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ThesisItem Open Access Trend analysis of area, production and trade of major agricultural crops in BRICS countries(CCSHAU, Hisar, 2022-07-22) Sowmya, Ravada; JoginderThe present study was carried out with the objectives: firstly, to identify the trends of area, production and trade of wheat, maize and sugarcane in BRICS countries by using various linear and non linear models. Secondly, to evaluate the contribution of BRICS countries to global pool. For this, we have discussed various linear and non-linear models such as quadratic, cubic, logarithmic, logistic, Gompertz and monomolecular models. The data for area, production and trade of selected crops for the period 1961 to 2019 have been collected from FAOSTAT. The parameters of the selected models were estimated using Levenberg - Marquardt‟s iterative method of non-linear regression. Based on various performance measures such as R2 , RMSE and MAE, best models were fitted among the selected models. Based on these performance measures, we found that cubic and logistic models followed by Gompertz model were well fitted for area, production and trade as compared to other models. Also, the contribution of BRICS countries in area, production, imports and exports of wheat is 24, 27, 46 and 12 percent respectively. In case of maize, the BRICS contributed 28, 24, 25 and 24 percent in area, production, imports and exports respectively and in case of sugarcane, the contribution of BRICS countries is 48, 49, 29 and 64 percent in area, production, imports and exports respectively.ThesisItem Open Access A comparative study of forecast models for sugarcane yield prediction of Haryana(CCSHAU, Hisar, 2022-11) Sanjeev; Bhardwaj, NitinCrop yield prediction is one of the most difficult issues in precision agriculture, and numerous models have been proposed. Because agricultural production is affected by a variety of factors such as climate, weather, soil, fertilizer, and seed variety. The most commonly used features in these models are temperature, rainfall, and soil type. Crop yield forecasting plays an important role for decision-makers at the national and regional levels. An accurate crop yield forecast model can help farmers decide what to plant and when to plant. Furthermore, as agricultural trade expanded and transportation infrastructure improved, farmers adopted a more business-like mindset and stopped viewing themselves as subsistence units. The study developed and compared the accuracy of sugarcane yield prediction models such as ARIMA, ARIMAX, ANN, NARX and Hybrid (ARIMA-ANN, ARIMAX-ANN) for the Karnal, Ambala, Kurukshetra, Yamunanagar, Panipat districts and Haryana as whole. The development of various models made use of time series data on sugarcane yields as well as fortnightly weather data on average maximum temperature, average minimum temperature, and accumulated rainfall over the crop period for Karnal, Ambala and Haryana from 1966–1967 to 2014–15, Kurukshetra, Yamunanagar, and Panipat from 1972–1973 to 2014–15. The yield data period from2015-16 to 2019-20 has been used to check the validity of the fitted models for sugarcane yield. The statistical modeling approaches viz., stepwise multiple linear regression, ARIMA, ARIMAX, ANN, NARX and Hybrid (ARIMA-ANN, ARIMAX-ANN) were applied for the study. ARIMAX and NARX models were developed to predict sugarcane yield for selected districts and Haryana using weather variable selected from stepwise multiple linear regression. Finally, forecast performance(s) of the fitted models were observed in terms of percent relative deviation, root mean square error and mean absolute percentage error of sugarcane yield forecasts from observed yield(s). Hybrid (ARIMA-ANN, ARIMAX-ANN) models performed well with lower error metrics as compared to the other fitted models. Five-steps ahead forecast figures i.e. 2015-16 to 2019-20 favored the use of Hybrid models to obtain sugarcane yield forecasts in all selected districts and Haryana under study. Empirical evidence from this study confirms that the Hybrid models can produce reliable forecasts. Therefore, developed forecast models are capable of providing reliable estimates of sugarcane yield well in advance while yield estimates given by state department were obtained quite later.ThesisItem Open Access Volatility forecast models of prices and arrivals of tomato in APMC markets of Haryana(CCSHAU, Hisar, 2023-01) Pushpa; JoginderThe majority of agricultural time series data are nonlinear, nonstationary and leptokurtic in nature. Thus, one of the most difficult areas of time series forecasting is agricultural price forecasting. Accurate forecasting assists both farmers and policymakers in making good decisions. According to the literature, each of the forecasting models has its own set of limitations. In the current study, forecasting performance of SARIMA, GARCH, ANN, Hybrid (SARIMA-GARCH and SARIMA-ANN) and