Modelling the Effect of Microclimate on Mulched Watermelon (Citrullus lanatus) Crop Grown under Low Tunnel with Different Sowing Dates
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Date
2019
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MPUT, UDAIPUR
Abstract
Watermelon (Citrullus lanatus) is great demanding vegetable because of its lots of health benefits and high nutrition value. The field experiment was conducted at the Plasticulture Farm of CTAE, MPUAT Udaipur, during the period of 15th December, 2018 to 20th May 2019. The experiment was laid out in randomized block design with three replications. There were total eight treatment with and without mulch, along with low tunnel and four dates of sowing of watermelon i.e., 15th December date of sowing and with low tunnel and without poly mulch (T1), 15th December date of sowing and with low tunnel and with poly mulch (T2), 1st January date of sowing with low tunnel and without poly mulch (T3), 1st January date of sowing and low tunnel and with poly mulch (T4), 15th January date of sowing and low tunnel and without poly mulch (T5), 15th January date of sowing and low tunnel and with poly mulch (T6), 1st February date of sowing and without poly mulch (Control) (T7), 1st February date of sowing and with poly mulch (Control) (T8). It was observed that the highest water requirement (421.96 mm) for 15th January date of sowing and highest water use efficiency (900.87 kg/ha-cm) for 15th December date of sowing with low tunnel and poly mulch condition. The average weekly soil temperature observed higher under poly mulch condition which was 1.7 °C to 3.9°C higher than without mulch condition. There was change in the relative humidity inside low tunnel about 1.53 to 27.95 % for every week compared to open field.
The developed prediction model (equation) by SPSS is useful for prediction of watermelon crop yield by use of temperature and relative humidity values for mulch and without mulch condition. It was observed that R2 is higher, which is acceptable range of R2 to fit the model. In this regression analysis value of R2 approaching to 1 and lower values of RMSE indicated the best fit model for prediction of watermelon crop yield. Vine length (185.63 cm), number of nodes (96.5), number of leaves (265.23), number of fruits per vine (4), average fruits weight (4.68 kg), fruit yield/vine (2.40 kg), fruit yield/plot (72.1 kg/plot) and yield (24.04 t/ha) were highest in 1st January date of sowing with low tunnel and poly mulch condition (T4). Result found that, maximum output-input ratio was observed in treatment T4 (2.46:1) and minimum output-input ratio
91
was reported in treatment T5 (1.67:1). Therefore, considering the 1st January date of sowing with low tunnel and mulching is best for watermelon sowing.
Description
Modelling the Effect of Microclimate on Mulched Watermelon Crop Grown under Low Tunnel with Different Sowing Dates
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Dineshbhai P.C