Calibration and Validation of Cropgro (DSSAT 4.7) Model for Chickpea (Cicer arietinum L.) Crop in Raipur

In agriculture aspect crop simulation models play key role in developing the decision making research, technology management and policy options. It acts as useful tool to predict the growth development and production of a crop under varying soil, crop input and climatic condition. The DSSAT CROPGRO model was calibrated and validated through field experiment on chickpea crop during rabi seasons i.e. 2020-21 and 2021-22 at instructional farm Indira Gandhi Krishi Vishwavidyalaya, Raipur Chhattisgarh. The experiment was laid out in randomized block design (factorial) considering 9 treatments of two factors 3 dates of sowing (D1=Nov. 10, D2=Nov. 25, D3=Dec. 10) and 3 cultivars (V1=Vaibhav, V2=JG-14 and V3=JG-16). The results reported highest deviation percentage at anthesis days was (4.8 to 10 %) and physiological maturity was (1.7 to 5.5%) for JG-16 cultivar, whereas in seed yield the highest deviation percent was (6.2 to 9%) for Vaibhav cultivar. Similarly after validation the highest deviation percentage at anthesis days was (0 to 10.7%) for JG-16, at physiological maturity (1.8 to 3.6%) for Vaibhav and in seed yield (2.4 to 9.5%) for JG-16.

Spatial Yield Assessment of Sorghum (Sorghum Bicolor) Using DSSAT – CERES –Sorghum Model in Solapur, Maharashtra, India

Accurate estimation of crop yield is crucial for ensuring food security and effective policy making. This study focuses on the estimation of sorghum yield in the Solapur region of Maharashtra (India), employing the Decision Support System for Agrotechnology Transfer (DSSAT) model. Sorghum is the fifth largely produced staple crop of the world which also plays a vital role in the food security produced by India. Maharashtra has the largest area under sorghum crop, and Solapur has the most area under rabi sorghum with an area of 4.6 lakh ha, accounting for 23% of the total area under rabi sorghum in the state. Although productivity is lower in Maharashtra than in other states, these studies will help us to get a preharvest estimate of the crop. Crop Cutting Experiments(CCE) were conducted for rabi sorghum and the model was validated for the simulated yields; which have a range of grain yield from 611 to 1525 kgs ha-1 and showed error with less than 14% and it was evaluated with statistical models such R2, Nash-Sutcliffe efficiency (NSE) and Normalized Root Mean Square Error (NRMSE) and results show as 84%, 0.84 and 0.07. This model can be used further used for the yield gap analysis, and climate change studies for the locations.

Sustainable Maize Based Cropping Sequences for Northern Transition Zone of Karnataka, India

Maize in SW monsoon and sorghum, wheat and chickpea during winter are the important crops in Northern Transition Zone (NTZ) of Karnataka, India. But, due to rising temperature and erratic rainfall patterns the productivity and profitability of maize based cropping sequences are being threatened under rainfed condition. As a result, a modelling research was conducted utilising the DSSAT model's seasonal analysis tool to test and determine sustainable and profitable cropping sequences for current climates of NTZ in Karnataka state. Field experiments were conducted from 2015 to 2018 to calibrate and validate the DSSAT model for four crop cultivars (maize, chickpea, wheat, and sorghum) grown under rainfed conditions on deep black soils, and then the DSSAT model's sequential analysis tool was run for 32 years (1985-2016) for three cropping sequences (maize-sorghum, maize-wheat, and maize-chickpea). The yield, number of years the crop failed throughout different seasons, and the B:C ratio of each sequence were used in the simulated output study. Out of 32 years maize crop, grown during kharif, failed three times whereas, during rabi season wheat, sorghum and chickpea failed nine, eight and five years, respectively. Out of 32 years maize-sorghum sequence recorded the highest B:C ratio (2.86) followed by maize-chickpea (2.82) and maize-wheat (2.66). Considering chances of crop failure, B:C ratio and owing to cereal followed by short duration legume, maize-chickpea sequence under rainfed condition was proven to be the most reliable and profitable system for NTZ of Karnataka under of current climate.

