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Plant Science Today (PST)

Research Articles

Vol. 13 No. sp5 (2026): Recent Advances in Agriculture

The relationship between various weather parameters and their influence on the growth and flowering of African marigold under continuous transplanting conditions throughout the year

DOI
https://doi.org/10.14719/pst.10443
Submitted
3 July 2025
Published
15-07-2026

Abstract

Climate variability poses a significant threat to agricultural sustainability; consequently, practical solutions are necessary to increase agricultural production. Planting time is a crucial factor influencing the growth and flower production of marigold, particularly when cultivated throughout the year. This study aims to determine the optimal growth period for African marigold in North Indian subtropical plains, where it is cultivated as a year-round cash crop. The research employed a randomised complete block design (RCBD), with 12 transplanting dates for marigold implemented from February 15th to January 15th of each year. The findings revealed that vegetative parameters, specifically maximum plant spread and higher number of primary branches (PB), along with physiological and yield traits such as fresh flower weight (FW), chlorophyll SPAD index, carotenoid content (CR) and flower yield per square meter, were optimally higher when the crop was transplanted on August 15th, followed by July 15th. The yield of flowers per square meter was observed maximum in August 15th transplanting, which decreased by approximately 38 % and 44 % when crop was transplanted during July and September, respectively. For other planting dates, the mean reduction in flower yield per square meter ranged from 66 % in February to 82 % in December transplanted crops compared to August transplanting. Phenological stages, color break stage and flowering duration occurred earlier in crops transplanted on October 15th. This study demonstrates that maximum plant growth development and flower production were observed when transplanting was done on July 15th and August 15th. The principal component analysis (PCA) biplot indicates clear associations between weather variables and plant growth and yield attributes. Plant height (PH), PB, FW and CR and SPAD value (SPD) show a positive correlation with sunshine hours (SUN) and maximum temperature (MXT) and a negative correlation with excessive rainfall, suggesting warm and spring seasons favour vegetative growth and pigment accumulation.

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