Using Logistic Regression to Predict Wheat Yield in Western Zone of Haryana
|
|
- Bathsheba Dean
- 6 years ago
- Views:
Transcription
1 Using Logistic Regression to Predict Wheat Yield in Western Zone of Haryana Sudesh 1*, P. Verma 2 and U. Verma 1 1* PG Scholar, CCS Haryana Agricultural University, Hisar, India 2 PG Scholar ( ), IIT Kharagpur, India Abstract The effect of weather variables on wheat yield has been evaluated for Hisar, Bhiwani, Sirsa and Fatehabad districts comprising the western zone of Haryana. Zonal wheat yield models based on fortnightly maximum temperature, minimum temperature, rainfall, relative humidity and sunshine hours of the period to have been attempted within the framework of multiple linear regression and ordinal logistic regression. The probabilities obtained through ordinal logistic regression along with trend predicted yield were used to develop zonal yield models. The validity of the contending models were tested for the post sample period(s) to Evaluation of the forecasts were done by percent deviations from the real-time data and root mean square error. Key words: Multiple linear regression, ordinal logistic regression, wheat yield forecast, percent relative deviation, root mean square error Introduction Timely and effective pre-harvest forecast of the crop yield is important for advance planning, formulation and implementation of policies related to the crop procurement, distribution, price structure and import-export decisions etc. These are also useful to farmers to decide in advance their future prospects and course of action. The yield of any crop is affected by technological change and weather variability. It can be assumed that the technological factors will increase yield smoothly through time and therefore, year or some other parameters of time can be used to study the overall effect of technology on crop yield. Weather variability both within and between seasons is another uncontrollable source of variability in crop yield. Therefore, model based on weather and year as explanatory variables can be effectively used for forecasting crop yield. The official forecasts/advance estimates of major cereal and commercial crops are issued by the Directorate of Economics and Statistics, Ministry of Agriculture, New Delhi. However, the final estimates are given a few months after the actual harvest of the crop. Thus, one of the limitations of state Department of Agriculture (DOA) yield estimates is timeliness and quality of the statistics. Hence, there is a considerable scope of improvement in the conventional system. Various statistical approaches are in vogue for arriving at crop forecasts. Every approach has its own advantages and limitations. Regression analysis is one of the most widely used statistical techniques for modelling multifactor data. The inference drawn from multiple regression model often depends on the estimates of the individual regression icients. However in some situations, the problem of multicollinearity exists when there are near linear dependencies among the regressors. On the other hand, regression models using time series data occur quite oftenly and the assumption of uncorrelated or independent errors for time series data is often not appropriate. Thus, its use is limited to those settings where the normal distribution is valid and the assumption of a linear function relating the response to the predictors is given. Logistic regression (LR) is an increasingly popular statistical technique used to model the probability of discrete (i.e., binary or multinomial) outcomes. These models also show the extent to which changes in the values of the attributes may increase or decrease the predicted probability of event outcome. LR is part of a category of statistical models called generalized linear models. This broad class of models includes ordinary 33 Sudesh, P. Verma and U. Verma
2 regression and ANOVA, as well as multivariate statistics such as ANCOVA and log linear regression. LR allows one to predict a discrete outcome, such as group membership, from a set of variables that may be continuous, discrete, dichotomous, or a mix of any of these. However, the independent or predictor variables in LR can take any form. That is, logistic regression makes no assumption about the distribution of the independent variables. They do not have to be normally distributed, linearly related or of equal variance within each group. The relationship between the predictor and response variables is not a linear function in logistic regression. Various workers have attempted to develop methodology for weather based models of crop yield forecasting using different techniques. To mention a few; regression models by Agarwal et al. 2001, Dadhwal et al. 2005, Bazgeer et al.2007, Pandey et al. 2013); principal component analysis by Gervini and Rousson 2004, Wang 2012, Alkan et al. 2015, Verma et al. 2015,16; logistic regression by Greenland and Drescher 1993, Ghamdi 2002, Lin et al. 2013, Bergtold and Onukwugha 2014, Tanaka et al etc. Wheat is one of the most important cereal crops in India as it forms a major constituent of the staple diet of a large part of the population. India is the second largest producer among wheat growing countries of the World (Source: Haryana occupies third place for wheat production among the various states in India (Source: Haryana is self-sufficient in food grains production and is one of the top contributors of food grains to the central pool. In accordance with the targeted objective, the analysis has been carried out to develop zonal wheat yield models based on weather data by following multiple linear regression and ordinal logistic regression for district-level wheat yield assessment in western zone of Haryana. Study region and statistical methodology The Haryana state comprising of 21 districts is situated between 74 o 25 E to 77 o 38 E longitude and 27 o 40 N to 30 o 55 N latitude. The total geographical area of the state is sq. km. Hisar, Bhiwani, Sirsa and Fatehabad districts comprising the western zone of the state have been considered for the model building. The Department of Agriculture wheat yield statistics of the study region from to published by Bureau of Economics and Statistics (BES), Haryana were collected for the purpose. Weather data i.e. maximum temperature, minimum temperature, rainfall, relative humidity and sunshine hours of Hisar district for the same period were collected from Department of Agri. Meteorology, CCS HAU, Hisar. Year (time) variable was included to take care of the variation between districts within zone as the weather data were not available for