scholarly journals Rice Yield Prediction for Cauvery Delta Zone of Tamil Nadu using Weather Based Statistical Model

2020 ◽  
Vol 9 (6) ◽  
pp. 400-406
Author(s):  
G. Senthil Kumar ◽  
K. Subrahmaniyan
Keyword(s):  
Statistical Model ◽  
Tamil Nadu ◽  
Rice Yield ◽  
Yield Prediction ◽  
Cauvery Delta

scholarly journals Comparison Statistical Rice Yield Prediction with Multiple Weather Parameters

2021 ◽  
pp. 31-38
Author(s):  
T. Thurkkaivel ◽  
G. A. Dheebakaran ◽  
V. Geethalakshmi ◽  
S. G. Patil ◽  
K. Bhuvaneshwari
Keyword(s):  
Bayesian Model ◽  
Tamil Nadu ◽  
Rice Yield ◽  
Model Performance ◽  
Research Centre ◽  
Yield Prediction ◽  
Sunshine Hours ◽  
Tamil Nadu State ◽  
Weather Parameters ◽  
Essential Food

Advance knowledge of harvestable products, especially essential food crops such as rice, wheat, maize, and pulses, would allow policymakers and traders to plan procurement, processing, pricing, marketing, and related infrastructure and procedures. There are many statistical models are being used for the yield prediction with different weather parameter combinations. The performance of these models are dependent on the location’s weather input and its accuracy. In this context, a study was conducted at Agro Climate Research Centre, Tamil Nadu Agricultural University, Coimbatore during Kharif (2020) season to compare the performance of four multivariate weather-based models viz., SMLR, LASSO, ENET and Bayesian models for the rice yield prediction at Tanjore district of Tamil Nadu State with Tmax, Tmin, Mean RH, WS, SSH, EVP and RF.  The results indicated that the R2, RMSE, and nRMSE values of the above models were ranged between 0.54 to 0.79 per cent, 149 to 398 kg/ha, 4.0 to 10.6 per cent, respectively. The study concluded that the Bayesian model was found to be more reliable followed by LASSO and ENET. In addition, it was found that the Bayesian model could perform better even with limited weather parameters and detention of wind speed, sunshine hours and evaporation data would not affect the model performance. It is concluded that Bayesian model may be a better option for rice yield forecasting in Thanjavur districts of Tamil Nadu.

scholarly journals Forecasting of Kharif Rice and Jute Yield in North Bengal through Statistical Model

2021 ◽  
pp. 60-65
Author(s):  
Kousik Nandi ◽  
Anwesh Rai ◽  
Soumen Mondal ◽  
Subhendu Bandyopadhyay ◽  
Deb Sankar Gupta
Keyword(s):  
Statistical Model ◽  
Crop Yield ◽  
Climate Change Scenario ◽  
Rice Yield ◽  
State Level ◽  
Change Scenario ◽  
Yield Prediction ◽  
Yield Forecast ◽  
Crop Yield Forecasting ◽  
North Bengal

Crop yield forecasting under the present climate change scenario needs an effective model and its parameter that how crop respond to the weather variable. A number of weather based models have been developed to estimate the crop yield for the various crops at block, district and state level. Among the different model statistical model is more popular and commonly used. The current study was undertaken to evaluate the performance of statistical model for rice and jute yield forecast of four different district viz. Cooch Behar, Jalpaiguri, Uttar Dinajpurand and Dakhin Dinajpur. Among the four districts Cooch Behar district found superior for kharif rice yield prediction (1.46% error with RMSE 177.68 kg/ha) whereas in case of jute crop its performance was the best in the Jalpaiguri district (-0.44% error with RMSE 217.50 kg/ha).

Evolving appropriate zinc fertilization strategy for rice-rice (Oryza sativa) cropping system in Cauvery Delta Zone

2019 ◽  
Vol 56 (3) ◽  
pp. 294-304
Author(s):  
C Sharmila Rahale
Keyword(s):  
Oryza Sativa ◽  
Tamil Nadu ◽  
Field Experiments ◽  
Foliar Spray ◽  
Cropping System ◽  
Green Leaf ◽  
Farm Yard Manure ◽  
Zinc Fertilization ◽  
Initiation Stage ◽  
Cauvery Delta

