MSc

Ginger (Zingiber officinale), a member of the Zingiberaceae family that originated in Indo-China, is a prominent tropical plantation crop used as a spice in a variety of culinary preparations and medicinal formulations. Because of its spicy flavor and distinctive aromatic properties, ginger gained popularity across the world through spice trade (Nybe and Miniraj, 2005). The primary objective of the research is to study the micro-meteorological aspects using different mulches and to determine the crop-weather relationship of ginger. Ginger variety Maran was raised at Instructional Farm (IF) Vellanikkara, by adopting split plot design. The experiment was laid out with four different dates of planting (1st June, 15th June 1st July and 15th July) as main plot treatment and three mulches (Green leaves, paddy straw and dry coconut leaves mulch) as sub plot treatments. Using SPSS software, a correlation analysis of the crop-weather relationship was studied. Principal Component Analysis (PCA), a dimensionality reduction technique in statistics is used to reduce the multicollinearity of large sets of weather parameters. Regression analysis was used to build models using the developed principal components. As an additional method of yield prediction, the multiple regression models were created by the enter method. The production and quality of ginger are significantly influenced by the optimum planting time under different agro-climatic conditions. The growth, performance and yield of ginger are affected by either early or delayed planting. The selection of optimum planting time is influential in deciding the germination percentage, number of tillers, growth, phenology, yield and finally the quality of the rhizome (Kandiannan and Chandragiri, 2008). Mulching with organic limits the soil temperature fluctuations and evaporative loss of soil moisture from the surface, thus modifying the microclimate to a better one that is conducive to crop development (Zaman et al., 2002). The life cycle of ginger was characterized by four distinct phenological stages, i.e., planting to 50% germination, 50% germination to active tillering, active tillering to bulking and bulking to physiological maturity. Duration taken for each phenophase found to vary
for all the four dates of planting in all the three mulches. Compared to late plantings, the June 1st planted crop required more days to germinate and longer days to reach physiological maturity. The plant biometric characters like plant height, number of tillers was higher in June 1st and June 15th planting whereas number of leaves, leaf area, and dry matter accumulation were found to be more in earlier dates of planting i.e., June 1stplantng. In mulching practices, paddy straw mulch had superior yield and it was on par with green leaves mulch. The yield produced by June 1st planting was significantly highest than other dates of planting (June 15th, July 1st, July 15th). The paddy straw mulch had more soil moisture content at 5cm and 15cm depth and recorded higher plant height, number of leaves, leaf area, number of tillers and dry matter accumulation. The observed soil temperature fluctuation was low in case paddy straw mulch at 5cm and 15cm depth for both forenoon and afternoon hours followed by green leaves mulch and dry coconut leaves mulch. To predict the crop growth and maturity, growing degree days serves as an excellent indicator, as it measures heat and energy consumption by the plant (Kandiannan et al., 2013). Because of the sudden rise in daily maximum and minimum temperatures at later stages of growth under late planting, that caused the shortening of reproductive stages and forced the crop to mature faster, so the crop sown on June 1st recorded significantly higher accumulated growing degree days, accumulated heliothermal units, accumulated photothermal units, accumulated hydrothermal units, normalized difference vegetation index followed by crop planted on, June 15th, July 1st and July 15th planting. This might have contributed highest yield in June 1st planting. The yield and other yield characteristics of the ginger crop are significantly influenced by the weather experienced during different phenophases. It was found that a higher in maximum and minimum temperature, bright sunshine hours and evaporation during the germination stage had a positive impact on yield. The higher yield in early planting dates (June 1st and June 15th) was influenced by increased total rainfall, rainy days, and vapor pressure deficit during active tillering to bulking. Likewise, the windspeed, evaporation and bright sunshine hours had a negative relation with the yield from bulking
to physiological maturity. At any phenological stages soil moisture showed significant positive correlation with yield whereas soil temperature showed significant negative correlation. Principal Component Analysis (PCA) was carried out and equations were developed using best principal components in regression analysis for predicting yield. The PCA-based regression model performed best for yield prediction when compared to a linear regression model. It was found that June 1st planting with paddy straw mulch was the best treatment with higher benefit cost ratio for the dates of planting studied.

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