CROP–WEATHER INTERACTION AND CORRELATION ANALYSIS OF SUGARCANE (SACCHARUM SPP.) YIELD IN NORTH COASTAL ZONE OF ANDHRA PRADESH
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Authors
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PADMAVATHI P V
Regional Agricultural Research Station, Anakapalle - 531001 Acharya N.G. Ranga Agricultural University, Lam, Guntur, Andhra Pradesh, India
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ADILAKSHMI D
Regional Agricultural Research Station, Anakapalle - 531001 Acharya N.G. Ranga Agricultural University, Lam, Guntur, Andhra Pradesh, India
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RAMANA MURTHY K V
Regional Agricultural Research Station, Anakapalle - 531001 Acharya N.G. Ranga Agricultural University, Lam, Guntur, Andhra Pradesh, India
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KUMARI M B G S
Regional Agricultural Research Station, Anakapalle - 531001 Acharya N.G. Ranga Agricultural University, Lam, Guntur, Andhra Pradesh, India
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GOURI V
Regional Agricultural Research Station, Anakapalle - 531001 Acharya N.G. Ranga Agricultural University, Lam, Guntur, Andhra Pradesh, India
Keywords:
Climate variability, Correlation analysis, Meteorological factors, Sugarcane yieldAbstract
Eleven sugarcane clones were evaluated in a randomized block design over two consecutive
plant crop seasons (2022–23 and 2023–24) at the Regional Agricultural Research Station,
Anakapalle, to quantify the influence of key meteorological parameters on cane yield. Pearson’s
correlation analysis of five weather variables – rainfall, number of rainy days, maximum temperature,
minimum temperature and bright sunshine hours (BSSH) – revealed that rainfall, rainy days and
minimum temperature were positively correlated with cane yield (r = +0.273, p < 0.05), while
maximum temperature and BSSH showed significant negative correlations (r = ”0.273, p < 0.05).
Among the clones, 2012A 340 recorded the highest mean yield of 123.84 t/ha, followed by
2012A 319 (123.06 t/ha), while 2013T 124 recorded the lowest (73.84 t/ha). Weather parameters
during the tillering phase were most influential in determining final yield. These results demonstrate
that moderate precipitation and favourable nocturnal temperatures during early crop growth are
critical drivers of productivity in the north coastal zone of Andhra Pradesh, and provide a basis
for developing climate-informed agronomy and clone selection strategies
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