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 Influence of Weather Parameters and Thermal Time Approach on Green Gram at Coimbatore, Tamil Nadu

2020 ◽  
pp. 1-5
Author(s):  
S. A. Naveen ◽  
S. Kokilavani ◽  
S. P. Ramanathan ◽  
G. A. Dheebakaran ◽  
S. Anitta Fanish
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Tamil Nadu ◽  
Green Gram ◽  
Research Centre ◽  
Maximum Temperature ◽  
Sowing Dates ◽  
Sunshine Hours ◽  
Diurnal Range ◽  
Weather Parameters

An investigation was carried out at the Agro Climate Research Centre, Tamil Nadu Agricultural University, on the effect of weather parameters on the green gram yield sown at various sowing dates during the rabi season of 2019. At various sowing dates, two green gram cultivars, VBN 4 and ADT 3, were sown. For both cultivars, the phonological crop length decreased with delays in sowing dates beyond October 23rd. The yield of green gram sown on 23rd October was significantly higher than the crops sown on 30th October and 6th November. The weather parameters Maximum Temperature (Tmax), Diurnal Range (Trange), Bright Sunshine Hours (BSS), Relative Humidity (RH I), Wind Speed (WS) were found to be negatively correlated with seed yield whereas Minimum Temperature (Tmin), Relative Humidity (RH II), Vapour Pressure (VP) were found to be positively correlated with the yield of green gram. The accurate prediction of green gram yield could be done with the maximum temperature, bright sunshine hours, wind speed and with thermal indices especially hygrothermal unit II with 82 percent, accuracy level.

scholarly journals Influence of multi-decadal meteorological variability on the reference evpotranspirtion in hot and humid coastal town of Annamalainagar in Tamil Nadu state

MAUSAM ◽  
2021 ◽  
Vol 71 (1) ◽  
pp. 45-56
Author(s):  
MURUGAPPAN A ◽  
MANIKUMARI N ◽  
MOHAN S
Keyword(s):  
Tamil Nadu ◽  
Reference Evapotranspiration ◽  
Meteorological Parameter ◽  
Vapour Pressure Deficit ◽  
Weather Data ◽  
Net Radiation ◽  
Sunshine Hours ◽  
Daily Weather Data ◽  
Tamil Nadu State ◽  
Decadal Trend

Reference evapotranspiration (ETo) is a key pointer of atmospheric evaporation demand and has been extensively used to describe the hydrological change. In this study, the reference evapotranspiration over the hot and humid town, Annamalainagar, very near to the east coast in Tamilnadu State, India, have been estimated employing the FAO Penman-Monteith (PM) method and the observed daily weather data during 1977-2016. The objective of the present study is two-fold: (i) To identify the multi-decadal trend of the various measured meteorological parameters namely, mean air temperature (Tmean), vapour pressure deficit (VPD), actual sunshine hours (SSH), net radiation (Rn) and wind speed (WS) at the study location and (ii) To identify the main contributing meteorological parameter for the detected decreasing trend in ETo over the multi-decadal period.

scholarly journals Selection of Important Features for Optimizing Crop Yield Prediction

2019 ◽  
Vol 10 (3) ◽  
pp. 54-71
Author(s):  
Maya Gopal P S ◽  
Bhargavi R
Keyword(s):  
Feature Selection ◽  
Crop Yield ◽  
Tamil Nadu ◽  
Feature Subset ◽  
Yield Prediction ◽  
Multilinear Regression ◽  
Secondary Sources ◽  
Backward Elimination ◽  
Tamil Nadu State ◽  
Selection Algorithms

In agriculture, crop yield prediction is critical. Crop yield depends on various features including geographic, climate and biological. This research article discusses five Feature Selection (FS) algorithms namely Sequential Forward FS, Sequential Backward Elimination FS, Correlation based FS, Random Forest Variable Importance and the Variance Inflation Factor algorithm for feature selection. Data used for the analysis was drawn from secondary sources of the Tamil Nadu state Agriculture Department for a period of 30 years. 75% of data was used for training and 25% data was used for testing. The performance of the feature selection algorithms are evaluated by Multiple Linear Regression. RMSE, MAE, R and RRMSE metrics are calculated for the feature selection algorithms. The adjusted R2 was used to find the optimum feature subset. Also, the time complexity of the algorithms was considered for the computation. The selected features are applied to Multilinear regression, Artificial Neural Network and M5Prime. MLR gives 85% of accuracy by using the features which are selected by SFFS algorithm.

