Population Dynamics of Pod Borer Helicoverpa armigera (Hubner) on Chickpea

Shivani Choudhary, H. Deshwal, J. K. Bana
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Abstract

A field experiment was carried out to study the population dynamics of pod borer Helicoverpa armigera (Hubner) on chickpea at the Agronomy Farm, College of Agriculture, Swami Keshwanad Rajasthan Agricultural University, Bikaner during two consecutive seasons i.e. rabi 2021-22 and 2022-23. The incidence commenced from first and second week of December i.e. 49th and 50th Standard Metrological Week (SMW) and disappeared in the first fortnight of January. Incidence again started from the third week of January (3rd SMW) which increased gradually and reached peak (6.4 and 5.2 larvae/ m row) in the third and second week of February (8th and 9th SMW) during first and second season. These peaks coincided with the vegetative, flowering, and podding stages. The correlation studies showed that incidence has a positive significant correlation with temperatures (p<0.01) while, morning (r = -0.609 and -0.640, p<0.05) and evening relative humidity (r = -0.728, p<0.01 & -0.666, p<0.05) showed negative significant correlation. Further, stepwise linear regression model indicated that maximum temperature as single predicator independent variable had the strongest relationship with incidence based on high R2 value (61% and 63.40%). This forewarning regression model may help the farmers to take advance decision so as to minimize the damage caused by pod borer on chickpea.
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豌豆荚螟虫 Helicoverpa armigera (Hubner) 在鹰嘴豆上的种群动态
在比卡内尔的斯瓦米-凯什瓦纳德-拉贾斯坦邦农业大学(Swami Keshwanad Rajasthan Agricultural University, Bikaner)农学院的农艺农场进行了一项田间试验,研究 2021-22 和 2022-23 连续两季鹰嘴豆上豆荚螟 Helicoverpa armigera (Hubner) 的种群动态。从 12 月的第一周和第二周,即第 49 和 50 个标准气象周(SMW)开始发病,并在 1 月的前两周消失。从 1 月第三周(第 3 个标准气象周)开始,发病率又逐渐上升,并在 2 月第三周和第二周(第 8 个和第 9 个标准气象周)达到高峰(6.4 和 5.2 头幼虫/米行)。这些峰值与植株期、开花期和结荚期相吻合。相关性研究表明,发病率与温度呈显著正相关(p<0.01),而早晨(r = -0.609 和 -0.640,p<0.05)和傍晚相对湿度(r = -0.728,p<0.01 和 -0.666,p<0.05)呈显著负相关。此外,逐步线性回归模型表明,最高气温作为单一的天敌自变量,与发病率的关系最为密切,R2 值较高(61% 和 63.40%)。这一预警回归模型可帮助农民提前做出决策,从而将豆荚螟对鹰嘴豆的危害降到最低。
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