CROPGRO-Cotton Model Application for Predicting Cotton Sowing Time in Nagarkurnool District of Telangana State, India

Aims: A study was carried out to find out the optimum sowing time with the validated CROPGRO-Cotton model using DSSAT v 4.7 seasonal analysis tool under rainfed situation at mandal level in Nagarkurnool district of Telangana state, India.Study Design: CROPGRO-Cotton model using DSSAT v 4.7 seasonal analysis tool.Place and Duration of Study: Nagarkurnool district, 2023.Methodology: Cotton production was affected with changing climate in several ways and its impact on rainfed agriculture was higher and influences the Indian economy. The prevailing weather conditions during different phenophases of the crop influences the seed cotton yield. There is a need to optimize the sowing time so that the timing of critical growth stages to minimize stresses and enhance resource utilization. The adjusting of sowing environment proved to be an adaptation management technique for realising higher seed cotton yield.A well calibrated and validated model was used for long term simulations using DSSAT seasonal analysis tool programme with Mallika Bt as test variety for 100 different scenarios (20 mandals × 5 sowing dates) using 32 years historical daily weather data from 1991 to 2022 starting sowing time from 1st June to 1st August at 15 days interval in twenty mandals of the district.Results: The simulation results showed, significantly higher seed cotton yield (1505 kg ha-1) was predicted with crop sown on 1st June followed by 1st July sown crop (1337 kg/ha) which was comparable with 16th June (1324 kg/ha) and significantly differed with delayed sowings of 16th July sown crop (1203 kg/ha) and 1st August sown crop (1192 kg/ha). Among the different mandals of the district, the model simulated higher seed cotton yield (2136-2530 kg/ha) in Amrabad mandal and lower yields in Thimmajipet mandal (596-997 kg/ha) under different sowing environments. Conclusion: Based on simulation scenarios, higher seed cotton yield can be obtained when crop sown between 1st June to 1st July in different mandals of the Nagarkurnool district of Telangana State. The mandals which have less yield potential and realising poor yields by the farmers can be advocated with location specific alternate best management practices to get the higher cotton yield.

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.

Diet seasonality and food overlap of the fish assemblage in a pantanal pond

We assessed the trophic structure of the fish fauna in Sinhá Mariana pond, Mato Grosso State, from March 2000 to February 2001. The aim was to determine the feeding patterns of the fish species during the rainy and dry seasons. The diets of 26 species (1,294 stomach contents) were determined by the volumetric method. Insects and fish were the most important food resources: insects were the dominant food of 23% and 27% of the species, respectively, in the rainy and dry season, and fish was the dominant item for 31% of the species in both seasons. Cluster analysis (Euclidean Distance) identified seven trophic guilds in the rainy season (detritivores, herbivores, insectivores, lepidophages, omnivores, piscivores and planktivores), and five trophic guilds in the dry season (detritivores, insectivores, lepidophages, omnivores and piscivores). The smallest mean values of diet breadth were observed for the specialist guilds (detritivores, lepidophages and piscivores), in both seasons. The widest means for diet breadth were observed for the omnivores, regardless of the season. In general, there was no seasonal variation in feeding overlap among the species studied. At the community level, diet overlap values between species were low (< 0.4) for 80% of the pairs in each season, suggesting wide partitioning of the food resource. The fish assemblage showed a tendency toward trophic specialization, regardless of the season, although several species changed their diets. We might consider two non-excludent hypothesis: that there is no pattern on the use of seasonal food resources and/or probably there are several patterns, because each one is based on characteristics of the studied site and the taxonomic composition of the resident species.

Neste trabalho foi avaliada a estrutura trófica da ictiofauna na baía Sinhá Mariana (MT), no período de março de 2000 a fevereiro de 2001, com o objetivo de detectar qual o padrão alimentar exibido pelos peixes, durante as estações chuvosa e seca. A dieta de 26 espécies (1.294 estômagos) foi avaliada pelo método volumétrico. Insetos e peixes foram os itens mais consumidos pela maioria das espécies, sendo que o primeiro foi alimento dominante para 23% e 27% das espécies, respectivamente, na cheia e na seca e o segundo para 31% das espécies em ambas as estações. Através da análise de agrupamento (Distância Euclidiana) foram identificadas sete guildas tróficas na cheia (detritívora, herbívora, insetívora, lepidófaga, omnívora, piscívora e planctívora)e cinco na seca (detritívora, insetívora, lepidófaga, omnívora e piscívora). Os menores valores médios de amplitude de nicho trófico foram verificados para as guildas constituídas por espécies especialistas (detritívora, lepidófaga e piscívora), em ambos os períodos. Em oposição, as maiores médias foram observadas para a guilda omnívora, independente do período. Em geral, não houve variação sazonal na sobreposição alimentar das espécies. Em nível de comunidade, os coeficientes de sobreposição alimentar foram baixos (< 0,4) para cerca de 80% das espécies para cada período, indicando ampla partição de recursos alimentares. A assembléia de peixes mostrou tendência à especialização trófica, independente da estação considerada e apenas algumas espécies mudaram suas dietas. Assim, é possível considerar duas hipóteses: que não existe um padrão sazonal no uso dos recursos alimentares e/ou que provavelmente existam vários padrões, uma vez que cada um deles é baseado nas características do ambiente estudado e na composição taxonômica das espécies residentes.