Browsing by Author "Shajeesh Jan, P"

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Crop simulation in groundnut (Arachis hypogaea L.) using DSSAT-CROPGRO model
(Department of Agricultural Meterology, College of Horticulture, Vellanikkara, 2020) Vinu, K S; Shajeesh Jan, P
The field work was conducted at Instructional Farm, Vellanikkara by adopting split plot design with five replications. Variety used in the experiment was TNAU CO-6. Four dates of sowing such as November 1st, November 15th, December 1st and December 15th were used as main plot treatments and three irrigation levels of IW/CPE ratio 0.6, 0.8 and 1.0 were used as sub plot treatments. The November 1st planting was produced significantly higher yield compared to the November 15th, December 1st and December 15th planting. All the growth characters like plant height, number of leaves and dry matter accumulation were found to be highest during November 1st planting. Shelling percentage and harvest index recorded during November 1st planting was on par with December 1st planting. Among the three irrigation treatments plant height, number of leaves, yield, shelling percentage and harvest index were found to be higher in IW/CPE ratio 1.0. Number of days taken to reach each phenophases were different under each dates of planting. Maximum duration was recorded during December 1st planting and minimum duration was recorded during November 1st planting. Crop weather relationship studies suggested that maximum temperature and bright sunshine hours recorded during pegging to pod formation period showed a negative influence on yield and phenology. Only rainfall during this period showed a positive influence on yield. The efficiency of every crop model depends on how accurately the genetic coefficients were calibrated. The genetic coefficients for DSSAT-CROPGRO Peanut model were calibrated for the variety TNAU CO-6 using the data sets generated during the field experiment. The goodness of fit between observed and simulated values were evaluated using root mean square error and d- stat index. The simulated value of yield, yield attributes and phenology of groundnut crop using DSSAT-CROPGRO Peanut model was in good agreement with observed value.
Ginger (Zingiber officinale) yield variability under different climate change scenarios
(Department of Agricultural Meteorology, College of Agriculture, Vellanikkara, 2021) Fathima Sona, N; Shajeesh Jan, P
Ginger (Zingiber Officinale) is an important commercial spice crop grown from very ancient times in India. Because of its valued aroma and lemon flavour, it has spread to tropical and subtropical regions from the Indo-China region and became one of the earliest oriental spices known to Europe (Nybe and Miniraj, 2005). Species diversity and yield of spices are threatened due to the ever increasing temperature and changes in precipitation pattern. Since spices are grownboth in plains and high altitudes, it is important to assess the long term climatic changes within a region and its influence on productivity (Sing, 2008). The present experiment was aimed to study the impact of climate change on growth and yield aspects of ginger crop under climate change scenarios of RCP 4.5 and 8.5. Ginger varieties, Maran and Varada were raised at Instructional Farm (IF) Vellanikkara, by adopting split plot design. The experiment was laid out with four dates of planting (15th May, 1st June, 15th June and1 st July) as main plot treatment and two varieties (Maran and Varada) as sub plot treatments. Fourreplications were given for the experiment. The crop weather relationship was analysed with correlation with the help of SPSS software. Principal Component Analysis (PCA), a multivariate statistical technique was done in order to reduce the multicollinarity of large data sets of weather variables to substantially smaller sets of new variables. The developed principal components were utilized for model development using stepwise regression analysis. The future climate was estimated by climate change projections generated using CCSM4 models for 2030, 2050 and 2080based on scenarios RCP 4.5 and 8.5. The life cycle of ginger was characterized by four distinct stages, ie., sowing to 50% germination, 50% germination to active tillering, active tillering to bulking and bulking to physiological maturity. Duration taken for each phenophases found to vary for all the four date of planting in both Maran and Varada. The May 15th date of planting took more days to germinate compared to other date of plantings. The number of days taken for sowing to germination was positively correlated with maximum temperature, minimum temperature, rainfall and soil temperature in both varieties. The number of days taken to attain physiological maturity also foundto be more in May 15th planted crop. The weather experienced during various phenophases have significant influence on yield and other yield attributes of ginger crop. It was found that the yield of both varieties of ginger havepositive correlation with minimum temperature at all the four phenophases except bulking t o physiological maturity. Maximum