all the districts, however, the zonal model utilized the same weather information in the adjoining districts under the zone. The weather variables affect the crop differently during different phases of its growth period. Thus, to integrate the weather variables over different growth phases, the crop growth period was divided into 11 fortnights. It is basically a winter crop and is grown in the rabi season during October-November to March- April. Data for the last one month of the crop season were excluded, as the idea behind the study was to predict yield(s) about 4-5 weeks before the crop harvest. Thus, weather data starting from 1 st fortnight of November to 1 month before harvest over the period to were utilized for the model building (crop growth period: 1 st November to 15 th April). Five-steps ahead (out of-model development period i.e , , , and ) district-level wheat yield forecasts have been obtained from the developed zonal models. The multiple linear regression model considered may be written in the form Y=Xb+ε; where Y is an (n l) vector of observations (DOA yields), X is an (n p) matrix of known form (weather variables & trend yield), b is a (p l) vector of parameters, ε is an (n l) vector of errors and E(ε)=0, V(ε)= Iσ 2, so the elements of ε are uncorrelated. Since E(ε)=0, an alternative way of writing the 34 Sudesh, P. Verma and U. Verma
3 model is E(Y)= Xb. The normal equations ( X X ) b = X Y are fitted by least squares technique (here Y, X & b are same as above and ( X X ) is the dispersion matrix) providing the solution b 1 (X' X) X' Y. Logistic regression with ordinal response variable If the response variable Y is ordinal, the categories can be ordered in a natural way such as good/moderate/bad. One way to take account of the ordering is the use of cumulative probabilities, cumulative odd and cumulative logits. Considering k+1 ordered categories, these quantities are defined by P(Y i) = p 1 + +p i odds (Y i) = = logit (Y i) = ln ( ), i = 1,,k The cumulative logistic model for ordinal response data is given by Logit (Y ) = α i +β i1 x 1 + +β ip x p, i=1,..,k Thus, we have k model equations and logistic icient β ij for each category/covariate combination. Zonal wheat yield modeling with three groups For this empirical study, crop years were categorized into three groups viz., adverse, normal and congenial. Using weather variables in these three groups, probabilities were obtained by ordinal logistic regression. These probabilities along with trend predicted yield were used for the development of zonal yield forecast models using stepwise regression procedure. When dependent variable has an ordinal nature taking three values say zero, one, two; then the ordinal logistic regression model is given as: and + where P 0 is probability of Y = 0, is probability of Y=1 and P 2 is probability of Y= 2, α s are the intercepts and β i s are the regression icients. Zonal yield forecast models were fitted using stepwise regression taking probabilities P 1 and P 2 along with trend yield as regressors. The model fitted was Yield = a + b 1 P 1 + b 2 P 2 + b 3 T r + ε where a is intercept, b i s are the regression icients, P 1 and P 2 are the probabilities of Y=1 and Y=2, T r is trend yield and ε is error ~ N (0,σ 2 ). The contending models have been compared using 35 Sudesh, P. Verma and U. Verma
4 i) Percent Deviation (RD%) = {(observed yield forecasted yield)/observed yield}*100, it measures the deviation of forecast yield from the observed yield and ii) Root Mean Square Error (RMSE) as a measure of comparing two models and its formula is 1 2 n 2 1 RMSE O i E i, where O i and E i are the observed and forecasted values of the crop yield and n n i 1 is the number of years for which forecasting has been done. Results and Discussion Zonal yield models were fitted by taking weather variables/estimated response probabilities along with trend yield as regressors and DOA wheat yield as regressand. The best subsets of weather variables were selected using stepwise regression (Draper and Smith, 1981) if they had the highest adjusted R 2 and lowest standard error (SE) of estimate (Table 1). Further, the developed zonal models were used to obtain the district-level wheat yield estimates for the post sample period(s) , , , and Table 1. Parameter estimates and adjusted-r 2 of zonal wheat yield models. Model Intercept X 1 / X 2 / X 3 / X 4 / X 5 / X 6 / X 7 / Adj. R 2 SE Model T r Model T r TMX P TMX P TMN SSH SSH TMN Model 1 - Weather parameters and trend yield as regressors Model 2 - Estimated response probability and trend yield as regressors X 1, X 2,..,X 7 stand for regressors in the model T r - Trend yield TMX - Av. maximum temperature TMN - Av. minimum temperature SSH - Av. Sunshine Hours Pi - Estimated cell probability for response category 1,2,3 SE - Standard error of estimate Table 2. Percent deviations of fitted yield(s) from DOA yield(s) using alternative models. District/ Forecast years Hisar DOA Yield (q/ha) Fitted Yield (q/ha) Model-1 RD (%) Fitted Yield (q/ha) Model-2 RD (%) Sudesh, P. Verma and U. Verma
5 Bhiwani Sirsa Fatehabad DOAyield fittedyield Percentdeviation ( RD%) 100 DOA yield Table 3. Comparative view in terms of average absolute percent deviations and RMSEs of forecast yield(s) based on both the models. Districts Average absolute percent deviation(s) RMSEs Hisar Bhiwani Model-1 Model-2 Model-1 Model Sudesh, P. Verma and U. Verma
6 Sirsa Fatehabad The performance(s) of the zonal yield equations were compared on the basis of statistics like adj-r 2, percent deviations of forecasts from the observed yields and RMSEs. The results showed that there is a considerable improvement in wheat yield assessment using ordinal logistic regression and the percent deviations from DOA yields are within acceptable limits. It indicates the usefulness of zonal yield models for district-level wheat yield assessment in western zone of Haryana. Moreover, the developed models provide reliable forecasts of crop yield at least one month in advance of the crop harvest while the DOA yields are obtained quite late after the actual harvest of the crop. References Agarwal, R., Jain, R.C. and Mehta, S.C. (2001). Yield forecast based on weather variable and agricultural inputs on agro-climatic zone basis. Ind. J. Agric. Sci. 71(7), Alkan, B.B., Atakan, C. and Alkan, N. (2015). A comparison of different procedures for principal component analysis in the presence of outliers. Journal of Applied Statistics 42(22), Bergtold, J.S. and Onukwugha, E. (2014). The probabilistic reduction approach to specifying multinomial logistic regression models in health outcomes