bluuebunny/crossref_metadata_2025 huggingface dataset:
Sensitivity analysis of CROPGRO- cotton model to intra-seasonal climatic variability in middle Gujarat
Authors: D. D. PATIL  , VYAS PANDEY  , VIPUL KAPADIA  , A. C. SADHU
Published: December 2021

The CROPGRO-Cotton model was first calibrated and validated with the six years (2011-12 to 2016-17) of experimental data collected at Regional Research Station, A.A.U., Anand for two cultivars of cotton (DCH 32 and G. Cot. Hy. 102) to study the effect of intra-seasonal climatic variability on seed cotton yield. The model sensitivity analysis was carried out by incremental change in climatic parameters (maximum and minimum temperature from -30 to +30C) and rainfall (-25% to +25%). Results revealed that elevated temperature had negative effect on seed cotton yield and reduced temperature had positive effect on seed cotton yield. The varieties DCH 32 was slightly less affected by the temperature variation than G. Cot. Hy. 102. Temperature variation during October to December was found to have maximum effect on cotton crop. The effect of minimum temperature on seed cotton yield was more than that observed with maximum temperature.Cotton crop was affected more by variation in rainfall during September in comparison to that of July and August.
Maize yield projections under different climate change scenarios in different districts of Punjab
Authors: NAVNEET KAUR  , PRABHJYOT KAUR
Published: December 2021

The study aimed to find out possible changes in climatic data (temperature and rainfall) from the regional climate model viz. PRECIS(Providing Regional Climates for Impact Studies)under different SRES scenarios (A1B, A2 and B2 scenario) by the mid (2021-2050) and end (2071-2100) century at six locations of Punjab representing different agroclimatic zones and to study their impact on maize yield using the crop growth simulation model.The results revealed that the different zones of the state are expected to bewarmer during the mid century and this trend has been projected to continue by the end of century because of increase in maximum and minimum temperature at all the locations.The CERES-Maize simulated significant decrease in duration and grain yield of maize crop under projected climate scenarios. The reduction in the crop duration and grain yield was found to be more under the A1B and A2 scenario (high emission scenario) followed by B2 scenario (low emission scenario)due to adverse effects on crop physiology.
Climate change impacts on intensity duration frequency curves of precipitation: A case study of Shiraz synoptic station, Iran
Authors: A.ROSHAN  , H. SEDGHI  , R.A.SHARIFAN  , J.PORHEMMAT
Published: December 2021

Intensity-duration-frequency (IDF) curves are among the standard design tools for many engineering applications such as urban drainage management. Since climate change may considerably affect precipitation, updating of IDF curves is highly necessary. The present study aims to examine the impacts of climate change on IDF curves of Shiraz synoptic station using downscaled outputs of Hadcm3 AOGCM under various emission scenarios (A1B, A2,B1) applying larswg-5 model for the period of 2046 to 2065. The fitted Gumbel distribution was used to estimate the maximum short-term precipitation quantiles in the base period (1968-2000) and the verified empirical Bell type equation was used for the future period. The results show that the mean of maximum daily precipitation and annual precipitation will decrease in the future. Also, the maximum precipitation intensities up to 60 min duration will reducefrom 0.15 mm hr-1 to about 10.79 mm hr-1 compared to the observed period in all returns periods and various scenarios. Overall, there were no tangible changes in intensities for durations higher than 60 min. The highest reduction in precipitation intensity would be at the 20 min duration with 100-year return period in the A2 scenario.
Crop coefficients of Bt. cotton under variable moisture regimes and mulching
Authors: G. V. PRAJAPATI  , R. SUBBAIAH
Published: December 2021

An experiment was undertaken for two years (2013-14 and 2014-15) on sandy loam soils of Junagadh (21°30’ N, 70°27’ E) to determine crop coefficients of Bt. cotton under three mulch treatments (M1- silver black plastic mulch, M2- biodegradable plastic mulch, M3- wheat straw mulch and C - control) with two irrigation regimes (I1- 1.0 IW/ETc, I2-0.8 IW/ETc). Actual evapotranspiration was estimated using soil moisture sensors. Results revealed that adjusted FAO Kc predicts higher value than sensor based Kc values at both irrigation regimes. Silver black plastic mulch recorded lower crop coefficient values at all growth stage of Bt. cotton compared to biodegradable plastic mulch, wheat straw mulch and control. Sensor based Kc ini and Kc-devvalues of silver black plastic mulch observed 72.2, 29.0 and 66.9 and 14.8 per cent lower than control at 1.0 IW/ETc and 0.8 IW/ETc respectively. Overestimated adjusted FAO Kc values caused a loss of 78.1mm and 66.5mm of precious water at 1.0 IW/ETc and 0.8 IW/ETc respectively. This study admonishes blind adoption of published FAO Kc curves for mulch conditions.
Study on paddy phenomics ecosystem and yield estimation using space-borne multi sensor remote sensing data
Authors: MAHESH PALAKURU  , KIRAN YARRAKULA
Published: December 2021

In the present study three phenological stages of rice namely transplanting stage, heading stage and harvesting stages were derived from MODIS EVI data. SMAP L-band was used to identify the puddling field. The performance of the estimated phenological stages from MODIS EVI and SMAP were evaluated with field data and root mean square error (RMSE) was calculated. The rice yield estimation was also performed by application of second order polynomial method. The performance of the polynomial model showed good results with the coefficient of determination of 0.74.
Drought assessment for kharif rice using standardized precipitation index (SPI) and vegetation condition index (VCI)
Authors: DEEPA B. KAMBLE  , SHWETA GAUTAM  , HIMANI BISHT  , SHRADDHA RAWAT  , ARNAB KUNDU
Published: December 2021