multivariate time series (VAR and VARMA) models has been compared for monthly prices and arrivals of tomato in selected markets of Haryana. The purpose of the study is to give short term forecast of prices and arrivals of tomato with various forecast horizons such as one, three, six, nine and twelve months. Based on empirical results of the study, it is found that ANN models outperformed the others models for all horizon except one month ahead based on performance measures like MAPE and SEP. It is observed that Hybrid (SARIAM-ANN) models do not enhance the forecasting performance. The hybrid (SARIMA-GARCH) model outperforms the individual SARIMA and GARCH models in forecasting the prices and arrivals of tomato. It can be seen that the residuals obtained from linear SARIMA models contain the appropriate ARCH effect. The results of multivariate time series reveal that VARMA model outperforms the VAR model based on minimum values of forecasting performance measures such as MAPE and SEP.ThesisItem Open Access Modeling of tuberculosis through structural equations and bayesian approach(CCSHAU, Hisar, 2023-01) Rohit Kundu; Sheoran, O.P.This study analyzed data on tuberculosis in India to identify latent variables and understand relationships between variables. A structural equation model (SEM) was used, but the initial model did not converge to a satisfactory solution. The model was revised and modified until it converged to an optimal solution with acceptable fit statistics. The Markov Chain Monte Carlo (MCMC) method was also used to identify change points in the number of notified cases of tuberculosis. The results showed an increase in TB cases in the 2000s, followed by two change points after 2010 when the government prioritized controlling the disease. However, the number of cases has continued to increase in recent years. The MCMC method and Gibbs sampler were found to be useful for analyzing epidemiological data with change points. The study also analyzed the prevalence of TB in India using data from the National Family Health Surveys from 2005-2006 and 2015-2016. The results showed that overall, the prevalence of TB did not significantly change between the two surveys. However, the gender gap in TB prevalence (difference in prevalence between males and females) did show a statistically significant decrease, mainly observed in rural areas and found to vary by religion and social group. The rural-urban gap in TB prevalence was most prominent among certain groups, including Muslims, individuals belonging to other religious groups, Scheduled Tribes, and those in the poorest wealth quintile. It is suggested that the decreasing trend in the gender gap may be due to an improvement in the socio-economic status of women and increased detection and reporting of TB cases among women.ThesisItem Open Access A study on impact of climate change and statistical models for pre-harvest forecast of wheat-yield in Haryana(CCSHAU, Hisar, 2023-05) Chetna; Monika DeviThis study aimed to improve the predictability of wheat yield in four districts of Haryana state using advanced statistical techniques. The best models for predicting weather variables were identified, and analyzed the impact of weather variables on crop yield during different growth stages. It was found that weather variables had varying effects on crop yield during different growth stages and across different districts. The observed positive effects of temperature on crop yield during the reproductive stages could be attributed to increased photosynthesis and growth rate of the crop, while the negative effects of temperature during the germination, milking, and harvesting stages could be due to increased plant stress and water loss. The study also found that the negative effects of rainfall on crop yield during certain growth stages could be attributed to waterlogging and soil compaction, while the positive effects of rainfall during certain growth stages could be due to increased soil moisture availability. The study developed models with high R2 values and low error values for predicting wheat yield in all four districts. Pre-harvest forecast models were developed to predict wheat yield before harvest in selected districts of Haryana, using discriminant function analysis and weekly meteorological variables. The models achieved high accuracy in correctly classifying the grouped cases in all districts, with varying effects of predictor variables and autocorrelation. The evaluation of various models for yield forecasting in different districts of Haryana State has yielded impressive results. Principal Component Analysis (PCA) was also utilized to investigate the impact of weather variables on the weather indices in various districts of Haryana State. The models showed a good fit with observed data and high accuracy in predicting yield, with different levels of complexity and performance depending on the district and the model used.ThesisItem Open Access