research. Journal of Applied Statistics 41(10), Boken, V.K. (2000). Forecasting spring wheat yield using time series analysis. A case study for the Canadian prairies. Agro. J. 92, Dadhwal, V.K., Sehgal, V.K., Singh, R.P. and Rajak, D.R. (2005). Wheat yield modeling using satellite remote sensing with weather data: Recent Indian experience. Mausam 54, Draper, N.R. and Smith, H. (1981). Applied Regression Analysis, 2 nd ed. New York: John Wiley. Gervini, D. and Rousson, V. (2004). Criteria for evaluating dimension Reducing components for multivariate data. The American Statistician 58(1), Ghamdi, A.S. (2002). Using logistic regression to estimate the influence of accident factors on accident severity. King Saud University, Saudi Arabia 34, Greenland, S. and Drescher, K. (1993) Maximum likelihood estimation of the attributable fraction from logistic models. Biometrics 49, Lin, H., Wang, C., Liu, P. and Holtkamp, D.J. (2013). Construction of disease risk scoring systems using logistic group lasso: application to porcine reproductive and respiratory syndrome survey data. Journal of Applied Statistics 40(4), Pandey, K.K., Rai, V.N., Sisodia, B.V.S., Bharati, A.K. and Gairola, K.C. (2013) Pre -harvest forecast models based on weather variable and weather indices for Eastern U.P. Advance in Bioresearch 4(2), Tanaka, H., Obayashi, C. and Takagi,Y. (2015). On second order admissibilities in two-parameter logistic regression model. Communications in Statistics Theory and Methods 44, Verma, U., Aneja, D.R. and Hooda, B.K. (2015). Principal component technique for pre-harvest estimation of cotton yield based on plant biometrical characters. J. of Cotton Research and Development 29(2), Verma, U., Piepho, H.P., Goyal, A., Ogutu, J.O. and Kalubarme, M.H. (2016). Role of Climatic Variables and Crop Condition Term for Mustard Yield Prediction in Haryana (India). International J. of Agricultural and Statistical Sciences 12(1), Wang, W. (2012). Bayesian principal component regression with data-driven component selection. Journal of Applied Statistics 39(6), Sudesh, P. Verma and U. Verma
Wheat Yield Prediction using Weather based Statistical Model in Central Punjab
Vol. 15, No. 2, pp. 157-162 (2015) Journal of Agricultural Physics ISSN 0973-032X http://www.agrophysics.in Research Article Wheat Yield Prediction using Weather based Statistical Model in Central Punjab
More informationCrop Weather Relationship and Cane Yield Prediction of Sugarcane in Bihar
Vol. 14, No. 2, pp. 150-155 (2014) Journal of Agricultural Physics ISSN 0973-032X http://www.agrophysics.in Research Article Crop Weather Relationship and Cane Yield Prediction of Sugarcane in Bihar ABDUS
More informationDevelopment of district-level Agro-meteorological Cotton Yield Models in Punjab
International Journal of Environmental Research and Development. ISSN 2249-3131 Volume 6, Number 1 (2016), pp. 17-32 Research India Publications http://www.ripublication.com Development of district-level
More informationImpact of cropped area and year on production of chilli, ginger and turmeric crops in North-East region of India
Agric. Sci. Digest., 35 (1) 2015: 7-12 Print ISSN:0253-150X / Online ISSN:0976-0547 AGRICULTURAL RESEARCH COMMUNICATION CENTRE www.arccjournals.com Impact of cropped area and year on production of chilli,
More informationProductivity Zoning of Indian Mustard (Brassica spp.) in Haryana State by Climatic and Physical Factors
Available online at www.ijpab.com Anurag et al Int. J. Pure App. Biosci. 5 (5): 1075-1079 (2017) ISSN: 2320 7051 DOI: http://dx.doi.org/10.18782/2320-7051.5194 ISSN: 2320 7051 Int. J. Pure App. Biosci.
More informationRegional Disparity in Cropping Intensity and Relative Impact of Irrigation in Haryana
IOSR Journal of Business and Management (IOSR-JBM) e-issn: 2278-487X, p-issn: 2319-7668. Volume 18, Issue 9.Ver. III (September. 2016), PP 41-45 www.iosrjournals.org Regional Disparity in Cropping Intensity
More informationFORECAST MODELS FOR SUGARCANE
Pak. J Agri. Sci., Vol. 41(1-2), 2004 FORECAST MODELS FOR SUGARCANE IN PAKISTAN M. Asif Masoood* and Malik Anver Javed Biometrics Programme, Social Sciences Institute, National Agricultural Research Centre,
More informationEffect of growing degree day on different growth processes of wheat (Triticum aestivum L.)
Journal of Crop and Weed, 8(2):18-22(2012) Effect of growing degree day on different growth processes of wheat (Triticum aestivum L.) S. BASU, M. PARYA, S. K. DUTTA, S. JENA, S. MAJI, R. NATH, 1 D. MAZUMDAR
More informationTRENDS IN GROWTH AND DETERMINANTS OF THE RICE PRODUCTIVITY IN HARYANA: AN EMPIRICAL STUDY
TRENDS IN GROWTH AND DETERMINANTS OF THE RICE PRODUCTIVITY IN Satinder Kumar* Somjit** HARYANA: AN EMPIRICAL STUDY Abstract: Through this study, we analyzed the growth trends of rice crop in India & Haryana
More informationWinsor Approach in Regression Analysis. with Outlier
Applied Mathematical Sciences, Vol. 11, 2017, no. 41, 2031-2046 HIKARI Ltd, www.m-hikari.com https://doi.org/10.12988/ams.2017.76214 Winsor Approach in Regression Analysis with Outlier Murih Pusparum Qasa
More informationJoint Adoption of Conservation Agricultural Practices by Row Crop Producers in Alabama
Joint Adoption of Conservation Agricultural Practices by Row Crop Producers in Alabama Jason S. Bergtold, Agricultural Economist, USDA-ARS-NSDL, Auburn, AL Manik Anand, Graduate Student, Auburn University,
More informationThermal requirement of indian mustard (Brassica juncea) at different phonological stages under late sown condition
Ind J Plant Physiol. (July September 2014) 19(3):238 243 DOI 10.1007/s40502-014-0072-0 ORIGINAL ARTICLE Thermal requirement of indian mustard (Brassica juncea) at different phonological stages under late
More informationCrop Water Requirement Estimation by using CROPWAT Model: A Case Study of Halali Dam Command Area, Vidisha District, Madhya Pradesh, India
Volume-5, Issue-3, June-2015 International Journal of Engineering and Management Research Page Number: 553-557 Crop Water Requirement Estimation by using CROPWAT Model: A Case Study of Halali Dam Command
More informationAgrometeorological Indices Requirement for Wheat Crop under Different Irrigation Levels
International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 6 Number 4 (2017) pp. 1547-1553 Journal homepage: http://www.ijcmas.com Original Research Article https://doi.org/10.20546/ijcmas.2017.604.190
More informationGENETIC VARIABILITY AND DIVERGENCE STUDIES IN OATS (AVENA SATIVA L.) FOR GREEN FODDER AND GRAIN YIELD
Forage Res., 42 (1) : pp. 51-55 (2016) http://forageresearch.in GENETIC VARIABILITY AND DIVERGENCE STUDIES IN OATS (AVENA SATIVA L.) FOR GREEN FODDER AND GRAIN YIELD JAIPAL AND S. S. SHEKHAWAT* AICRP on