The monthly weather data for 31 years from 1985-2015 was used to analyze the extent of meteorological drought using standardized precipitation index (SPI) over Allahabad, Kanpur and Lucknow. MODIS NDVI data from 2000-2015 was used for monitoring of agricultural drought through NDVI based vegetation condition index (VCI) for all the three districts. The monthly SPI and VCI values from July to October were correlated with productivity index (PI) of kharif rice.Both the indices (SPI and VCI) were positively correlated with PI for all the districts. In Allahabad SPI and VCI during September month showed a significant correlation (0.70**& 0.61*) while in Kanpur VCI during October and SPI of July and August were significantly correlated with PI of kharif Rice. The multiple regression equation developed for predicting kharif rice PI in Allahabad, Kanpur and Lucknow districts explained 69 to 76 per cent variabilityin PI.
Comparison of Lasso and stepwise regression technique for wheat yield prediction
Authors: SUDHEER KUMAR  , S.D. ATTRI  , K.K. SINGH
Published: December 2021

Multiple regression approach has been used to forecast the crop production widely. This study has been undertaken to evaluate the performance of stepwise and Lasso (Least absolute shrinkage and selection operator) regression technique in variable selection and development of wheat forecast model for crop yield using weather data and wheat yield for the period of 1984-2015, collected from IARI, New Delhi. Statistical parameters viz. R2, RMSE, and MAPE were 0.81, 195.90 and 4.54 per cent respectively with stepwise regression and 0.95, 99.27, 2.7 percentage, respectively with Lasso regression. Forecast models were validated during 2013-14 and 2014-15. Prediction errors were -8.5 and 10.14 per cent with stepwise and 1.89 and 1.64 percent with the Lasso. This shows that performance of Lasso regression is better than stepwise regression to some extent.
Influence of prevailing weather parameters on population dynamics of fruit borer, Helicoverpa armigera (Hübner) on tomato in Haryana
Authors: SHIVANI KHOKHAR  , KRISHNA ROLANIA  , GAURAV SINGH  , ANIL KUMAR
Published: December 2021

A field experiment was conducted for two years (2016-17 and 2017-18) at Entomological Research Area, Department of Entomology, CCS Haryana Agricultural University, Hisar to ascertain the influence of various meteorological parameters on population fluctuations of Helicoverpa armigera on tomato. The maximum oviposition (4.60 eggs/ plant) was recorded during 15th standard meteorologicalweek (SMW) whereas larval population was at peak (4.91 larvae/ plant) during 16th SMW. The larval population showed significant positive correlation with maximum temperature (r=0.617*) and highly significant negative correlation with morning (r=-0.784**) as well as evening relative humidity (r=-0.814**). Maximum eggs parasitization (12.85 %) by Trichogramma sp. was recorded during 16th SMW. These trichogrammatid parasitoids exhibited non-significant correlation with weather parameters and highly significant positive correlation (r=0.976**) with egg counts of H. armigera. Multiple linear regression analysis showed that 77 per cent (R2=0.77) variability in larval population was accounted by weather parameters particularly maximum temperature, morning and evening relative humidity.
Climate vulnerability assessment in semi-arid and arid region of Rajasthan, India: An enquiry into the disadvantaged districts
Authors: NAVEEN P. SINGH  , SURENDRA SINGH  , BHAWNA ANAND  , S. K. BAL
Published: December 2021

This paper assesses the district level climate vulnerability in the state of Rajasthan using largescale data on climate and socio-economic variables.More than thirty indicators segregated into four components of exposure, sensitivity, adaptive capacity and crop production loss were combined to develop a composite index of vulnerability and homogenous districts were clustered into three categories, viz.low, medium and high.Wide inter-district variations were observed across the calculated indices. The result reveals that highest production losses occurred in Ganganagar district followed by Hanumangarh and Bharatpur. Pali was least exposed to the climatic variability, whereas Bundi had the maximum exposure.Jaisalmer rated the maximum sensitivity level. Further, Pratapgarh followed by Jaisalmer and Banswara had the lowest degree of adaptive capacity. On the whole, districts like Hanumangarh, Jaisalmer, Ganganagar, Bundi, Bharatpur, Jodhpur, Bikaner, Chittorgarh, Alwar, Baran and Pratapgarh exhibit high level of vulnerability to climatic change. While on the other spectrum Sirohi district was least vulnerable due to lower exposure, sensitivity, crop production loss and high adaptive capacity. The analysis, suggests the need for prioritizing vulnerable areas to arrest regional imbalances by encouraging need/location based interventions for moderating the degree of vulnerability, whilst making agro-ecosystem in Rajasthan resilient to climatic aberrations.
Effect of date of sowing and rainfall on sustainability of yield and rainwater use efficiency in cereal crops under arid alfisols
Authors: B.SAHADEVA REDDY  , B.RAVINDRANATHA REDDY  , C.RADHA KUMARI  , G.R.MARUTHI SANKAR  , Y.ASHOKA REDDY  , A.MALLISWARA REDDY
Published: December 2021

