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Volume-28--Number-2


ABUNDANCE OF MAJOR INSECT-PESTS OF INDIAN BEAN IN RELATION TO MAJOR WEATHER FACTORS


Department of Entomology, N.M. College of Agriculture
Navsari Agricultural University, Navsari, Gujarat


Author(s): 

M.A GANGURDE AND SUSHIL KUMAR


Abstract: 

Abundance of major insect-pests of Indian bean cv. Gujarat Papdi was studied at standard week wise interval during 2011-12 at Navsari Agricultural University, Navsari. Whitefly, Bemisia tabaci (Gennadius) population commenced from 41 standard week (SW) attaining peak (8.28/leaf) during 4 SW. It indicated significant negative correlation with temperature (maximum, minimum and average) ('r' = -0.6463, -0.5697 and -0.6162). Total contribution of all the weather factors was 31.62 per cent indicating significant multiple correlation coefficient (R = 0.5623). Leaf miner,  Liriomyza trifoli (Burgess) oriented leaf damage commenced from 41 SW attaining peak status (34.86 %) on 5 SW exhibiting significant positive correlation with wind velocity ('r'= 0.6270) and negative correlation with temperature (maximum, minimum and average) ('r'= - 0.6157, -0.4958 and -0.5562).Total impact of all the weather factors was 41.54 per cent indicating significant multiple correlation coefficient (R= 0.6445). Appearance of Aphid, Aphis craccivora (Koch) colony commenced from 48 SW attaining peak (3.65 aphid index) on 3 SW indicating significant positive correlation with wind velocity ('r'= 0.5160) but significant negative correlation with temperature (maximum, minimum and average) ('r' = -0.7219, -0.5619 and -0.6398). The multiple correlation coefficient (R= 0.7014) was significant explaining 49.16 per cent variation due to all the weather factors. Pod borer, (Hubner) population commenced on 49 SWattaining peak (6.21 larvae/plant) on 4 SW. It indicated significant positive correlation with wind velocity ('r'= 0.4590) and significant negative correlation with temperature (maximum, minimum and average)('r' = -0.6992, -0.5701 and -0.6376). The multiple correlation coefficient (R= 0.6333) explained 40.11 per cent variation due to all the weather factors.