More informationSUSTAINABLE AGRICULTURE DEVELOPMENT IN INDIA: A CASE STUDY OF UTTAR PRADESH ABSTRACT
SUSTAINABLE AGRICULTURE DEVELOPMENT IN INDIA: A CASE STUDY OF UTTAR PRADESH ABSTRACT Agriculture is a critical sector of the Indian economy. It forms the backbone of development in the country. An average
More informationTrends of Rainfall in Different Sectors of Uttar Pradesh Under Present Scenario of Climate Change
Trends of Rainfall in Different Sectors of Uttar Pradesh Under Present Scenario of Climate Change Krishna Deo, Padmakar Tripathi, Arvind Kumar, Akhilesh Gupta*, K. K. Singh**, S. R. Mishra and Ajit Singh
More informationChapter 3. Database and Research Methodology
Chapter 3 Database and Research Methodology In research, the research plan needs to be cautiously designed to yield results that are as objective as realistic. It is the main part of a grant application
More informationChange in Land Use and Cropping Pattern in Assam: An Economic Analysis
Economic Affairs, Vol. 63, No. 1, pp. 39-43, March 2018 DOI: 10.30954/0424-2513.2018.00150.5 2018 New Delhi Publishers. All rights reserved Change in and Use and Cropping Pattern in Assam: An Economic
More informationCorrelation of weather parameters with development of leaf spot of safflower caused by Alternaria carthami
Correlation of weather parameters with development of leaf spot of safflower caused by Alternaria carthami M. A. Gud, D. R. Murumkar, S. K. Shinde and J. R. Kadam All India Coordinated Research Project
More informationESTIMATION OF TECHNICAL EFFICIENCY ON WHEAT FARMS IN NORTHERN INDIA A PANEL DATA ANALYSIS. Dr. S. K. Goyal
ESTIMATION OF TECHNICAL EFFICIENCY ON WHEAT FARMS IN NORTHERN INDIA A PANEL DATA ANALYSIS Dr. S. K. Goyal Assistant Professor, Department of agricultural Economics, CCS Haryana Agricultural University,
More informationIntroduction to yield forecasting with CST
Introduction to yield forecasting with CST H. Kerdiles (JRC), H. Boogaard & S. Hoek (Alterra) Harare, Zimbabwe 26 Oct 2016 Yield variability: can you rank the maize fields according to their yield? Same
More informationEFFECT OF ORGANIC FARMING ON DRY FODDER YIELD, GRAIN YIELD, NET RETURNS AND SOIL SFERTILITY IN MUNG BEAN- WHEAT (TALL) PRODUCTION SYSTEM
Forage Res., 38 (3) : pp. 177-181 (2012) http://forageresearch.in EFFECT OF ORGANIC FARMING ON DRY FODDER YIELD, GRAIN YIELD, NET RETURNS AND SOIL SFERTILITY IN MUNG BEAN- WHEAT (TALL) PRODUCTION SYSTEM
More informationGrowth Models and Projection of Area, Production and Productivity of Wheat in India and Uttar Pradesh, India
International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 6 Number 11 (2017) pp. 2587-2595 Journal homepage: http://www.ijcmas.com Original Research Article https://doi.org/10.20546/ijcmas.2017.611.303
More informationHARI RAM*, GURJOT SINGH, G S MAVI and V S SOHU
Journal 147 of Agrometeorology 14 (2) : 147-153 (December HARI 2012) RAM et al [Vol. 14, No. 2 Accumulated heat unit requirement and yield of irrigated wheat (Triticum aestivum L.) varieties under different
More informationAN ECONOMETRIC ANALYSIS OF THE RELATIONSHIP BETWEEN AGRICULTURAL PRODUCTION AND ECONOMIC GROWTH IN ZIMBABWE
AN ECONOMETRIC ANALYSIS OF THE RELATIONSHIP BETWEEN AGRICULTURAL PRODUCTION AND ECONOMIC GROWTH IN ZIMBABWE Alexander Mapfumo, Researcher Great Zimbabwe University, Masvingo, Zimbabwe E-mail: allymaps@gmail.com
More informationAdoption of Integrated Pest Management Practices in Paddy and Cotton : A Case Study in Haryana and Punjab
Agricultural Economics Research Review Vol. 21 July-December 2008 pp 221-226 Adoption of Integrated Pest Management Practices in Paddy and Cotton : A Case Study in Haryana and Punjab Alka Singh* a, A.K.
More informationModeling Haze Problems in the North of Thailand using Logistic Regression
J. Math. Fund. Sci., Vol. 46, No. 2, 2014, 183-193 183 Modeling Haze Problems in the North of Thailand using Logistic Regression Busayamas Pimpunchat 1, Khwansiri Sirimangkhala 1 & Suwannee Junyapoon 2
More informationDecomposition analysis and acreage response of cotton in western Vidarbha
J. Cotton Res. Dev. 30 (2) 294-301 (July, 2016) Decomposition analysis and acreage response of cotton in western Vidarbha K.R. MANKAWADE, S.S. THAKARE, D.H. ULEMALE Shri Shivaji Agriculture College, Amravati
More informationAgro-meteorological Indices to Predict Plant Stages and Yield of Wheat for Foot Hills of Western Himalayas
International Journal of Agriculture and Food Science Technology. ISSN 49-3050, Volume 4, Number 9 (013), pp. 909-914 Research India Publications http://www.ripublication.com/ ijafst.htm Agro-meteorological
More informationWEATHER BASED PRE-HARVEST CROP FORECASTING - AN OVERVIEW
WEATHER BASED PRE-HARVEST CROP FORECASTING - AN OVERVIEW Ranjana Agrawal Indian Agricultural Statistics Research Institute, New Delhi-110012 Reliable and timely forecasts of crop production are required
More informationCrop Yield Forecasting by Adaptive Neuro Fuzzy Inference System
Abstract Crop Yield Forecasting by Adaptive Neuro Fuzzy Inference System Pankaj Kumar* VCSG College of Horticulture, GBPUA&T, Pantnagar, Uttarakhand *pankaj591@gmail.com Meteorological uncertainties affect
More informationGrowth and export dimensions of Indian turmeric
Internationl Research Journal of Agricultural Economics and Statistics Volume 4 Issue 1 March, 2013 91-97 Research Paper Growth and export dimensions of Indian turmeric VINOD R. NAIK AND S.B. HOSAMANI
More informationStability and regression analysis in elite genotypes of sugarcane (Saccharum spp hybrid complex)
Vol. 9(37), pp. 2846-2853, 11 September, 2014 DOI: 10.5897/AJAR2013.8444 Article Number: D051FB647204 ISSN 1991-637X Copyright 2014 Author(s) retain the copyright of this article http://www.academicjournals.org/ajar
More informationGrowth, Export Performance and Competitiveness of Basmati and Non-Basmati Rice of India-an Markov Chain Approach
International Journal of Agriculture, Environment and Biotechnology Citation: IJAEB: 9(2): 305-311 April 2016 DOI Number: 10.5958/2230-732X.2016.00040.1 2016 New Delhi Publishers. All rights reserved AGRICULTURAL
More informationStudy the heat unit requirement of soybean (Glycine max) varieties under varied weather condition at Parbhani
2018; 7(3): 526-530 E-ISSN: 2278-4136 P-ISSN: 2349-8234 JPP 2018; 7(3): 526-530 Received: 04-03-2018 Accepted: 06-04-2018 KK Chavan Research Scholar, Deptt. of AM Khobragade Asst. Professor, Deptt. Of
More informationREFERENCE EVAPOTRANSPIRATION ESTIMATION USING CROPWAT MODEL AT LUDHIANA DISTRICT (PUNJAB) A. Patel 1, R. Sharda 2, S. Patel 3 and P.
