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Not AvailableUsing Standardized Precipitation Index (SPI), an analysis on incidence and severity of droughts occurred in arid Rajasthan during the period 1960-2009 showed that the drought frequency varied from 32 years at Barmer to 24 years at Hanumangarh. The decades 1960-1969, 1980-89 and 2000-2009 experienced highest number of moderate and severe droughts. Year-wise and monthly SPI was also calculated for Barmer, Churu and Jodhpur, to know drought severity during the cropping period of July, August and September. To validate the SPI as a drought indicator, a multiple-linear regression analysis between SPI of July, August and September as independent variables and pearl millet grain yield as dependent variable was made. The regression model using SPI predicted pearl millet yield up to 83% of Barmer district, 47% of Churu district and 62% of Jodhpur district, thus the SPI is found useful as an indicator for monitoring drought conditions in arid RajasthanNot Availabl

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Not AvailableDifethialone, a second generation anticoagulant rodenticide was assessed for its susceptibility and acceptance in baits against Meriones hurrianae. Fresh loose bait containing difethialone (25 ppm) prepared in pearl millet grain resulted in 100 per cent mortality during no-choice test in one day feeding, Mean period to death was 5.90 days with an average poison intake of l.l7 + 0.09 mg/Kg/day. Poison bait acceptability was fairly good as observed by non-significant differences in the consumption pattern of poisoned and plain bait in choice test. Single day exposure of difethialone (0.0025%) accounted for 70 per cent mortality of test animals from 5 to I I days (Av. 7.86), whereas, two days exposure yielded 90 per cent mortality in choice test. The compound did not induce bait shyness in the surviving test animals. The death of the gerbils was due to excessive bleeding through nose, anal aperture and ears. These trials revealed that difethialone is a potent rodenticide for containing this predominant rodent species inhabiting the Indian arid agro-ecosystemNot Availabl

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Not AvailableA field experiment was conducted during rainy season (June–October) of 2016, to study the effect of different integrated crop management (ICM) modules on productivity and profitability of direct-seeded basmati rice. The experiment was laid out in a randomized block design with eight treatment combinations, i.e. ICM modules (ICM1 to ICM8). The study indicated that the yield attributes, grain yield (4.03 t/ha), harvest index, as well as gross ( 96,253/ha) and net ( 50,693/ha) returns as well as gross B: C ratio (2.11) of rice crop were significantly higher in the ICM7, i.e. zero till (ZT)-summer mungbean residue retention (SMB-RR) + ZT- direct seeded rice (DSR) + wheat residue @ 3 t/ha + 75% of recommended dose of fertilizers @ 100 : 50 : 50 kg N : P2 O5 : K2 O/ha (RDF) (N through Zn coated urea/ZCU) + glyphosate as pre-plant (PP) @ 1 kg a.i./ha + pretilachlor as pre-emergence (PE)@ 0.75 kg a.i./ha followed by bispyribac-sodium @ 25 g a.i./ha as post emergence (POE) at 25 days after sowing(DAS) + need based water management, disease and integrated pest management, with comparison to othermodules. The escalation of cost due to transplanting was increased 5,045/ha compared to direct–seeded rice.The increase in net returns with ICM7 was 36.7, 41.4 and 9.3% over ICM1, conventional transplanting/TPR + 100% of RDF + butachlor-PE @ 1 kg a. i./ha + 1 hand-weeding (HW); ICM6 , ZT-DSR + wheat residue @ 3 t/ha + 75% RDF + AMF + NPK-biofertilizer + glyphosate as PP @ 1 kg a.i./ha + pretilachlor-PE @ 0.75 kg a.i./ha followed by bispyribac-sodium @ 25 g a.i./ha as POE at 25 DAS + 1 HW and ICM8 , ZT-SMB-RR + ZT- DSR + wheat residue @ 3 t/ha + 50% RDF + AMF + NPK-bf + glyphosate as PP @ 1 kg a.i./ha + pretilachlor-PE @ 0.75 kg a.i./ha followed by bispyribac-sodium @ 25 g a.i./ha as POE at 25 DAS + 1 HW, respectively. Hence, the superior ICMmodule, i.e. ICM7 may be useful for improving profitability and B : C ratio of direct-seeded rice with respect to other modules.Not Availabl

Predição do peso vivo a partir de medidas corporais em animais mestiços Holandês/Gir Prediction of live weight based on body measurements in crossbred animals Holstein/Gir

O objetivo deste estudo foi investigar as relações entre o peso corporal e as medidas corporais altura de garupa (ag), comprimento de garupa (cg), comprimento corporal (cc) e perímetro torácico (pt), em bovinos oriundos principalmente do cruzamento das raças Holandês e Gir. Foram utilizados dados de 483 vacas, 469 novilhas e 62 machos, de três rebanhos distintos, analisados separadamente para cada categoria a fim de estabelecer equações polinomiais dos pesos em relação às medidas corporais. As correlações simples do peso corporal com pt, cc, cg e ag foram respectivamente 0,807; 0,440; 0,187 e 0,504 para vacas; 0,928; 0,735; 0,819 e 0,880 machos, e 0,942; 0,748; 0,902 e 0,573 para novilhas. Embora as regressões de peso corporal em relação ao cc e cg tenham sido significativas (P<0,05), o aumento da porcentagem de explicação das variações do peso corporal obtido com a inclusão destas medidas, em adição ao pt, não parece justificar o custo das medições. As equações de predição do peso corporal em função do pt foram as seguintes: para vacas, peso = 12.174 - 187,410 pt + 0,97196960 pt&sup2; - 0,00162382 pt&sup3;, para novilhas, peso= 1.717-35,167 pt + 0,238978 pt&sup2; - 0,00046260 pt&sup3; e, para machos, peso = -3.862+76,014 pt-0,488837 pt&sup2;+ 0,00109755 pt&sup3;.<br>The objective of this study was to investigate the relationship between hip height (ag), rump length (cg), body length (cc) and heart girth (pt) with live body weight of crossbred animals, mainly from the cross between Holstein and Gir breeds. Data on 483 cows, 469 heifers and 62 males in three herds were analyzed for each category using polynomial regression equations of body weight on measurements. The correlations between body weight and pt, cc, cg and ag were, respectively 0.807, 0.440, 0.187 and 0.504 for cows, 0.928, 0.735, 0.819 and 0.880 for males and 0.942, 0.748, 0.902 and 0.573 for heifers. Although the regressions of body weights on cc and cg were significant (P<0.05), the additional goodness of fit of a model that includes these two traits in addition to heart girth does not justify the extra cost for recording these traits. The prediction equations were: for cows, body weight = 12174-187.410 pt+0.97196960 pt&sup2;-0.00162382 pt&sup3;, for heifers, body weight = 1717-35.167pt+0.238978pt&sup2;-0.00046260pt&sup3; and for males, body weight = -3862+76.014pt-0.488837pt&sup2;+0.00109755pt&sup3;