A Study on Job Satisfaction among Tamil Nadu State Transport Corporation (TNSTC) Employees at Tiruvarur Branch

GIS Business ◽  
2019 ◽  
Vol 14 (6) ◽  
pp. 230-242
Author(s):  
M. Ganesan, K ◽  
K. Veerakumar ◽  
N. R Vembu ◽  
Dr. M. K Durgamani ◽  
Dr. Renuka
Keyword(s):  
Job Satisfaction ◽  
Job Stress ◽  
Tamil Nadu ◽  
Heavy Traffic ◽  
Road Transportation ◽  
The Road ◽  
Tamil Nadu State ◽  
On The Road ◽  
Day By Day ◽  
Labour Turnover

Job satisfaction is an important factor for employees working in formal and informal sector. The job is small or big, permanent or temporary, risky or non-risky, job satisfaction is important. It is the mental feeling which drives the employees to excel. Job satisfaction is a combination of psychological, physiological and environmental circumstances. A satisfied employee is a contented and happy human being. The labour turnover depends upon job satisfaction. Even highly paid employees quit the job when they are not satisfied with the job. Road transportation in Tamilnadu is growing day by day. Job stress in the road transportation is very high due to increase in number of vehicle playing on the road and heavy traffic. The drivers and conductors working in public transport corporation are suffering from high job stress. If drivers and conductors are not satisfied with their job which leads to mental stresses and affects the productivity and also creates accidents. In this present study the researchers made an attempt to study the level of job satisfaction among the drivers and conductors who are working in the Tamilnadu State Transport Corporation (TNSTC). The study reveals the expectations of drivers and conductors working in TNSTC with regards to the attributes like salary, promotion and fringe benefits etc., are satisfactory and not detrimental. 

scholarly journals Maternal Vitamin B12 Status and Risk of Cleft Lip and Cleft Palate Birth Defects in Tamil Nadu State, India

2021 ◽  
Vol 58 (5) ◽  
pp. 567-576
Author(s):  
Ronald G. Munger ◽  
Rajarajeswari Kuppuswamy ◽  
Jyotsna Murthy ◽  
Kalpana Balakrishnan ◽  
Gurusamy Thangavel ◽  
...  
Keyword(s):  
Cleft Palate ◽  
Tamil Nadu ◽  
Cleft Lip ◽  
Maternal Nutrition ◽  
Case Control ◽  
Vitamin B ◽  
Plasma Vitamin ◽  
Maternal Vitamin ◽  
Increased Risk ◽  
Tamil Nadu State

Background and Objective: The causal role of maternal nutrition in orofacial clefts is uncertain. We tested hypotheses that low maternal vitamin B12 and low folate status are each associated with an increased risk of isolated cleft lip with or without cleft palate (CL±P) in a case–control study in Tamil Nadu state, India. Methods: Case-mothers of CL±P children (n = 47) and control-mothers of unaffected children (n = 50) were recruited an average of 1.4 years after birth of the index child and plasma vitamin B12, methylmalonic acid (MMA), total homocysteine (tHcy), and folate were measured at that time. Logistic regression analyses estimated associations between nutrient biomarkers and case–control status. Results: Odds ratios (ORs) contrasting biomarker levels showed associations between case-mothers and low versus high plasma vitamin B12 (OR = 2.48, 95% CI, 1.02-6.01) and high versus low plasma MMA, an indicator of poor B12 status (OR = 3.65 95% CI, 1.21-11.05). Case–control status was not consistently associated with folate or tHcy levels. Low vitamin B12 status, when defined by a combination of both plasma vitamin B12 and MMA levels, had an even stronger association with case-mothers (OR = 6.54, 95% CI, 1.33-32.09). Conclusions: Mothers of CL±P children in southern India were 6.5 times more likely to have poor vitamin B12 status, defined by multiple biomarkers, compared to control-mothers. Further studies in populations with diverse nutritional backgrounds are required to determine whether poor maternal vitamin B12 or folate levels or their interactions are causally related to CL±P.