International Journal of Science, Environment and Technology, Vol. 6, No 1, 2017, 620 629 ISSN 2278-3687 (O) 2277-663X (P) REFERENCE EVAPOTRANSPIRATION ESTIMATION USING CROPWAT MODEL AT LUDHIANA DISTRICT
More informationMEASUREMENT OF PRODUCTIVITY AND EFFICIENCY OF POTATO PRODUCTION IN TWO SELECTED AREAS OF BANGLADESH: A TRANSLOG STOCHASTIC FRONTIER ANALYSIS
Progress. Agric. 21(1 & 2): 233 245, 2010 ISSN 1017-8139 MEASUREMENT OF PRODUCTIVITY AND EFFICIENCY OF POTATO PRODUCTION IN TWO SELECTED AREAS OF BANGLADESH: A TRANSLOG STOCHASTIC FRONTIER ANALYSIS A.
More informationApplying the Path Analysis Method to determine the significance of input parameters on the output of Derbendikhan power station
Energy and Sustainability 123 Applying the ath Analysis Method to determine the significance of input parameters on the output of Derbendikhan power station R. A. Saeed 1, M. M. Faqe 1 & F. M. Khoshnaw
More informationHEAT USE EFFICIENCY AND HELIO-THERMAL UNITS FOR MAIZE GENOTYPES AS INFLUENCED BY DATES OF SOWING UNDER SOUTHERN TRANSITIONAL ZONE OF KARNATAKA STATE
I.J.S.N., VOL. 2(3) 2011: 529-533 ISSN 2229 6441 HEAT USE EFFICIENCY AND HELIO-THERMAL UNITS FOR MAIZE GENOTYPES AS INFLUENCED BY DATES OF SOWING UNDER SOUTHERN TRANSITIONAL ZONE OF KARNATAKA STATE 1 Girijesh,
More informationEfficiency of Different Selection Indices for Desired Gain in Reproduction and Production Traits in Hariana Cattle
789 Efficiency of Different Selection Indices for Desired Gain in Reproduction and Production Traits in Hariana Cattle Ravinder Kaushik and A. S. Khanna* Department of Animal Breeding, C C S Haryana Agricultural
More informationRole of Co-Operative Societies in Adoption of Improved Production Technology by Sapota Growers
Indian Res. J. Ext. Edu. 13 (3), September, 2013 59 Role of Co-Operative Societies in Adoption of Improved Production Technology by Sapota Growers B.M. Mehta 1, Madhuri Sonawane 2 and R.F. Thakor 3 1.
More informationAgrometeorological-Heat and Energy use of Kinnow Mandarin (Citrus nobilis Lour * Citrus deliciosa Tenore)
Available online at www.ijpab.com DOI: http://dx.doi.org/10.18782/2320-7051.2590 ISSN: 2320 7051 Int. J. Pure App. Biosci. 5 (2): 506-512 (2017) Research Article Agrometeorological-Heat and Energy use
More informationWater requirement of wheat crop for optimum production using CROPWAT model
2017; 5(3): 338-342 ISSN (E): 2320-3862 ISSN (P): 2394-0530 NAAS Rating 2017: 3.53 JMPS 2017; 5(3): 338-342 2017 JMPS Received: 20-03-2017 Accepted: 22-04-2017 Krishna Deo SR Mishra AK Singh AN Mishra
More informationComparison of Simulated and Statistical Model Prediction of Wheat at District Scale Yield under Sub-Temperate Climate of North Western Himalayas
Available online at www.ijpab.com Verma et al Int. J. Pure App. Biosci. 5 (4): 1035-1050 (2017) ISSN: 2320 7051 DOI: http://dx.doi.org/10.18782/2320-7051.5236 ISSN: 2320 7051 Int. J. Pure App. Biosci.
More informationGrowth Rates and Decomposition Analysis of Onion Production in Rajasthan State of India
Economic Affairs, Vol. 62, No. 1, pp. 157-161, March 2017 DOI: 10.5958/2230-7311.2017.00051.4 2017 New Delhi Publishers. All rights reserved Growth Rates and Decomposition Analysis of Onion in Rajasthan
More informationOPTIMUM IRRIGATION OF WHEAT PRODUCTION AT BAU FARM
International Journal of Innovation and Applied Studies ISSN 2028-9324 Vol. 9 No. 3 Nov. 2014, pp. 1113-1123 2014 Innovative Space of Scientific Research Journals http://www.ijias.issr-journals.org/ OPTIMUM
More informationSTABILITY ANALYSIS OF YIELD AND RELATED TRAITS IN CHICKPEA (CICER ARIETINUM L.)