temperature observed at sowing to germination was positively correlated with yield of both Maran and Varada. At active tillering to bulking stage, rainfall, rainy days and minimum temperature showed a significant positive correlation with yield, but maximum temperature, wind speed and solar radiation showed a significant negative correlation with yield. The Principal Component Analysis was carried out for ginger varieties Maran and Varadaby using the weather parameters experienced in four stages ie., sowing to 50% germination, 50% germination to active tillering, active tillering to bulking and bulking to physiological maturity. Weather parameters considered include maximum temperature (Tmax), minimum temperature (Tmin), rainfall (RF), rainy days (RD), relative humidity (RH), wind speed (WS) and solar radiation (SRAD). The statistical model was developed with principal components as independentand yield as dependent variable. Projected climatic conditions of Vellanikkara, Thrissur under climate change scenarios of RCP 4.5 and 8.5 were downscaled from CCSM4 model. The projected climate of near century (2010-2039), midcentury (2040-2069) and end of century (2070-2099) were downscaled for the study. The projected yield of the ginger variety Maran was found to decrease at all planting datesexcept July 1 st under both the RCP 4.5 and 8.5 scenarios. Under RCP 4.5 scenario, more reductionwas reported at the end of the century on May 15th (38%), June 1st (29%) and June 15th (54.5%) dates of planting. July 1 st planted crop reported increase in projected yield under near, mid and end of centuries. More increase in yield was observed in midcentury (17.7%). Under RCP 8.5 scenario,May 15th (50.2%) and June 1st (20.3%) dates of planting reported the highest percentage of yield reduction during midcentury. June 15th date of planting, recorded the highest yield reduction of 52.6% at the end of the century. July 1st planting date recorded increase in yield and it was more in end of century (15.5%). In case of Varada, under RCP 4.5 scenario, more yield reduction was reported at the end of century during May 15th (24%) and June 1 st (7.2%) dates of planting. DuringJune 15th planting dates, near and end of century reported the same yield reduction of 24.9%. TheJuly 1 st planted crop reported an increase in yield, which was more (15.5%) during end of century. Under RCP 8.5 scenario, more yield reduction was observed in midcentury on May 15th (28.8%) date of planting. June 1st (6.6%) and June 15th (19.9%) dates of planting reported more reduction in end of century. July 1 st reported more increase of 24% in end of century.
Leaf and spadix phenology of coconut (Cocos nucifera L.)
(Department of Agricultural Meteorology, College of Horticulture, Vellanikkara, 2004) Shajeesh Jan, P; Prasada Rao, G S L H V
The field experiment entitled "Leaf and spadix phenology of coconut (Cocos nucifera L.) was conducted at Department of Agricultural Meteorology, College of Horticulture, Vellanikkara, during the period from February 2002 - June 2003. The investigations were undertaken with the following objectives such as to understand the seasonal influence on leaf and spadix production and their interval on different cultivars of coconut namely Tiptur Tall, Kuttiadi (WCT), Kasargod (WCT) and Komadan (WCT) including the duration of spadix emergence and on leaf and spadix phenology of coconut. All the four coconut cultivars behaved uniformly with respect to seasons in terms of functional leaves, spathe and female flower production. Nevertheless, they responded differently to different weather variables. However, Tiptur Tall was tolerant to weather aberrations and superior in terms of its floral and yield characters. The study indicated that favourable weather conditions during post monsoon season might have resulted in maximum absorption and translocation of food material during the same season in which maximum number of functional leaves were noticed whereas the rise in temperature, vapour pressure deficit coupled with low rainfall and bright' sunshine hours led to higher leaf shedding during summer. The favourable weather conditions such as optimum soil moisture, maximum temperature and bright sunshine hours during the primordium initiation (29 months prior to the spathe emergence) resulted in maximum spathe emergence during post monsoon. The unfavourable weather conditions such as low rainfall, less rainy days and high maximum temperature coupled with bright sunshine during the primordia initiation stage would have played a major role in low emergence of spathes during the southwest monsoon. The study also indicated that low minimum temperature, and optimum temperature range, wind speed, vapour pressure deficit, evaporation and sunshine hours resulted in maximum spathe duration during winter. The reasons for maximum spadix emergence during summer season can be attributed to the maximum number of spathes present on the crown during winter in which the duration from spathe to spadix was also more. When coconut spathes were exposed to a range of higher atmospheric temperature it may