Comparative study of stability measures for rice (Oryza sativa) genotypes(CCS HAU, Hisar, 2023-07) Bisht, Prashant; Vinay KumarThe study aimed to compare existing parametric and non-parametric stability measures for rice genotypes and propose a modified measure based on entropy-based TOPSIS. Experimental data from thirty-six rice genotypes evaluated at two locations over two cropping seasons were analyzed to evaluate genotype-environment interaction. The results revealed strong positive correlations between stability measures such as Wricke's ecovalence and Shukla's stability variance, indicating their similarity in stability ranking. Additionally, significant positive correlations were found between mean yield and specific stability measures, suggesting their effectiveness in selecting genotypes with high yield potential. The proposed modified measure, incorporating entropy weights and four parametric measures, provided a comprehensive assessment of stability. The study emphasized the importance of considering both stability and yield in genotype selection, and the findings contribute to a better understanding of stability analysis in rice cultivation.ThesisItem Open Access An Economic Analysis of Carrot Cultivation in Haryana and Karnataka(CCS HAU HISAR, 2022-08) M S, Manasa; Papang.S, JanailinThe present study was undertaken to know the growth rate, instability and contribution of area and yield on the production of carrot. The study also focussed on the economic analysis of carrot cultivation, resource use efficiency in carrot production and constraints faced by farmers in production and marketing of the carrot crop. The study is based on both primary and secondary data. For collection of primary data, a multistage sampling method was used which includes a sample of 40 farmers cultivating carrot from Haryana and 40 farmers cultivating carrot from Karnataka. The secondary data was collected for a period of 20 years from 2001 to 2020.The growth rate was estimated using compound annual growth rate, instability is measured using CDVI, contribution of area and yield on production is studied using decomposition analysis. The economics of carrot cultivation was calculated using various cost concepts as devised by CACP and B:C Ratio. Resource-use efficiency was measured by employing Cobb-Douglas production function and for constraints analysis Garrett’s ranking technique was employed. Results revealed that the growth rate in area and production carrot in India as well as in Haryana and Karnataka have increased with 7.62, 14.72, 0.81 and 7.57, 4.47, 0.46 per cent per year, respectively while productivity have decreased by -0.24, -0.24 and -0.38 per cent per year, respectively. The instability in area and production of carrot showed a higher degree of instability compared to productivity. The decomposition analysis showed that the area effect and yield effect were found to be responsible for increase in production of carrot in India as well as in Haryana. Whereas, in Karnataka, the yield effect was found to be responsible for increase in production of carrot, while area effect and interaction effect were responsible for decrease in production. In Haryana, the per hectare total cost of cultivation of carrot worked out was ₹219528. Farmers received a net return of ₹185238 with a B:C ratio of 1.84 per hectare. Similarly, the farmers growing carrot in Karnataka obtained a net returns ₹218941 per hectare and total cost of cultivation worked out was ₹358886 per hectare with a B:C ratio of 1.61.The returns to scale from carrot production in Haryana was found to be 1.03 and resource use efficiency of different inputs used in production was revealed as positive and greater than one indicating their under-utilization, except for the irrigation where it found to be positive and less than one indicating its over-utilization. The returns to scale from carrot production in Karnataka was found to be 0.54 and resource-use efficiency of different inputs used in production was revealed as positive and greater than one indicating their under-utilization, except for the input plant protection chemicals and human labour where they found to be positive and less than one indicating their over-utilization. The major constraints faced by farmers were, high cost of labour, scarcity of labour, attack of pest and diseases, high fluctuation in prices and lack of cooperative marketing system in village.ThesisItem Open Access Problems and prospects of flower crops in India(Chaudhary Charan Singh Haryana Agricultural University hisar, 2022-12) Ritu; Bhatia, Jitender KumarThe present study was carried out with the objectives to analyze the trends and growth in area, production and production and productivity of flowers in India, to examine costs involved, returns attained, various marketing channels, value added products from flowers and to identify various constraints in flower cultivation, marketing and export of flower