Legume Res., 37 (6) : 641-645, 2014 doi:10.5958/0976-0571.2014.00689.4 AGRICULTURAL RESEARCH COMMUNICATION CENTRE www.arccjournals.com / www.legumeresearch.in STABILITY ANALYSIS OF YIELD AND RELATED TRAITS
More informationMETEOROLOGICAL DROUGHT ASSESSMENT IN RAIPUR DISTRICT OF CHHATTISGARH STATE, INDIA
Plant Archives Vol. 15 No. 1, 2015 pp. 465-469 ISSN 0972-5210 METEOROLOGICAL DROUGHT ASSESSMENT IN RAIPUR DISTRICT OF CHHATTISGARH STATE, INDIA Sanjay Bhelawe*, J. L. Chaudhary, N. Manikandan and Rupesh
More informationScope and Prospects of Agricultural Production in Kolhapur District of Maharashtra, India
International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 6 Number 11 (2017) pp. 2478-2485 Journal homepage: http://www.ijcmas.com Original Research Article https://doi.org/10.20546/ijcmas.2017.611.291
More informationCREDIT RISK MODELLING Using SAS
Basic Modelling Concepts Advance Credit Risk Model Development Scorecard Model Development Credit Risk Regulatory Guidelines 70 HOURS Practical Learning Live Online Classroom Weekends DexLab Certified
More informationGENETIC AND ENVIRONMENTAL FACTORS INFLUENCING PERSISTENCY OF MILK PRODUCTION IN KARAN FRIES CATTLE*
Indian J. Anim. Res., 40 (2): 95-100, 2006 GENETIC AND ENVIRONMENTAL FACTORS INFLUENCING PERSISTENCY OF MILK PRODUCTION IN KARAN FRIES CATTLE* Amit Kumar and Avtar Singh Dairy Cattle Breeding Division,
More informationQuantification of microclimate of cotton hybrids under different sowing environments
2018; 7(2): 1032-1040 E-ISSN: 2278-4136 P-ISSN: 2349-8234 JPP 2018; 7(2): 1032-1040 Received: 13-01-2018 Accepted: 14-02-2018 Abhijeet Sharma ML Khichar Department of Agricultural Meteorology, CCS Haryana
More informationA Statistical Analysis on Instability and Seasonal Component in the Price Series of Major Domestic Groundnut Markets in India
International Journal of Current Microbiology and Applied Sciences ISSN: 2319-776 Volume 6 Number 11 (217) pp. 815-823 Journal homepage: http://www.ijcmas.com Original Research Article https://doi.org/1.2546/ijcmas.217.611.96
More informationIndia. India Grain Voluntary Update - October 2017
THIS REPORT CONTAINS ASSESSMENTS OF COMMODITY AND TRADE ISSUES MADE BY USDA STAFF AND NOT NECESSARILY STATEMENTS OF OFFICIAL U.S. GOVERNMENT POLICY Voluntary - Public Date: 10/3/2017 GAIN Report Number:
More informationProbability Distribution Analysis of Rainfall Data for Western Maharashtra Region
Probability Distribution Analysis of Rainfall Data for Western Maharashtra Region Swami Shivprasad T. 1, Anandrao Deshmukh 2, Ganesh Patil 3, Sagar Kahar 4 1 Department Civil Engineering, Rajarshi Shahu
More informationRISK ASSESSMENT OF CLIMATE VARIABILITY ON RICE PRODUCTIVITY IN SINDH PROVINCE OF PAKISTAN
ISSN 1023-1072 : 68-77 RISK ASSESSMENT OF CLIMATE VARIABILITY ON RICE PRODUCTIVITY IN SINDH PROVINCE OF PAKISTAN M. Joyo 1, N. Ram 2 and H. Magsi 1 1 1 Department of Agricultural Economics, Sindh Agriculture
More informationDEMAND, SUPPLY ESTIMATION AND PROJECTION OF WHEAT SITUATION IN BANGLADESH
Bangladesh J. Agric. Econs XXVII, 2 (2004) 25-44 DEMAND, SUPPLY ESTIMATION AND PROJECTION OF WHEAT SITUATION IN BANGLADESH M.A.Matin Shamsul Alam ABSTRACT This paper fills an information gap regarding
More informationR. V. JOSHI, B. J. PATEL AND K. M. PATEL*
Forage Res., 41 (2) : pp. 104-108 (2015) http://forageresearch.in EFFECT OF NITROGEN LEVELS AND TIME OF APPLICATION ON GROWTH, YIELD, QUALITY, NITROGEN, PHOSPHORUS CONTENT AND UPTAKE FOR SEED PRODUCTION
More informationWelfare Effects of Selected Food-grain Policies in India
Agricultural Economics, 4 ( 1990) 179-192 Elsevier Science Publishers B.V., Amsterdam- Printed in The Netherlands 179 Welfare Effects of Selected Food-grain Policies in India V.K. Chetty and P.V. Srinivasan
More informationEffect of Water and Nitrogen Management on Water Productivity and Nitrogen Use Efficiency of Wheat in a Semi-arid Environment
International Journal of Agriculture and Food Science Technology. ISSN 2249-3050, Volume 4, Number 7 (2013), pp. 727-732 Research India Publications http://www.ripublication.com/ ijafst.htm Effect of Water
More informationModified Ratio Estimators for Population Mean Using Function of Quartiles of Auxiliary Variable
Bonfring International Journal of Industrial Engineering and Management Science, Vol. 2, No. 2, June 212 19 Modified Ratio Estimators for Population Mean Using Function of Quartiles of Auxiliary Variable
More informationTrend and seasonal analysis of wheat in selected market of Sriganganagar district
Trend and seasonal analysis of wheat in selected market of Sriganganagar district Meera 1 and Hemant Sharma 2 1 Department of Agricultural Economics, Swami Keshwanand Rajasthan Agricultural University,
More informationExtent and Correlates of Knowledge of Farmers regarding Scientific Potato Production Technologies in Himachal Pradesh
International Journal of Agriculture, Environment and Biotechnology Citation: IJAEB: 8(2): 381-385 June 2015 DOI Number: 10.5958/2230-732X.2015.00046.7 2015 New Delhi Publishers. All rights reserved AGRICULTURE
More informationEconomic variables and electricity consumption in Northern Cyprus
Energy 26 (2001) 355 362 www.elsevier.com/locate/energy Economic variables and electricity consumption in Northern Cyprus F. Egelioglu a,*, A.A. Mohamad a, H. Guven b a Department of Mechanical Engineering,
More informationComparative economics of Banana cultivation in Anand district of Gujarat
Comparative economics of Banana cultivation in Anand district of Gujarat A.K. Dave 1, Y.C. Zala 2 and R.S. Pundir 3 * 1 Department of Agricultural Economics, B.A. College of Agriculture, Anand Agricultural