Six field experiments were conducted at Tamil Nadu Rice Research Institute, Aduthurai to evolve suitable zinc fertilization method for rice - rice (Oryza sativa L.) cropping system in Cauvery delta zone. The treatment includes: T1 : Control, T2 : 100 g zinc sulphate (ZnSO4)/cent in nursery alone., T3 : root dipping alone in 2 % zinc oxide (ZnO) solution, T4 : 25 kg ZnSO4 ha-1, T5 : 37.5 kg ZnSO4 ha-1, T6 : 25 kg ZnSO4 ha-1+ Farm Yard Manure (FYM) 12.5 t ha-1, T7 : 25 kg ZnSO4 ha-1 + Green Leaf Manure (GLM) 6.5 t ha-1, T8 : Tamil Nadu Agricultural University Micro Nutrient (TNAU MN) mixture 25 kg ha-1 as Enriched Farm Yard Manure (EFYM), T9 : TNAU MN mixture 37.5 kg ha-1 as EFYM, T10 : Foliar spray of 0.5% ZnSO4 + 1 % urea at tillering and panicle initiation stage, T11 : 100g ZnSO4 /cent in nursery alone + Foliar spray of 0.5 % ZnSO4 + 1 % urea at tillering and panicle initiation stage (T2+ T10), T12 : root dipping alone in 2 % ZnO solution + Foliar spray of 0.5 % ZnSO4 + 1 % urea at tillering and panicle initiation stage (T3 + T10), T13: 100 g ZnSO4 /cent in nursery alone + root dipping alone in 2 % ZnO solution + Foliar spray of 0.5 % ZnSO4 + 1 % urea at tillering and panicle initiation stage (T2 + T3 + T10). The treatments T5, T6, T7 and T9 were skipped in rabi season to know the residual effect of these treatments in the subsequent season. Among the treatment combinations, application of 25 kg ZnSO4 ha-1 + FYM 12.5 t ha-1 recorded higher grain yield in both kharif (6232 kg ha-1) and rabi (6236 kg ha-1) seasons. The same treatment combination recorded higher Zn content and Zn uptake as well. Regarding soil nutrient content, the same treatment recorded higher N, P and K content. This treatment was followed by application of 25 kg ZnSO4 ha-1 + green leaf manure 6.5 t ha-1. The experimental findings suggested that combination of organic and inorganic sources not only increased the yield but also improves soil health in Cauvery delta zone.

Diagnosis and management of green algae in low land paddy fields of Cauvery delta zone, Tamil Nadu

2021 ◽  
Vol 58 (1) ◽  
pp. 33-42
Author(s):  
M Jeya Bharathi ◽  
M Raju ◽  
S Elamathi
Keyword(s):  
Green Algae ◽  
Tamil Nadu ◽  
Rice Cultivation ◽  
Rice Root ◽  
Wetting And Drying ◽  
Alternate Wetting And Drying ◽  
Green Algal ◽  
Algae Growth ◽  
Cauvery Delta ◽  
Soil And Water

Rice is a prime food crop for Asian countries. Wet land rice cultivation contributes maximum grain yield than dry land rice. Cauvery delta is a predominant area for rice cultivation in Tamil Nadu. Green algae growth during Kuruvai (June -August) season is a serious problem in wet land rice. These algae growth create anaerobic condition and prevent rice root respiration. The entire rice root was uprooted and floated on the stagnated water during initial stage. There is no preliminary study for green algae control in rice field. Soil and water samples were collected and analyzed for the nature of occurrence. Laboratory and field experiments were conducted to find out the remedial measures. The results of soil and water sample analysis showed that use of bore well water and dumping of phosphatic fertilizers leads to salt accumulation which favours the green algal growth. The results of the laboratory experiment revealed that the CuSO4 londox power, propiconazole and hexaconazole showed moderate inhibition on 5th day after treatment. The findings from field experiment indicated that use of conoweeder, alternate wetting and drying and CuSo4 drenching @ of 2.5 kg/ha when green algae appearance has just noticed or 5.0 kg/ha when severe growth occurred was effective in managing the green algae. Among all measures, alternate wetting and drying is the best management practices. CuSO4 drenching reduces around 70% of the growth. Even though CuSO4 react negatively with algae growth, soil pH changes and salt concentration play a major role on the CuSO4 action towards green algae. In order to maintain soil health condition, biofertilizer application, crop rotation, green manure trampling to be practised to recover the soil from alkaline pH, removal of accumulated salt and to control the algae growth using CuSO4.

Incidence of Debarking by Caterpillar, Indarbela quadrinotata Walker on Casuarina equisetifolia in Tamil Nadu and its Management

2019 ◽  
Vol 42 (3) ◽  
pp. 225-230
Author(s):  
K.R. Sasidharan ◽  
◽  
G. Ramesh ◽  
Keyword(s):  
Tamil Nadu ◽  
Seed Oil ◽  
Melia Azedarach ◽  
Seed Kernel ◽  
Casuarina Equisetifolia ◽  
The North ◽  
Eastern Zone ◽  
Tamil Nadu State ◽  
Multipurpose Tree Species ◽  
Cauvery Delta

Casuarina equisetifolia is an exotic, fast growing, multipurpose tree species grown in Tamil Nadu. Altogether, about 40 species of insects have been recorded on C. equisetifolia in Tamil Nadu State. Among them, the bark eating caterpillar, Indarbela quadrinotata is considered as the most destructive pest in plantations. Wide variation in the infestation levels of bark eating caterpillar was noticed in Casuarina plantations grown under four agro-climatic zones of Tamil Nadu; the Cauvery Delta Zone showed highest intensity of attack, followed by the North Eastern Zone and the Southern Zone in the decreasing order of infestation, while the High Rainfall Zone was not affected by the pest. Plantations of younger age suffered from higher levels of infestation, compared to that of older ones. Among the climatological parameters, the minimum temperature had significant positive correlation with the pest infestation. Apart from the naturally occurring entomopathogenic fungus, Beauveria bassiana, the botanical formulations such as Melia azedarach seed kernel extract (5%), Pongamia pinnata seed oil (5%), Hydnocarpus pentandra seed oil (10,000 ppm) and Neem oil (5%) were found to be very effective in managing the pest under field condition.

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