An assessment of the effects of date of sowing and crop seasonal rainfall on the sustainability of yield and rainwater use efficiency (RWUE) of sorghum, pearl millet and foxtail millet sown on five dates at 15 days interval from first fortnight of June to first fortnight of August during 2009 to 2014 under arid Alfisols at Anantapur has been made in this paper. A suitable date of sowing has been identified for each crop based on the relationships sorghum equivalent yield with crop seasonal rainfall and crop growing period observed in the 6-year study. The yield was significantly influenced by the variation in the crop seasonal rainfall and crop growing period when sown on different dates of sowing. It was significantly higher when crops were sown with the onset of monsoon in the first fortnight of June, and decreased with the subsequent sowings. Among crops, sorghum attained maximum mean yield of 923 kg ha-1 with RWUE of 2.73 kg ha-1 mm-1; while pearl millet attained mean yield of 873 kg ha-1 with RWUE of 2.95 kg ha-1 mm-1 and foxtail millet attained mean yield of 646 kg ha-1 with RWUE of 1.64 kg ha-1 mm-1 when sown during first fortnight of June. Based on the ranks assigned to the yield attained on different dates of sowing in different years, pearl millet was superior for sustaining maximum yield and RWUE comparedto sorghum and foxtail millet under arid Alfisols at Anantapur.
Effect of elevated temperature regimes on growth and yield of rice cultivars under temperature gradient tunnel (TGT) environments
Authors: PRABHJYOT KAUR  , HARLEEN KAUR  , HARPREET SINGH  , S.S. SANDHU
Published: December 2021

The effect of elevated temperature on rice were studied during kharif 2013 and 2014 using six cultivars of rice (PR-116, PR-118, PR-113, PR-115, PR-121 and PR-122) with two replications within a temperature gradient tunnel in which temperature was elevated from the ambient level (+4.5, +5.0, +5.3, +5.5 and +5.8 °C) for the entire crop growth period. The results revealed that the plant height increasedunder elevated temperature regimes, although the rate of change varied with cultivars as well as the stages of the crop. Amongst the six cultivars, the plant height was maximum for cv PR-118 (13.9 cm in vegetative stage (VS) and for cv PR-113 (58.5 cm in grain development stage (GDS) and minimum for cv PR-121 (12.4 cm in VS and 51.8 cm in GDS). The overall tiller number under elevated temperature regimes was maximum for cv PR-122 followed by PR-121, PR-113, PR-116, PR-115 and PR-118 in decreasing order. The 1000-grain weight was reduced from the ambient temperature regime by 8.7 to 14.5 per cent and number of grains per panicle was reduced by 30.6 to 46.7 per cent under elevated temperature of 4.5 to 5.8 oC from ambient. Similarly, the grain yield was reduced by 38.3 to 54.5 per cent and biomass yield reduced by 19.7 to 33.6 per cent with increase under temperature 4.5 to 5.8 oC from theambient environment. Amongst the six cultivars the harvest index was maximum in cv PR-122 (33.0%), i.e., it is most tolerant to heat stress followed by PR-121 (28.3%) and least tolerant were cv PR-116 (20.2%) and PR-115 (18.9%).
Assessment of performance of potato crop under modified microclimates in rice based cropping system of Upper Brahmaputra valley zone of Assam
Authors: M. PANGING  , P. NEOG  , R. L. DEKA  , K. MEDHI
Published: December 2021

A field experiment was conducted during rabi, 2017-18 in Assam Agricultural University, Jorhat to identify appropriate adaptive strategies for combating ill effect of heat and moisture stress through modifying microclimate in rice-potato double cropping system. The potato variety – Kufri Jyoti was planted in split plot design with 3 dates starting from 10 November at 10 days interval (main plots) and three mulching treatments with water hyacinth, black polythene and without mulching (sub-plots) following recommended agronomic practices. The study revealed that there were 11.8 and 7.0 per cent increase in average soil moisture content under water hyacinth and black polythene, respectively as compared to non-mulched treatment. On the other hand, soil temperature was 0.5 to 1.5 °C (morning) and 1.1 to 2.3°C (evening) lower under water hyacinth, but 1.2 to 2.1°C (morning) and 1.7 to 2.6 (evening) higher underblack polythene as compared to non-mulched crop. In all planting dates, crop growth parameters like LAI and biomass production were observed to be highest under water hyacinth, followed by black polythene and without mulching. Among the mulching treatment the highest and lowest tuber yield was recorded under water hyacinth (120.81 q ha-1) and non-mulched treatment (85.0 q ha-1), respectively in all planting dates.It was found that the tuber yield was significantly and positively correlated (at 5% level) with theaverage soil moisture retention (mm) in upper 30 cm layer of soil during tuber formation to physiological maturity (r =77*). Increase in tuber yield (up to 42.2%) under water hyacintheven in case of late plantings (beyond 10 November) was probably due to increase insoil moisture retention (8.1 to 15.7 %) and reduction of soil temperature (1 to 1.8°C) under water hyacinthwhich endowed with favorablehydrothermal environment as compared to that under black polythene and non mulched treatment.
Evaluating InfoCrop model for growth, development and yield of spring wheat at farmers' field in semi-arid environment
Authors: RAJKUMAR DHAKAR  , VINAY KUMAR SEHGAL  , DEBASISH CHAKRABORTY  , JOYDEEP MUKHERJEE  , S. NARESH KUMAR
Published: December 2021