More informationMarketable Surplus and Price-Spread for Maize in Hamirpur District of Himachal Pradesh
Agricultural Economics Research Review Vol. 18 January-June 2005 pp 39-49 Marketable Surplus and Price-Spread for Maize in Hamirpur District of Himachal Pradesh S.K. Chauhan and Amit Chhabra Abstract A
More informationTHE PERFORMANCE OF NEW PEARL MILLET HYBRIDS WITH GREENGRAM UNDER SOLE CROPPING AND INTERCROPPING SYSTEMS IN SEMI-ARID ENVIRONMENT
Forage Res., 43 (1) : pp. 26-30 (2017) http://forageresearch.in THE PERFORMANCE OF NEW PEARL MILLET HYBRIDS WITH GREENGRAM UNDER SOLE CROPPING AND INTERCROPPING SYSTEMS IN SEMI-ARID ENVIRONMENT RENU*,
More informationCritical period for weed control in field pea
Legume Research, 39 (1) 2016: 86-90 Print ISSN:0250-5371 / Online ISSN:0976-0571 AGRICULTURAL RESEARCH COMMUNICATION CENTRE www.arccjournals.com/www.legumeresearch.in Critical period for weed control in
More informationVeena 1, Savita 2, Reetu Sharma 3 Sarvan 4. Haryana Space Applications Centre (HARSAC),
& Fruit Mapping of Adampur and Hisar-IInd Blocks of Hisar District Using On Screening Visual Interpretation Approach on WV-2 Data Veena 1, Savita 2, Reetu Sharma 3 Sarvan 4 Haryana Space Applications Centre
More informationEffect of Change in Indian Rice Price on Nepalese Rice Market: A Partial Equilibrium Model
Agricultural Economics Research Review Vol. 29 (No.1) January-June 2016 pp 127-133 DOI: 10.5958/0974-0279.2016.00025.2 Effect of Change in Indian Rice Price on Nepalese Rice Market: A Partial Equilibrium
More information). Individual correlation coefficient with disease severity showed that, among the 10 meteorological factors VP, T min
Effect of Varieties, Levels of Nitrogen and Meteorological Factors on Severity of Foliar Blight of Barley Caused by Helminthosporium... National Academy of Agricultural Science (NAAS) Rating : 3. 03 Serials
More informationJapanese Demand for Wheat Characteristics: A Market Share Approach. By: Joe Parcell. and. Kyle Stiegert*
Japanese Demand for Wheat Characteristics: A Market Share Approach By: Joe Parcell and Kyle Stiegert* Paper presented at the Western Agricultural Economics Association Annual Meetings, Logan, Utah, July
More informationPOTATO (SOLANUM TUBEROSUM L.) TUBER YIELD AS AFFECTED BY PLANTING TIMES AND FERTILIZER DOSES UNDER SANDY LOAM SOILS
Indian J. Agric. Res.., 47 (6) : 496-502, 2013 AGRICULTURAL RESEARCH COMMUNICATION CENTRE www.arccjournals.com / indianjournals.com POTATO (SOLANUM TUBEROSUM L.) TUBER YIELD AS AFFECTED BY PLANTING TIMES
More informationUPDATE OF THE NEAC MODAL-SPLIT MODEL Leest, E.E.G.A. van der Duijnisveld, M.A.G. Hilferink, P.B.D. NEA Transport research and training
UPDATE OF THE NEAC MODAL-SPLIT MODEL Leest, E.E.G.A. van der Duijnisveld, M.A.G. Hilferink, P.B.D. NEA Transport research and training 1 INTRODUCTION The NEAC model and information system consists of models
More informationAn economic inquiry into adoption of non-conventional bio pesticides and fungicides R.Ravikumar* 1, S. Ramesh Kumar 2 and P.
2015 RELS ISSN: 0974-4908 http://rels.comxa.com Res. Environ. Life Sci. rel_sci@yahoo.com 8 (1) 21-26 (2015) An economic inquiry into adoption of non-conventional bio pesticides and fungicides R.Ravikumar*
More informationGrowth and Pattern of Fertilizer Consumption in Haryana
Available online at: http://euroasiapub.org pp. 138~148 Thomson Reuters Researcher ID: L-5236-2015 Growth and Pattern of Fertilizer Consumption in Haryana Dr. Sandeep Kumar 1, Lecturer Economics, dept.
More informationResource Use Efficiency of Major Field Crops in Reasi District of Jammu Region of Jammu and Kashmir State
Agro Economist - An International Journal Citation: AE: 4(1): 15-19, June 2017 DOI: 10.5958/2394-8159.2017.00004.4 2017 Renu Publishers. All rights reserved Resource Use Efficiency of Major Field Crops
More informationPerformance of Rainfed Wheat Based Intercropping in Kaymore Plateau
International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 6 Number 7 (2017) pp. 2619-2625 Journal homepage: http://www.ijcmas.com Original Research Article https://doi.org/10.20546/ijcmas.2017.607.369
More informationLINKING GEOGRAPHIC ORIGINS OF PLANT GERMPLASM WITH CLIMATIC DATA
LINKING GEOGRAPHIC ORIGINS OF PLANT GERMPLASM WITH CLIMATIC DATA Sunil Archak 1, Anuj Singh 1, DP Semwal 1, Sushil Pandey 1, Sarika Mittra 2, PN Mathur 2, Pramod Agarwal 3 and KC Bansal 1 1 National Bureau
More informationGrowth in area, production and productivity of major crops in Karnataka*
Karnataka J. Agric. Sci.,25 (4) : (431-436) 2012 Introduction Growth in area, production and productivity of major crops in Karnataka* SARASWATI POUDEL ACHARYA, H. BASAVARAJA, L. B. KUNNAL, S. B. MAHAJANASHETTI
More informationEffect of Weather Variables on Wheat Yield
Available online at www.ijpab.com DOI: http://dx.doi.org/10.18782/2320-7051.5837 ISSN: 2320 7051 Int. J. Pure App. Biosci. 5 (6): 971-975 (2017) Research Article Effect of Weather Variables on Wheat Yield
More informationKefei Chen, Rebecca O'Leary & Fiona Evans Department of Agriculture and Food, WA
Yield prediction using real paddock data and generalised additive modelling Kefei Chen, Rebecca O'Leary & Fiona Evans Department of Agriculture and Food, WA Wheat yield prediction Yield prediction is one
More informationANALYSIS OF INTER-TEMPORAL PRICING EFFI- CIENCY OF SORGHUM IN GUYUK LOCAL GOVERN- MENT OF ADAMAWA STATE, NIGERIA
ISSN - 2277-078X UNAAB 2010 Journal of Humanities, Social Sciences and Creative Arts ANALYSIS OF INTER-TEMPORAL PRICING EFFI- CIENCY OF SORGHUM IN GUYUK LOCAL GOVERN- MENT OF ADAMAWA STATE, NIGERIA *D.C.