Regionalization of sediment rating curve for sediment yield prediction in ungauged catchments

2013 ◽  
Vol 46 (1) ◽  
pp. 26-38 ◽  
Author(s):  
Sokchhay Heng ◽  
Tadashi Suetsugi
Keyword(s):  
Sediment Yield ◽  
Model Performance ◽  
Data Uncertainty ◽  
Spatial Proximity ◽  
Yield Prediction ◽  
Rating Curve ◽  
Ungauged Catchments ◽  
Probability Curve ◽  
Sediment Rating Curve ◽  
Almost All

The main objective of this research is to regionalize the sediment rating curve (SRC) for subsequent sediment yield prediction in ungauged catchments (UCs) in the Lower Mekong Basin. Firstly, a power function-based SRC was fitted for 17 catchments located in different parts of the basin. According to physical characteristics of the fitted SRCs, the sediment amount observed at the catchment outlets is mainly transported by several events. This also indicates that clockwise hysteretic phenomenon of sediment transport is rather important in this basin. Secondly, after discarding two outlier catchments due to data uncertainty, the remaining 15 catchments were accounted for the assessment of model performance in UCs by means of jack-knife procedure. The model regionalization was conducted using spatial proximity approach. As a result of comparative study, the spatial proximity approach based on single donor catchment provides a better regionalization solution than the one based on multiple donor catchments. By considering the ideal alternative, a satisfactory result was obtained in almost all the modeled catchments. Finally, a regional model which is a combination of the 15 locally fitted SRCs was established for use in the basin. The model users can check the probability that the prediction results are satisfactory using the designed probability curve.

Wells for welfare or illfare? Cost of groundwater depletion in Coimbatore, Tamil Nadu, India

Water Policy ◽  
2008 ◽  
Vol 10 (4) ◽  
pp. 391-407 ◽  
Author(s):  
K. Palanisami ◽  
A. Vidhyavathi ◽  
C. R. Ranganathan
Keyword(s):  
Tamil Nadu ◽  
Economic Cost ◽  
Groundwater Depletion ◽  
Cropping Pattern ◽  
Watershed Development ◽  
Groundwater Overdraft ◽  
Well Spacing ◽  
Coimbatore District ◽  
Tamil Nadu State ◽  
The Cost

Groundwater depletion is experienced in several districts of Tamil Nadu state and Coimbatore district is heading in that direction. The average well failure rate is 47% for open wells and 9% for bore wells. The total cost of depletion for new wells varies from Rs 1,999 per ha to Rs 90,975 per ha. The electricity subsidy to the farmers has varied from Rs 22,621 per ha for coconut growers to Rs 25,498 per ha for banana growers as on 2004. The cost of irrigation per cubic metre (m3) is less on large farms. The average net return with free electricity varies from Rs 0.14 per m3 to Rs 1.38 per m3 and is drastically reduced when electricity is priced at an economic cost, i.e. Rs −1.15 to Rs −0.14 per m3. The shift in cropping pattern towards high value crops helped the farmers to some extent to bear the cost of externalities arising out of depletion. The social cost caused by groundwater overdraft is about Rs 554.3 million, which may increase when the well density increases further. Suggested policy options are to change the cropping pattern to less water-consuming crops, to invest in watershed development activities, to change inefficient pumpsets and to adopt well spacing norms.

Most Difficult Topic in Social Science Curriculum as Perceived by Elementary Level Student-Teachers

2021 ◽  
pp. 236-247
Author(s):  
R. Vinodh Kumar ◽  
M. Vakkil
Keyword(s):  
Social Science ◽  
Student Teachers ◽  
Tamil Nadu ◽  
Science Curriculum ◽  
Sampling Technique ◽  
First Year ◽  
Elementary Teacher Education ◽  
Tamil Nadu State ◽  
Interest And Motivation ◽  
And Training

The study was conducted to identify the most difficult topic in elementary teacher education first-year social science curriculum as perceived by the student-teachers by using survey research design. The study also investigated the underlying reasons responsible for the student-teachers' difficulties in learning different topics. 218 student-teachers were selected using convenience sampling technique from five District Institutes of Education and Training (DIET), in Tamil Nadu State (India) for the study. The instrument used for data collection was a checklist designed by the researchers to elicit information from the student-teachers. The data collected were analysed using frequencies and percentages. The results showed that the topic namely, 'Reading the Globe, Maps and Atlas' was perceived as the most difficult topic in social science curriculum. The results also showed that teaching the topic without using the maps, lack of previous knowledge about the maps, the existence of vague concepts, heavy content load, and lack of interest and motivation to learn map concepts were the main reasons responsible for the student-teachers' difficulties in learning the topic.

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