Evaluation of crop simulation model for growth and development of crops at farmers' eld is uncommon, as large variability exists in management practices at farmers' elds. Present study was attempted to evaluate the suitability of InfoCrop v2.1 model for prediction of growth, development and yield of wheat crop at farmers' elds using two years data i.e. 2015-16 & 2016-17. A total of 42 farmers'elds were selected in Pataudi block of Haryana state. The large variability in wheat sowing date (1-Nov to 25-Dec), seed rate (87 to 150 kgha-1), N application rate (70 to 195 kgha-1) and number of irrigations (5-8) were observed in farmers' eld. InfoCrop model could able to predict well days to anthesis and physiological maturity within an acceptable error of 5% (RMSE~3 days). Measured leaf area index (LAI) matched well with simulated LAI (RMSE ~ 0.5). The agreement between observed and model simulated wheat grain yield was found to be satisfactory (nRMSE ~ 6-8%). We conclude that InfoCrop-wheat model satisfactorily simulate the growth, development and yield of wheat crop under varied management practices at farmers' elds, and hence can be applied for agricultural applications for farmers
Impacts of rainfall and temperature on photoperiod insensitive sorghum cultivar : model evaluation and sensitivity analysis
Authors: F. M. AKINSEYE  , A. H. FOLORUNSHO  , AJEIGBE  , A. HAKEEM  , S. O. AGELE
Published: December 2021

A combination of local-scale climate and crop simulation model were used to investigate the impacts of change in temperature and rainfall on photoperiod insensitive sorghum in the Sudanian zone of Mali. In this study, the response of temperature and rainfall to yield patterns of photoperiod insensitive sorghum (Sorghum bicolor L. Moench) using the Agricultural Production Systems Simulator (APSIM) model was evaluated. Following model calibration of the cultivar at varying sowing dates over two growing seasons (2013 and 2014), a long-term simulation was run using historical weather data (1981-2010) to determine the impacts of temperature and rainfall on grain yield, total biomass and water use efficiency at varying nitrogen fertilizer applications. The results showed that model performance was excellent with the lowest mean bias error (MBE) of -2.2 days for flowering and 1.4 days for physiological maturity. Total biomass and grain yield were satisfactorily reproduced, indicating fairly low RMSE values of 21.3% for total biomass and very low RMSE of 11.2 % for grain yield of the observed mean. Simulations at varying Nfertilizer application rate with increased temperature of 2 °C, 4 °C and 6 °C and decreased rainfall by 25 and 50 % (W-25% and W-50%) posed a highly significant risk to low yield compared to increase in rainfall. However, the magnitude of temperature changes showed a decline in grain yield by 10%, while a decrease in rainfall by W-25% and W-50% resulted in yield decline between 5% and 37%, respectively. Thus, climate-smart site-specific utilization of the photoperiod insensitive sorghum cultivar suggests more resilient and productive farming systems for sorghum in semi-arid regions of Mali.
Assessing impact of thermal units on growth and development of mustard varieties grown under optimum sown conditions
Authors: M.R. ISLAM  , M.A. ALAM  , MOHD. MOSTOFA KAMAL  , R. ZAMAN  , AKBAR HOSSAIN  , ALHARBY, H.  , BAMAGOOS, A.  , MOHD. FAROOQ  , J. HOSSAIN  , C. BARUTCULAR  , F. ÇIG  , AYMAN EL SABAGH
Published: December 2021

Thermal unit indices have a strong correlation with the phenology, growth and yield of crops and can be effectively used to select suitable crop cultivars for specific environmental conditions especially temperature. In this study, four mustard varieties (viz., 'BARI Sharisha-14', 'BARI Sharisha-15', 'BARI Sharisha-16' and 'Tori-7') were grown in two consecutive growing to assess the impact of thermal unit indices on crop growth and development, and to select the suitable variety for better yield under optimum sowing condition. Thermal unit indices viz., growing degree-day (GDD), helio-thermal units (HTU), phenothermal index (PTI) and heat use efficiency (HUE) were estimated from daily temperature and sunshine hours. Role of GDD on different growth indicators and seed yield (SY) were estimated through association and dependence of the traits. Significant variations in studied genotypes were observed for different traits. Among the studied varieties, 'BARI Sharisha-16' produced higher dry matter and seed yields (1.82 t ha-1) while accumulated maximum GDD at different growth stages. A strong positive association was obtained between GDD and the studied traits. Thermal unit indices had a strong influence in attaining different phenophases and other growth indicators. Therefore, results suggest that those indices could be used for growth prediction; further 'BARI Sharisha-16' is expected to use heat energy more efficiently for increasing the seed yields which indicated that the crop can perform better under global warming scenarios.
Heat unit requirement and yield of wheat (Triticum aestivum L.) varieties under different growing environment in mid hill conditions of Himachal Pradesh
Authors: RANU PATHANIA  , RAJENDRA PRASAD  , RANBIR SINGH RANA  , S. K. MISHRA
Published: December 2021

A eld experiment was conducted during rabi seasons of 2015-16 and 2016-17 to study the accumulated growing degree days (GDD), helio-thermal unit (HTU), photo-thermal unit (PTU), heat use efciencies (HUE) at different phenological stages and performance of wheat (Triticum aestivum L.) varieties grown under different sowing dates. Results of present study revealed that the crop sown on 20th October required maximum calendar days, growing degree days, photo-thermal unit and helio-thermal unit for tillering, owering, earing and maturity which was signicantly reduced with subsequent delay in sowing time. The grain yield recorded in 20th November (4065 kgha-1) was statistically at par with 5th November yield (3863 kgha-1). The signicant reduction in grain yield on varieties was recorded when sowing was delayed beyond 20th November. Among the varieties 'VL-907' produced highest grain yield(3771 kgha-1) which was statistically on par with 'VL-829' (3726 kgha-1). The early and timely sown wheat  variety like VL-829 and VL-907 took highest calendar days, GDD, HTU and PTU for earing and maturity. The variety 'VL-907' recorded the highest grain yield (4196 and 4168 kgha-1) at 5th and 20th November sowing as compared to all other sowing dates.
Influence of altitude on eco-phytochemical parameters of Peganum harmala, Sophora alopecuriodes and Ziziphora clinopodioides Lam in rangelands of northern Iran
Authors: M.R. KHATAMI MOGHADDAM  , H. FALLAH  , Y. NIKNEJAD  , S. DASTAN
Published: December 2021