More informationThe SPSS Sample Problem To demonstrate these concepts, we will work the sample problem for logistic regression in SPSS Professional Statistics 7.5, pa
The SPSS Sample Problem To demonstrate these concepts, we will work the sample problem for logistic regression in SPSS Professional Statistics 7.5, pages 37-64. The description of the problem can be found
More informationImpact of climate change on wheat productivity in Ludhiana and Bathinda of Punjab
Indian J. Agric. Res., 49 (4) 2015: 368-372 Print ISSN:0367-8245 / Online ISSN:0976-058X AGRICULTURAL RESEARCH COMMUNICATION CENTRE www.arccjournals.com/www.ijarjournal.com Impact of climate change on
More informationYield trend estimation in the presence of non-constant technological change and weather effects
Paper prepared for the 123 rd EAAE Seminar PRICE VOLATILITY AND FARM INCOME STABILISATION Modelling Outcomes and Assessing Market and Policy Based Responses Dublin, February 23-24, 2012 Yield estimation
More informationGrowth and Instability in Wheat Production: A Region Wise Analysis of Uttar Pradesh, India
International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 6 Number 9 (2017) pp. 2537-2544 Journal homepage: http://www.ijcmas.com Original Research Article https://doi.org/10.20546/ijcmas.2017.609.312
More informationProblem Points Score USE YOUR TIME WISELY SHOW YOUR WORK TO RECEIVE PARTIAL CREDIT
STAT 512 EXAM I STAT 512 Name (7 pts) Problem Points Score 1 40 2 25 3 28 USE YOUR TIME WISELY SHOW YOUR WORK TO RECEIVE PARTIAL CREDIT WRITE LEGIBLY. ANYTHING UNREADABLE WILL NOT BE GRADED GOOD LUCK!!!!
More informationModeling the Safety Effect of Access and Signal Density on. Suburban Arterials: Using Macro Level Analysis Method
Modeling the Safety Effect of Access and Signal Density on Suburban Arterials: Using Macro Level Analysis Method Yuan Jinghui 1,2 and Wang Xuesong 1,2 (1. The Key Laboratory of Road and Traffic Engineering,
More informationCorrecting Sample Bias in Oversampled Logistic Modeling. Building Stable Models from Data with Very Low event Count
Correcting Sample Bias in Oversampled Logistic Modeling Building Stable Models from Data with Very Low event Count ABSTRACT In binary outcome regression models with very few bads or minority events, it
More informationREGIONAL CONVERGENCE IN AGRICULTURE GROWTH IN INDIA: A STATE LEVEL ANALYSIS
REGIONAL CONVERGENCE IN AGRICULTURE GROWTH IN INDIA: A STATE LEVEL ANALYSIS Anju Rani Research Scholar, Dept. of economics, Central University of Haryana Dr. Ranjan Aneja Head, Assistant Professor, Dept.
More informationREGIONAL GROWTH ANALYSIS OF OILSEED PRODUCTION IN UTTAR PRADESH, INDIA
Plant Archives Vol. 18 No. 2, 2018 pp. 1915-1919 e-issn:2581-6063 (online), ISSN:0972-5210 REGIONAL GROWTH ANALYSIS OF OILSEED PRODUCTION IN UTTAR PRADESH, INDIA Pramendra Kumar 1, Sharad Sachan 2 *, H.
More informationBalance Scorecard Application to Predict Business Success with Logistic Regression
12 Journal of Advances in Economics and Finance, Vol. 3, No.1, February 2018 https://dx.doi.org/10.22606/jaef.2018.31002 Balance Scorecard Application to Predict Business Success with Logistic Regression
More informationAppendix A Mixed-Effects Models 1. LONGITUDINAL HIERARCHICAL LINEAR MODELS
Appendix A Mixed-Effects Models 1. LONGITUDINAL HIERARCHICAL LINEAR MODELS Hierarchical Linear Models (HLM) provide a flexible and powerful approach when studying response effects that vary by groups.
More informationModelling Repeat Visitation
European Regional Science Association 40 th European Congress, Barcelona 2000 Modelling Repeat Visitation Jie Zhang AKF (Institute of Local Government Studies) Nyropsgade 37 DK-1602 Copenhagen V Denmark
More informationMidterm Exam. Friday the 29th of October, 2010
Midterm Exam Friday the 29th of October, 2010 Name: General Comments: This exam is closed book. However, you may use two pages, front and back, of notes and formulas. Write your answers on the exam sheets.
More informationASSESSING PROBABILITY DISTRIBUTIONS FROM DATA
ASSESSING PROBABILITY DISTRIBUTIONS FROM DATA INTRODUCTION VICTOR RICHMOND R. JOSE McDonough School of Business, Georgetown University, Washington, D.C. The task of assessing probabilities for uncertain
More informationEarly estimation of the wheat crop yield in Irrigation District 038, Río Mayo, Sonora, México. Palacios-Vélez Enrique Palacios-Sánchez Luis
Early estimation of the wheat crop yield in Irrigation District 038, Río Mayo, Sonora, México Palacios-Vélez Enrique Palacios-Sánchez Luis Study background India wheat In Report No. 28 of the International
More informationTrend and Growth in Agricultural Credit Portfolio of the Jaipur Central Co-operative Bank: A Case Study
International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 6 Number 6 (2017) pp. 3081-3089 Journal homepage: http://www.ijcmas.com Original Research Article https://doi.org/10.20546/ijcmas.2017.606.365
More information