cause for early spadix emergence. In contrast, the number of spathes present on the crown was less during the southwest monsoon and hence the opening of spathe during the ensuing post monsoon was less. The high female flower production during summer can be attributed to the favourable weather prevailed during primordia initiation (32 months prior to the spadix emergence) and ovary development (6-7 months before the spadix emergence,). High maximum temperature, temperature range, sun shine hours and high vapour pressure deficit and prolonged dry spell during the above critical stages caused to the low female flower production during post monsoon season. The number of female flowers produced could be explained up to 99 percent due to weather prevailed during the above two critical stages in the case of Kuttiadi and Kasargod. The relationship between the female flower production and button shedding revealed that when female flower production was high button shedding was also high, while not in the case of Tiptur Tall. It also revealed that button shedding was more in summer 2003 when compared to that of summer 2002. It was attributed to the occurrence of prolonged dry spell from November 2002 to 8th June 2003 when compared to that of summer 2002. In addition to the prolonged dry spell during the above season, the occasional intermittent rains in the form of cloud burst/ summer showers might have caused imbalance in nut setting resulting in immediate fall of buttons. The spathe duration and button shedding in coconut responded positively to the growing degree days. It revealed that that both the above phenological events may respond to thermal regime. Future line of work Such studies, if undertaken for at least five years, will be quite useful in understanding the response of biotic events to weather variations. In addition, the information can be used in crop improvement programmes of coconut.
Phenology and yield of strawberry (Fragaria X ananassa Duch.) under varied weather conditions
(Department of Agricultural Meteorology, College of Agriculture , Vellanikkara, 2025-02-04) Ajaykumar, V C; Shajeesh Jan, P
Strawberry (Fragaria × ananassa Duch.), a widely consumed fruit of the Rosaceae family, is an octoploid hybrid (2n=8x=56) derived from Fragaria chiloensis and Fragaria virginiana. Renowned for its adaptability to diverse climatic conditions, the crop thrives across temperate to tropical regions. This study aimed to investigate the phenology of the strawberry variety 'Winter Dawn' under varying weather conditions and analyze the crop weather relationship to predict yield using statistical and artificial intelligence techniques. Experiments were conducted at the Regional Agricultural Research Station, Ambalavayal, employing a randomized block design (RBD) in open-field conditions and a completely randomized design (CRD) in polyhouse conditions. Five planting dates (1st September, 15th September, 30th September, 15th October and 30th October) were evaluated in the open field, while a single planting date (30th September) was tested under two polyhouse conditions. The study revealed that planting time significantly influenced the yield and quality of strawberries, with optimal weather conditions enhancing vegetative growth and fruit development. Phenological observations indicated six distinct stages: inflorescence emergence, first flower opening, fruit set, full flowering, fruit development, and fruit ripening. September 30th planting recorded superior growth parameters, including plant height, spread, number of leaves and crown number, and achieved the highest yield across both open field and polyhouse conditions. Among polyhouse treatments, the Indian polyhouse demonstrated superior performance in terms of growth and yield compared to the Dutch polyhouse, attributed to its higher light intensity and lower humidity levels, which promoted photosynthesis and nutrient assimilation. Weather parameters critically influenced phenophases and yield. Correlation analysis indicated negative impacts of higher temperatures and suboptimal humidity during later growth stages, while increased bright sunshine hours and reduced minimum temperatures during early phenophases positively influenced vegetative and reproductive development. In polyhouses, the Dutch polyhouse's higher humidity and lower light intensity curtailed growth and yield compared to the Indian polyhouse. For yield prediction, Random Forest emerged as the most effective model among machine learning techniques evaluated, including AdaBoost, Gradient Boosting, and Stacking. Feature importance analysis underscored the pivotal role of weather variables in determining yield across phenophases. This study highlights the importance of optimizing planting time and microclimatic conditions to enhance productivity and highlights the potential of machine learning models for accurate yield forecasting, thereby aiding informed agricultural decision-making .
Weather service to farmers
(Department of Agricultural Meteorology, College of Horticulture, Kerala Agricultural University, 2020) Vinu, K S; Shajeesh Jan, P