Northern Iran especially Alborz Mountain range is one of the most important floristic regions of Iran, which has high medicinal plant biodiversity. Research areas were located between the northern part of the Alborz Mountains range and south of the Caspian Sea in northern Iran, west of the Mediterranean. Selection of rangelands for ecological survey was carried out according to the climate diversity of Amol County in Mazandaran province during 2018 growing season. Three altitude in the regions including Rineh (1800 m above mean sea level), Polur (2300 m AMSL) and Lar Plain (2800 m AMSL) for each herbal medicinal plant (Sophora alopecuriodes, Peganum harmala and Ziziphora clinopodioides Lam) were chosen as treatment. The results showed that plant fresh weight and plant dry matter of Peganum harmala, Sophora alopecuriodes and Ziziphora clinopodioides was decreased with enhance of altitudefrom sea level. Essential oil yield of Peganum harmala and Sophora alopecuriodes enhanced by increase of altitude, but for Ziziphora clinopodioidest, with increase of altitude the essential oil yield was decreased. In Peganum harmala, only benzaldehyd 2-amino was enhanced with increase of altitude from 1800 m to 2800 m AMSL, but eicosane was decreased by altitude increasing. For Sophora alopecuriodes the most amount of sophoramine and adenocarpine was obtained in 1800 m above sea level, but sophocarpineand vinylphenol shows the highest rates in 2800 m AMSL. For Ziziphora clinopodioides, the highest amount of alpha.-thujene, camphene and sabinene was observed in altitude of 1800 m above sea level. But, alpha.-pinene, 2-beta.-pinene, beta.-myrcene and 3-octanol in altitude of 2800 m AMSL demonstrated higher rates. As a result, natural ecosystems, altitude above sea level are among the main determinants of the qualitative and plant quantitative parameters of medicinal plants.
Spatio-temporal variability of climatic parameters across different altitudes of North- Western Himalaya
Authors: PANKAJ PANWAR  , SHARMISTHA PAL  , NANCY LORIA  , MED RAM VERMA  , N.M. ALAM  , V.K. BHATT  , N.K. SHARMA
Published: December 2021

Climate change impact varies across different altitudinal ranges and demands local specific management strategies for water resource and farming system management. The present study analyses spacio-temporal climate parameters across different altitudes of Himachal Pradesh a hilly state of India. Analysis shows that annually, minimum temperature has significantly decreased by -0.09°C at altitude I (350 - 400 m) while maximum temperature has significantly increased by 0.05°C at altitudes I and II (1400-1500 m) and decreased significantly by -0.08°C at altitude III (2000- 2100 m). Higher regions Altitude – IV (2900-3000 m) received lowest rainfall (746.1 mm) with 30.2 % variation. Seasonal rainfall variability was higher in post monsoon (102 - 174%) and least in monsoon (21 - 57%). Annual rainfall at altitude I is strongly irregular (PCI 20.1 to 22.3), followed by altitude – IV (PCI 15-25); altitude – II irregular (PCI 15-20) and altitude – III moderate to irregular (PCI 12 -19) rainfall. Seasonal Index values for four altitudes fall between 0.91-0.96 revealed that rainfall is irregular and markedly seasonal with longer drier season. Higher wavelet powers in altitude - I and II after 2005 suggests frequency of extreme rainfall occurrence had increased.
Trend analysis of weather parameters over Indian Sundarbans
Authors: UTTAM KUMAR MANDAL  , DIBYENDU BIKAS NAYAK  , SOURAV MULLICK  , ARPAN SAMUI  , AMIT KUMAR JANA  , K.K. MAHANTA  , SHISHIR RAUT  , SHIVAJI ROY  , D. BURMAN
Published: December 2021

Sundarbans in West Bengal of India by virtue of its strategic location in the Eastern coast on the Bay of Bengal falls in one of the most vulnerable zones of abrupt climate change. Temporal trends of weather parameters of Canning Town (22o18'10.8'' N Latitude, 88o39'58.4'' E Longitude, elevation 3.52 m msl) representing Indian Sundarbans were analysed by non-parametric Mann-Kendall test and Sen's slope approaches. Analysis of long term rainfall data (1966-2015) indicated that Canning receives a mean annual rainfall of 1821 mm (±341.8 mm) with a considerable variation (CV = 18.8%). The results revealed that total annual rainfall trend decreased non-signicantly at the rate of 0.94 mm yr-1. On an average 84.4 rainy days in a year was recorded in the region, whereas during last ten years (2006-2015), the number of rainy days was reduced to 79.7 days yr-1. There was no signicant change in maximum, minimum and mean temperature of the region. Bright sunshine hours declined signicantly at an annual rate of 0.055 hr yr-1. Reference crop evapotranspiration (ET ) calculated using FAO Penman-Monteith method revealed that annual ET signicantly decreased at the rate of 5.98 mm yr-1. There was 2.7 times surplus rainfall than  crop evapotranspiration during monsoon months indicating very high scope of water harvesting to tackle water logging during the monsoon season and unavailability of fresh water for irrigation during lean season.
Reference evapotranspiration modeling using radial basis function neural network in different agro-climatic zones of Chhattisgarh
Authors: DIWAKAR NAIDU  , BABITA MAJHI
Published: December 2021