Assessment of Rice Yield Sensitivity to Changing Weather Conditions in Prayagraj Using DSSAT V4.7.5 Crop Simulation Model

The Field experiments were conducted during 2012-19 to determine the effect of changing weather such as (Tmax, Tmin, Tavg, Solar radiation and CO2 concentration) on grain yield, LAI, Anthesis days and maturity days of four rice cultivars i.e (Swarna sub 1, Sarjoo 52, Pant Dhan 4 and NDR 359) at the college of forestry farm , SHUATS Prayagraj. The DSSAT-CERES rice model was calibrated and validated, for the cultivars under Prayagraj conditions and it was observed that the values i.e Percent error, RMSE, nRMSE and Pearson correlation coefficient (r) were good in agreement and within permissible limit. Among all the four varieties NDR 359 yields more followed by pant dhan 4, Swarna sub 1 and sarjoo-52. The result revealed that by increasing temperature (Tmax, Tmin, Tavg) for all the variety and phenophases the yield got reduced but under increased condition of Solar radiation and CO2 concentration the yield got increased. In case of LAI same result was observed but during the phenophase of flowering to maturity stage of the crop there was no effect found. During the interaction between changing weather with anthesis days and maturity days it was found that the anthesis days and maturity days got increased with increased in Tmax and Tavg. Other weather parameter has no effect on it. The interaction of weather parameter with the yield, LAI, anthesis days and aturity days were found significant at 5% or 1% level for all the four varieties and henophases. The research outcome indicates that, the future farming will be challengeable due to climate change, we must prepare with suitable varieties and crop management plan to tackle the situation.

Influences of Changes in Rainfall and Solar Radiation on Performance of Kharif Sorghum

Kharif sorghum is an important crop of the northern transition zone (NTZ) of Karnataka. Historically this zone was characterized by the assured and uniform distribution of rainfall during the southwest monsoon. The last decade has witnessed increased erraticity in the onset, progress and distribution of rainfall, but days without rain also remain cloudy for weeks during Kharif season, thus lower the crop canopy, which affects the yield, interrupts solar radiation. Solar radiation, rainfall are the two important climatic factors affecting crop performance, but it is logistically difficult, and resource demanding to artificially create study-growing environment under field conditions. Alternately, Crop Simulation Models can be effectively used for such studies by creating customized weather scenarios within the model. Four rainfall scenarios (±10 and ±20 % over observed) and four solar radiation scenarios (±10 and ±20 % over observed) were created by using 32 years’ observed weather data (1985-2016) within the calibrated and validated DSSAT-CERES-Sorghum model [1].Simulations were run across all the above scenarios for 32 years' seasonal analysis with the best four kharif sorghum cultivars sown across three dates of sowing under the standard package of practices followed for NTZ. Model simulated annual outputs for grain yield over 32 years were averaged and presented. The model simulated results revealed that for NTZ changes in solar radiation was found to have more effect on yield than rainfall. Any reduction in solar radiation over observed drastically reduces the yield. Across cultivars and dates of sowing under observed weather (1985-2016), on average, 1720 kg ha-1 yield was simulated. When solar radiation was reduced by 10 % across rainfall scenarios the average yield was reduced to 1424 kg ha-1 which further reduced to 670 kg ha-1 (61% reduction) when solar radiation was reduced by 20 %. In contrast, when solar radiation was increased by 10 % and 20 %, the model simulated 2967 kg ha-1 and 3181 kg ha-1 yield, respectively which is 42 and 46 % more over the yield of observed weather. This study showed that for NTZ of Karnataka during the Kharif season increased cloudy period will have a more adverse effect on yield than changes to rainfall.

Phasic Development of Rice During the Present and Future Climatic Conditions in Central Zone of Kerala

