reduzir os custos de insumos e melhorar a qualidade e a quantidade do produto. O modelo será agricultor e ambientalmente amigável.

Abstract Rice is a widely consumed staple food for a large part of the world’s human population. Approximately 90% of the world’s rice is grown in Asian continent and constitutes a staple food for 2.7 billion people worldwide. Bacterial leaf blight (BLB) caused by Xanthomonas oryzae pv. oryzae is one of the devastating diseases of rice. A field experiment was conducted during the year 2016 and 2017 to investigate the influence of different meteorological parameters on BLB development as well as the computation of a predictive model to forecast the disease well ahead of its appearance in the field. The seasonal dataset of disease incidence and environmental factors was used to assess five rice varieties/ cultivars (Basmati-2000, KSK-434, KSK-133, Super Basmati, and IRRI-9). The accumulated effect of two year environmental data; maximum and minimum temperature, relative humidity, wind speed, and rainfall, was studied and correlated with disease incidence. Average temperature (maximum & minimum) showed a negative significant correlation with BLB disease and all other variables; relative humidity, rainfall, and wind speed had a positive correlation with BLB disease development on individual varieties. Stepwise regression analysis was performed to indicate potentially useful predictor variables and to rule out incompetent parameters. Environmental data from the growing seasons of July to October 2016 and 2017 revealed that, with the exception of the lowest temperature, all environmental factors contributed to disease development throughout the cropping season. A disease prediction multiple regression model was developed based on two-year data (Y = 214.3-3.691 Max T-0.508 Min T + 0.767 RH + 2.521 RF + 5.740 WS), which explained 95% variability. This disease prediction model will not only help farmers in early detection and timely management of bacterial leaf blight disease of rice but may also help reduce input costs and improve product quality and quantity. The model will be both farmer and environmentally friendly.

The effects of yeast cell wall (YCW) supplementation on growth performance, cell-mediated immune response, blood metabolites, and health scores in early-weaned male buffalo (Bubalus bubalis) calves were evaluated. Forty Nili Ravi buffalo calves were randomly divided into four groups and supplemented with four dietary treatments, namely control (animals without prebiotics), YCW-2 (yeast cell wall fed at 2 g/calf/day), YCW-4 (yeast cell wall fed at 4 g/calf/day), and cMOS-4 (commercial mannan-oligosaccharide fed at 4 g/calf/day). Milk intake, dry matter intake (DMI), and health scores were recorded daily, whereas body weight (body weight) and structural developments (hip height, wither height, heart girth, and body length) were recorded weekly. Feed efficiency and average daily gain (ADG) were calculated at the end of the experiment. Blood samples were collected fortnightly to determine glucose, non-esterified fatty acids, beta-hydroxybutyric acid (ßHBA), blood urea nitrogen (BUN), catalase, malondialdehyde, creatinine, hepatic enzymes, cholesterol, triglycerides, and total serum protein profile. The cell-mediated immune response was determined by the application of dinitrochlorobenzene directly to the skin. The results of the study revealed that supplementation of YCW and cMOS increased DMI, body weight, feed efficiency, ADG, and structural growth in buffalo calves, whereas faecal scores were significantly improved in supplemented groups compared to the control. Glucose, BUN, and ßHBA improved in supplemented animals more than in the control group, indicating bioactivity that contributed to the improvement of gut health. Supplementation with YCW improved the growth performance, physiological responses, and gut health of early-weaned male buffalo calves.

Objectives of the experiment were to determine effects of dietary hay concentration in a dry total mixed ration and its carryover effects on intake, growth performance, faecal score, and feed efficiency of weaned dairy calves. Eighteen Friesian χ Jersey weaned calves (n = 6 calves/treatment) were randomly assigned to three rhodes grass hay treatments (RG13, RG26, and RG39). The experimental diets were rhodes grass hay-based total mixed rations containing 13%, 26%, and 39% chopped hay on a DM basis. The experiment had two phases of four weeks each. In phase 1 (weeks 1-4), weaned calves were fed RG13, RG26, or RG39. Then, in phase 2 (weeks 5-8), all calves were shifted to a maize silage-based diet. All the diets were iso-nitrogenous and were fed ad libitum. Calves were housed in individual pens and had free access to water and feed. Average daily gain and daily dry matter intake were analysed as repeated measures, whereas bodyweight and feed efficiency were analysed using one-way ANOVA. In phases 1 and 2 dry matter intakes were similar. Growth rate decreased linearly with increasing concentration of hay in phase 1. Overall, daily dry matter intake, average daily gain, change in body condition score and structural measurements were not affected by dietary treatments. However, overall feed efficiency was improved for calves fed RG26 compared with RG13 and RG39. Thus, feeding a moderate level of hay had positive impacts on the transition to a silage-based TMR.