Precise estimation of evapotranspiration (ET) is extremely essential for efficient utilization of available water resources. Among the empirical models, FAO-Penman-Monteith equation (FAO-PM) is considered as standard method to determine reference evapotranspiration (ET ). In developing countries  like India, application of FAO-PM equation for ET estimation has certain limitations due to unavailability of specific data requirements. Several empirical models such as Hargreaves, Turc, Blaney-Criddle etc., arealso considered for ET estimation. However, ET estimates obtain with these models are not comparable with benchmark FAO-PM ET . To address this issue, potential of radial basis function neural network  (RBFNN) is investigated to estimate FAO-PM ET . Result obtained with proposed RBFNN models are compared with equivalent multi-layer artificial neural network (MLANN) and empirical approach of Hargreaves, Turc and Blaney-Criddle. Lower RMSE values obtained with RBFNN and MLANN models is an indication of improved performance over empirical models. Similarly, higher R2 and Efficiency Factor obtained with RBFNN and MLANN models also approves the superiority of machine learning techniques over empirical models. Among the two machine learning techniques, RBFNN models performed better as compared to MLANN. In a nut shell, proposed RBFNN models can simulate FAO-PM ET even with limited meteorological parameters and consistence degree of accuracy level.
An analysis of drought evolution characteristics based on standardized precipitation index: a case study in Southwest Guizhou Autonomous Prefecture, China
Authors: XU YANG  , XIAOHOU SHAO  , XINYU MAO  , XIUNENG LI  , RONGQI LI
Published: December 2021

Drought is a worldwide concerned issue which causes huge losses in agriculture, economic and damages in natural ecosystems. The precise assessment of drought evolution characteristics is essential for agricultural water management and drought resistance, while such work is rarely reported. Thus, eight meteorological stations located within the Southwest Guizhou Autonomous Prefecture (SGAP) were selected, and the Standardized Precipitation Index (SPI) was used to assess the drought evolution characteristics. The results revealed that the drought occurrences number in Pu'an station was the largest (23 droughts), and the average drought duration in Xingren station was the longest (48.75 months). Moreover, the drought characteristics of the eight stations have account for the largest proportion under normal conditions, was more than 60%, the frequency of drought disaster occurring in Xingren is the highest (30.05%), followed by Wangmo (23.73%). The results of this study will provide theoretical guidance for drought resistance and agricultural production in Southwest Guizhou Autonomous Prefecture of China.
Pre-harvest forecast of kharif rice yield using PCA and MLR technique in Navsari district of Gujarat
Authors: K.B. BANAKARA  , H.R. PANDYA  , Y.A. GARDE
Published: December 2021

In this paper Principal Components (PC) and Multiple Linear Regression (MLR) Technique were used for development of pre-harvest model for rice yield in the Navsari district of south Gujarat. The weather indices were developed and utilized for development of pre-harvest forecast models. The data of rice yield and weather parameters from 1990 to 2012 were utilized. The cross validation of the developed forecast model were confirmed using data of the years 2013 to 2016. It was observed that value of Adj. R2 varied from 89 to 96. The appropriate forecast model was selected based on high value of Adj. R2. Based on the outcomes in Navsari district, MLR techniques found to be better than PCA for pre harvest forecasting of rice crop yield. The Model-2 found competent to forecast rice yield in Navsari district before eight weeks of actual harvest of crop (37th SMW) i.e during reproductive stage of the crop growth period.
Characterisation of rice fallow period for increasing cropping intensity in Khordha district of Odisha
Authors: S. PATTANAYAK  , B.S. RATH  , S. PASUPALAK  , A.K.B. MOHAPATRA  , A. BALIARSINGH  , A. NANDA  , G.S. PANIGRAHI
Published: December 2021

The possibility of increasing the cropping intensity in Khordha district was assessed by block-wise characterisation of rainfall, soil texture, available water holding capacity of soil and district level temperature during the rice fallow period as well as deciding the appropriate sowing window for both kharif and rabi crops. More than 50% chances of occurrence of wet weeks at the beginning of the kharif season (20-22 SMW) indicated that the summer ploughing and initial seed bed preparation could be taken up during the period followed by sowing of rice from 23 SMW. The 42-43 SMW with greater than 30% initial probability of wet week at 20 mm threshold limit. Considering the length of growing period (LGP) available, the adjustment of rice variety duration by 10-15 days in medium land and advancement of pulse sowing almost by 15 days before harvest of the rice crop (Pira crop) in low land was registered as the best su  suitable option for rabi pulses to ensure better utilisation of rice fallow. In addition to these, harvesting surplus water during kharif and storing in farm ponds for judicious utilisation during rabi season further enhanced the possibility of utilisation of rice fallow and increasing the cropping intensity. In the event of delayed monsoon the rice duration has to be adjusted accordingly not to sacrifice the designated suitable period for rabi pulses.
Assessing suitability of temperature-based reference evapotranspiration methods for semi-arid basin of Maharashtra
Authors: P.S. WABLE  , M.K. JHA  , S.D. GORANTIWAR
Published: December 2021