Rice is a staple food and its demand is substantially increasing with the growth of the global population. Phenological development was found to play a signi?cant role in the distribution of carbon among plant organs, which has an impact on rice yield. Temperature affects plant phenology, and the current rapid climate change has revived interest in understanding and modelling plant phenology response to the warming trend. Two rice varieties viz., Jyothi (short duration variety) and Jaya (medium duration variety) were raised at Agriculture Research Station, Mannuthy, during the kharif season of 2021 and phenological observations viz., days to 50% flowering and physiological maturity were recorded. The phenophase has been also predicted from the Info-Crop and CERES-DSSAT for both varieties during the experimental period for validation. To study the phenology changes in future conditions i.e., near (2030), mid (2050) and end (2080) century, future weather data has been downloaded from the GFDL-CM3 climate model under RCP 4.5 and RCP 8.5 scenarios. Using the projected weather data, the phenophase of both varieties has been predicted using Info-Crop and CERES-DSSAT models. During the base period, Jyothi took 71 days and Jaya took 75 days to reach 50% flowering, while the total duration was found to be 101 days in Jyothi and 108 days in Jaya. In the case of 50% flowering, CERES-DSSAT predicted more accurately for Jyothi while InfoCrop predicted more accurately for Jaya. The prediction of physiological maturity was found to be more accurate using CERES-DSSAT in Jaya and Info-Crop in Jyothi. Validation results showed that both models can be used to predict the phenophases of rice varieties. The predicted duration during base period was compared with future duration. In Info-Crop model, the days to 50% flowering of Jyothi variety in near, mid and end century is expected to reduce by 3, 3 and 4 days in RCP 4.5 scenario and 1, 3 and 4 days in RCP 8.5 scenario whereas for Jaya variety, it is by 2, 3 and 3 days in RCP 4.5 and 1, 3 and 3 days in RCP 8.5 scenario respectively. CERES-DSSAT model predicted reduction of 50% flowering duration of Jyothi variety in near, mid and century by 1, 2 and 3 days in RCP 4.5 scenario and 1, 2 and 2 days in RCP 8.5 scenario whereas for Jaya variety, the reduction is by 2, 2 and 3 days in RCP 4.5 scenario and 1, 2 and 3 days in RCP 8.5 scenario respectively. The physiological maturity is projected to shorten by 3-6 days in Jyothi and 4-5 days in Jaya, by the end century. Results showed that the temperature rise in future can cause the considerable reduction in duration to attain 50% flowering and physiological maturity of rice varieties.

Número de gerações de um percevejo e seu parasitoide e da severidade da ferrugem asiática em soja, simulados em cenários de clima e manejo no norte do RS / Number of generations of a stink bug and its parasitoid and severity of soybean rust, simulated under climate and crop management scenarios in northern RS State, Brazil

Objetivou-se simular o número de gerações do percevejo Euschistus heros e seu parasitoide Telenomus podisi e da severidade da ferrugem causada por Phakopsora pachyrhizi na cultura da soja em função da data de semeadura, cultivar e momento de ocorrência desses organismos. A simulação foi feita em dois locais representativos de duas importantes regiões produtoras de soja no Estado do Rio Grande do Sul. Modelos bioclimáticos dos insetos e da doença foram integrados a um modelo de simulação da cultura da soja (DSSAT) e rodados para uma série temporal de dados meteorológicos diários para Passo Fundo (52 anos) e Santa Rosa (34 anos). Independente do grupo de maturação, quanto mais antecipada foi a data da semeadura e o estádio de ocorrência de E. heros na cultura, maior o número de gerações (de 2 a 3) até a maturação fisiológica da soja. Para T. podisi, um maior número de gerações (5 a 6) foi simulado para semeadura antecipada e cultivares de ciclo tardio. Para a ferrugem asiática não foram observadas tendências de redução nos níveis médios de severidade com o uso de práticas preconizadas, como plantio antecipado e cultivares de grupos mais precoces de maturação.

The objective of this study was to simulate the number of generations of a soybean insect pest (Euschistus heros) and its parasitoid (Telenomus podisi) and a fungal disease (soybean rust caused by Phakopsora pachyrhizi) as influenced by sowing date, cultivar and time of occurrence of the pest and the disease. Bioclimatic models that predict development of the organisms and severity of the disease were integrated into a crop simulation model of soybean (DSSAT) that predicted phenological stages of the crop for scenarios of sowing data and cultivar maturity group in a long time series of daily meteorological data to Passo Fundo and Santa Rosa, Rio Grande do Sul State, Brazil. The results showed that regardless of the maturity group, the earlier the sowing date and the time of occurrence of E. heros in the field, the greater its number of generations (2 to 3) until physiological maturity. For T. podisi, a higher number of generations (5 to 6) was estimated for the earlier sowing dates and late-maturing cultivars. For soybean rust no significant trends of reduction in the mean disease severity was observed when advocated practices such as early sowing and early-maturing cultivars were used.