crops in Haryana. The study was based on primary as well as secondary data. The time-series data related to area, production, productivity, export and import of flowers in different zones of India as well as in different zones of Haryana was collected for years 2001-21; the growth rate and trends were computed. The study has been restricted to three crops only i.e. marigold, rose and gladiolus due to availability of reasonable number of flower growers. The study pertains to two districts Sonipat and Gurugram of Haryana. From the selected districts, one block of Sonipat (Rai) and one block of Gurugram (Pataudi) were selected based on highest number of flower cultivators. For marketing data, Delhi flower markets were selected. The outcome of study revealed an increasing trend in the area and production and productivity with CGRs values of 7.86, 8.43 and 3.65 per cent, respectively. Whereas, in Haryana, the trend in area, production of cut flowers and productivity indicated declining trend (-1.04%, -4.64% and -4.54%) over the study period while production of loose flowers illustrated increasing trend with CGRs value of 1.35 per cent. The trends in export indicated declining trend (-2.76%), while import illustrated increasing trend (12.02%). The results of direction of trade of export of flowers from India through Markov value chain resulted that USA was the most reliable country with high probability of retention (0.6217). Per acre total cost of cultivation in French and African marigold worked out was ₹ 65948.48 and ₹ 45495.37, respectively. The corresponding figures for rose were 132874.91for 1st year and ₹ 123884.7 for 2nd year and for gladiolus it was ₹ 318096.63 for 1st year and ₹ 82960.16 for 2nd year. Further, the net returns for French and African marigold were ₹ 177651.52 and ₹ 128504.63, respectively. The corresponding figures for rose were ₹164620.36 for 1st year and ₹ 404866.99 for 2nd year and for gladiolus were ₹170595.87 in 1st year and ₹ 405732.34 in 2nd year. It was found that channel-I was the most efficient among all the marketing channels in disposal of flowers. While considering marketing of value-added products then found that processor’s margin was highest and marketing efficiency was highest among shortest marketing channels for marketing of all floricultural products. Attack of insects-pests, high input prices were major cultivation problems, while transportation cost and high commission charges were major marketing constraints and lack of lack of exporting agencies, coordination among flower growers and exporters and lack of role of FPO’s dealing with flower crops were major export problems faced by farmers in the study area.ThesisItem Open Access Resampling Techniques For Evaluating G × E Interaction In Oilseed Crops(Chaudhary Charan Singh Haryana Agricultural University hisar, 2022-09) Deepankar; Hooda, B. KIn multi-environment trials (METs), a set of genotypes is grown simultaneously in different set of environments. The major objective of METs is identification of genotypes which consistently perform across a wider range of environments. To assess the stability of genotype, in literature there exists various parametric and non-parametric measures. But researcher faces conundrum of choosing appropriate stability measure before moving to main objective of MET. To ease researcher in this dilemma, we developed majority approaches where the results of various parametric and nonparametric stability measure were combined. Under majority approaches, we evaluated i) rank sum of parametric and non-parametric stability measures, ii) modal approach, iii) A new weighted-normalized index and iv) a composite measure using TOPSIS algorithm. A statistical distribution is a mathematical function that describes how the results of an experimental trial are likely to occur at random. The stability measures are a complex function of observed values therefore it is difficult to develop theoretical framework to predict their sampling distribution. Hence bootstrap technique has been used to determine their sampling distributions of stability measures. In METs, for studying GEI, additive main effects and multiplicative interactions (AMMI) and genotype and genotype x environment interaction (GGE) models are frequently used by researchers. In both models after removing the additive effect, singular value decomposition is used to partition genotype x environment interaction into ordered sum of multiplicative terms. Researchers usually retain first two multiplicative terms for biplot analysis without giving much thought in checking the significance of multiplicative terms for retention. The resampling techniques such as bootstrap and cross-validation have been used to test the significance of the multiplicative terms by approximating p value for each multiplicative term. Only those multiplicative terms have been retained in model which are found to be significant i.e., p value < 0.05 or 0.01.