FAO Penman-Monteith (FAO-PM) is deemed as a sole standard method for estimating reference evapotranspiration (ET ). However, limited availability of meteorological data at spatial and temporal o scales restricts the application of this method. To address this issue, the FAO 56 experts suggested three methods when only maximum and minimum temperature data are available: (i) Temperature-based Penman-Monteith (PMT-1) method wherein T ≈ T (ii) PMT-2 wherein T ≈ T -2.5, and (iii) dew min dew min Hargreaves method. These ET methods were assessed for a semi-arid basin of Western India which lacks adequate climatic data. The performances of the ET methods were evaluated against the standard FAO-PM method using salient statistical and graphical indicators, together with the sensitivity analysis. The results of the three temperature-based methods had a tendency of over-predication of ET in the study area. The PMT-1 method, however, provided superior ET estimates compared to PMT-2 and Hargreaves methods. For estimating monthly ET , the FAO-PM method was most sensitive to temperature. Further, ET of the monsoon season over the study area increased from 5 to 12% during 'drought' years compared to 'normal' years. It was concluded that PMT-1 method is the most suitable temperature-based method for estimating ET in semi-arid regions under limited climatic condition.
Impact of temperature humidity index (THI) on physiological responses and milk yield of Tharparkar and Karan Fries cows exposed to controlled environment
Authors: S.V. SINGH  , Yogendra Kumar  , SUNIL KUMAR
Published: December 2021

Tharparkar and Karan Fries cows were exposed to 25°C, 35°C and 42°C with relative humidity of 50±5%, corresponding to THI of 72.2, 85.3 and 91.0, respectively for three hours continuously for three days consecutively in the control climatic chamber. At THI of 91.0, physiological responses i.e. RR/ min, PR/min and RT (°F) increased by 14, 13, and 1.18 in Tharparkar and 23, 14 and 2.98 in Karan Fries cows, respectively over pre exposure values. At THI of 91.0, the surface body temperature was increased over THI 72.2 by 5.21 to 7.52°C in Tharparkar and 7.45 to 8.42°C in Karan Fries cows. Skin blood flow of Karan Fries cows was increased by 4.98, 4.15 and 3.95 PU at THI 85.3 and 6.84, 9.18 and 8.04 PU at 91 THI over the pre exposure values of respective THI at dorsal, ventral and ear part of body, respectively. The decrease in milk yield was calculated in the THI range of 72.2 - 91.0, the milk yield was decrease (per unit increase in THI) by 135.11ml in Karan Fries and 51.60 ml in Tharparkar cows. The results of the study clearly indicated the more sensitivity of Karan Fries compared to Tharparkar cows at higher THI. Therefore, Karan Fries cows needs protection from extreme heat for sustained production performance.
Elevated CO2 ameliorate the negative effects of high temperature on groundnut (Arachis hypogaea)- Studies under free-air temperature elevation
Authors: M. Vanaja  , P. Sathish  , N. Jyothi Lakshmi  , G. Vijay Kumar  , P. Vagheera  , Ch. Mohan  , S.K. Yadav  , B. Sarkar  , M. Maheswari  , K. SAMMI REDDY
Published: December 2021

Four groundnut (Arachis hypogaea L.) genotypes- Narayani, Dharani, K-6 and K-9 were assessed for growth and yield responses at elevated temperature of 3.0 ± 0.5°C above ambient canopy temperature (eT) and its interaction with elevated CO of 550 ± 50ppm (eT+eCO ) under Free Air 2 2 Temperature Elevation (FATE) facility. The study revealed that eT significantly decreased photosynthetic rate (A ) of all groundnut genotypes whereas eT+eCO condition ameliorated the ill effects of eT. The net 2 impact of eT on A was higher than transpiration rate (Tr) and this reflected in decreased WUE with all net genotypes. WUE improved significantly at eT+eCO with increased A and decreased Tr. Increase in 2 net canopy temperature (eT) resulted decreased relative water content (RWC), cell membrane stability and increased osmotic potential, Malondialdehyde (MDA) content and accumulation of proline. Elevated CO 2 along with eT (eT+eCO ) facilitated these parameters to recover to that of ambient controls, revealing the 2 ameliorative effect of eCO . Similar responses were recorded for biomass and yield parameters. Among 2 the selected groundnut genotypes, superior performance for seed yield at high temperature of >40°C by K-9 was due to ability to maintain better reproductive capacity and Dharani was responsive to elevated CO even at high temperature, indicating the genotypic variability.
Development and application of SPI generator using open source for analyzing drought at a varying time scale
Authors: T. Rajasivaranjan  , N.R. Patel  , A. Ponraj  , V. Kumar  , U. Surendran
Published: December 2021

The Standardized Precipitation Index (SPI) is a probability index that gives a belier representation of abnormal wetness and dryness than any other drought indices. The primary objective of the current study is to develop a comprehensive tool to compute SPI on a spatial basis and analyze spa!iotemporal variability of drought in North West Indian region during 1951-2007 using APHRODITE waler resource data at 0.25-degree resolution. This tool was developed using the python programming language, and the site-packages such as Numpy, Scipy, Ma!plo!lib, Ne!CDF, PyQt were used. The result showed Iha! the SPI time series showed significant inter-annual and multi-decadal variations. In the whole data period, three consecutive droughts have occurred only once, 1999-2002. This prolonged drought hurt the agricultural and water resources sectors over the study area. The computed SPI for the year2002 showed an extreme dry spell over the study area signifying the major drought over India in the same year with a 56% deficit of rainfall in July. The computed 12-month SPI for the year 1996 shows a wet period over the northwestern part of India, especially over Haryana signifying medium to heavy rainfall, conforming 1996 flood. The developed SPI tool, portray a realistic picture of drought scenario over the Northwest region and improve the timely identification of emerging drought conditions that can trigger appropriate responses by the decision makers.
Evaluation of crop water demand for sustainable crop production using geospatial tools in a canal command of West Bengal
Authors: Laishram Kanta Singh  , Madan K. Jha  , V.M. Chowdary  , Srikanta Sannigrahi
Published: December 2021

The agricultural sector is the primary consumer of water resources around the world, and the need for additional food production for growing population further exerts more pressure on water resources. In this study, crop water demand was assessed spatially and temporally for a case study area, Damodar Canal Command (DCC) using geospatial techniques. Crop evapotranspiration was estimated for all the crop seasons using reference evapotranspiration and Fraction of Vegetation cover (FV) that was used as a surrogate for crop coefficient. The reference evapotranspiration (ET ) was calculated using the FAO o Penman-Monteith method. FV was computed based on Normalized Difference Vegetation Index (NDVI) derived from MODIS satellite imagery and its value ranges from 0 to 1. The maximum and minimum reference evapotranspiration values were estimated as 8.44 and 1.88 mmday-1 in May and September, respectively during the normal year 2004. The average monthly crop water demand was maximum in May i.e. 8.08 mmday-1. Among all crop seasons, Boro season has the maximum crop water demand followed by Aus and Aman seasons with maximum ET as 496, 438 and 328 mm, respectively. Total annual crop c water demand for normal year, 2004 was estimated at 1237 mmyr-1 in the study area. Spatially and temporally distributed crop water demand estimates help the irrigation planners to devise the strategies for effective irrigation management.
Quantile mapping for improving precipitation extremes from regional climate models
Authors: Satyanarayana Tani  , Andreas Gobiet
Published: December 2021

The potential of quantile mapping (QM) as a tool for bias correction of precipitation extremes simulated by regional climate models (RCMs) is investigated in this study. We developed an extended version of QM to improve the quality of bias-corrected extreme precipitation events. The extended version aims to exploit the advantages of both non-parametric methods and extreme value theory. We evaluated QM by applying it to a small ensemble of hindcast simulations, performed with RCMs at six different locations in Europe. We examined the quality of both raw and bias-corrected simulations of precipitation extremes using the split sample and cross-validation approaches. The split-sample approach mimics the application to future climate scenarios, while the cross-validation framework is designed to analyse “new extremes”, that is, events beyond the range of calibration of QM. We demonstrate that QM generally improves the simulation of precipitation extremes, compared to raw RCM results, but still tends to present unstable behaviour at higher quantiles. This instability can be avoided by carefully imposing constraints on the estimation of the distribution of extremes. The extended version of the bias-correction method greatly improves the simulation of precipitation extremes in all cases evaluated here. In particular, extremes in the classical sense and new extremes are both improved. The proposed approach is shown to provide a better representation of the climate change signal and can thus be expected to improve extreme event response for cases such as floods in bias-corrected simulations, a development of importance in various climate change impact assessments. Our results are encouraging for the use of QM for RCM precipitation post-processing in impact studies where extremes are of relevance.
Assessing the impact of climate change on crop yields in Gangetic Plains Region, India
Authors: NAVEEN P. SINGH  , SURENDRA SINGH  , BHAWNA ANAND  , P.C. Ranjith
Published: December 2021

Against the increasing vulnerability of agriculture and farm livelihoods to climate change, the study attempted to analyse the trend in climate variables and their impact on major crop yields during the period from 1966-2011, across 4 agro-climatic zones forming Gangetic Plains Region. A rising trend was observed in annual and seasonal (kharif and rabi) mean maximum and minimum temperature across the zones. Rainfall on the other hand, showed a declining trend. Overall, climate change adversely impacted crop yield, but the magnitudes of such effects vary spatially. The results reveal that rice and wheat yield will decline in the entire Gangetic region. By 2050s, maize yield will be higher by 6 percent in Lower Gangetic Plains; pearl millet will increase by 15 percent and rapeseed & mustard by 3.8 percent in Trans-Gangetic Plains. Amongst the crops, sugarcane yield was the most impacted to climate change and is expected to reduce by 21 percent in Middle Gangetic Plains towards end of the century. Hence, there is a need to formulate sustainable adaptation measures and practices suitable to location-specific needs for enhancing climate resiliency and capacity of agricultural system to withstand climatic shocks.
Bayesian discriminant function analysis based forecasting of crop yield in Kanpur district of Uttar Pradesh
Authors: Vandita Kumari  , Kaustav Aditya  , Hukum Chandra  , Amarender Kumar
Published: December 2021

Discriminant function analysis technique using Bayesian approach has been attempted for wheat forecasting in Kanpur district of Uttar Pradesh, India both qualitatively and quantitatively. Crop yield data and weekly weather data on temperature (maximum and minimum), relative humidity (maximum and minimum), rainfall for 16 weeks of the crop cultivation have been used in the study. These data have been utilized for model fitting and validation. Crop years were divided into two and three groups based on the de-trended yield. Crop yield forecast models have been developed using posterior probabilities calculated through Bayesian approach in stepwise discriminant function analysis along with year as regressors for different weeks. Suitable strategy has been used to solve the problem of number of variables more than number of data points. Performance of the models obtained at different weeks was compared using Adjusted R2, PRESS (Predicted error sum of square), number of misclassifications. Forecasts were evaluated using RMSE (Root Mean Square Error) and MAPE (Mean absolute percentage error) of forecast. The result shows that the model based on three groups case perform better. The performance of the proposed Bayesian discriminant function analysis technique approach was better as compared to existing discriminant function analysis score based approach both qualitatively and quantitatively.