Yield Of Food Grains Research Articles

Dynamics of Foodgrains Production and Decomposition of Output Components of Foodgrains in Bihar

"Bihar stands in seventh place in foodgrain production in the country. It produced 15.38 million tonnes in 2020-21 from an area of 6.36 million hectares. Production of cereals was 15 million tonnes, from which rice accounts for 6.74 million tonnes and maize accounts for 2.08 million tonnes of production, but pulses contribute only 0.38 million tonnes. This paper calculated the growth rate, instability index, and decomposition analysis of the area, production, and yield of food grains in Bihar. The study period was from 1991-92 to 2020-21. It was divided into three decades. The area under foodgrains was showing a negative growth rate every decade. Production showed an increasing growth rate in the first and third decades, but in the second decade, it showed a negative growth rate. The yield of foodgrains showed a positive growth rate every decade, which was the main source of production growth. Cereals followed a similar trend as food grains, but the scenario was somewhat different for pulses. Pulse area and production showed a negative growth rate every decade, but its yield showed a positive growth rate in the first two decades and a negative growth rate in the last decade. In cereals, the rice area showed a negative growth rate in all the decades, but production and yield showed a positive growth rate in the first and third decades and a negative growth rate in the second decade. The area under maize showed a negative growth rate in every decade except in the second decade, where it was found a positive growth rate. Production of maize showed a positive growth rate in all the decades though its yield also had a positive growth rate in the first and third decades and a negative growth rate in the second decade. The highest instability in the area of foodgrains was observed in the first decade, but production and yield of foodgrains showed the highest instability in the second decade. Yield effects of crops were contributing more than area effect in increasing foodgrains production. Net cropped area and gross cropped area in Bihar had decreased. Due to more intensive cultivation, the cropping intensity in Bihar has increased from 138% in 2001-02 to 143% in 2018-19. More effective production methods are used, fallow land is used for the production of pulses, short-duration varieties may be encouraged, and focused efforts from various line departments be made in order to ensure that Bihar is both food and nutritionally secure."

Multi-Objective Optimization with Artificial Neural Network Based Robust Paddy Yield Prediction Model

Agriculture plays a vital role in the food production process that occupies nearly one-third of the total surface of the earth. Rice is propagated from the seeds of paddy and it is a stable food almost used by fifty percent of the total world population. The extensive growth of the human population alarms us to ensure food security and the country should take proper food steps to improve the yield of food grains. This paper concentrates on improving the yield of paddy by predicting the factors that influence the growth of paddy with the help of Evolutionary Computation Techniques. Most of the researchers used to relay on historical records of meteorological parameters to predict the yield of paddy. There is a lack in analyzing the day to day impact of meteorological parameters such as direction of wind, relative humidity, Instant Wind Speed in paddy cultivation. The real time meteorological data collected and analysis the impact of weather parameters from the day of paddy sowing to till the last day of paddy harvesting with regular time series. A Robust Optimized Artificial Neural Network (ROANN) Algorithm with Genetic Algorithm (GA) and Multi Objective Particle Swarm Optimization Algorithm (MOPSO) proposed to predict the factors that to be concentrated by farmers to improve the paddy yield in cultivation. A real time paddy data collected from farmers of Tamilnadu and the meteorological parameters were matched with the cropping pattern of the farmers to construct the database. The input parameters were optimized either by using GA or MOPSO optimization algorithms to reconstruct the database. Reconstructed database optimized by using Artificial Neural Network Back Propagation Algorithm. The reason for improving the growth of paddy was identified using the output of the Neural Network. Performance metrics such as Accuracy, Error Rate etc were used to measure the performance of the proposed algorithm. Comparative analysis made between ANN with GA and ANN with MOPSO to identify the recommendations for improving the paddy yield.

Addressing the effect of meteorological factors and agricultural subsidy on agricultural productivity in India: a roadmap toward environmental sustainability.

In the last two decades, the extensive literature that has measured agricultural productivity and growth rate remains controversial and provides few strategies about its main determinants. The present study aims to find out the key determinants of food grain yield (FGY) and examine the role of climate change and agricultural subsidy (SUB) in the context of India using annually data spanning from 1991 to 2018. The current study applied the ARDL modelling to investigate the impacts of climatic factors (average rainfall (RF), mean temperature (AT), and carbon emission (CO2) and agricultural subsidy (SUB) on food grain yield (FGY) in the short-and long-term in India. The estimated outcomes indicate that climatic factors such as RF have a positive impact while AT and CO2 have a negative effect on FGY. Similarly, non-climate variables such as gross capital formation (GCF) and fertilizer usage (FERT) positively contributed to FGY, while the area under crop (LUC), SUB, and employment (AL) negatively affected FGY in India. The results from Granger causality divulge that climatic and non-climatic elements are the main determinants of food grain yield, which have been playing play a significant role in enhancing food grain production and ensuring food security in India. Based on empirical outcomes and findings, some key policy implications emerged. Precisely, government and policy developers should focus on technological innovation and precision agriculture to increase agriculture production and productivity. Government should create funds to curb the climate change problem and promote eco-friendly renewable energy.

Projected Food-grain Production and Yield in India: An Evidence from Statewise Panel Data Investigation during 1977-2014

Purpose : This study examines the impact of climatic change on food-grain production and yield using state-wise panel data during 1977-2014 in fifteen Indian states. Accordingly, it estimates the projected food-grain production and yield by the years of 2040, 2040, 2060, 2080 and 2100. Finally, it provides the effective practical and effective policy suggestions to reduce the climate change impact on food-grain farming based on existing studies. Research Method : Regression coefficients of food-grain production and yield with climatic and non-climatic factors are estimated using Cobb-Douglas production function model. Marginal impact analysis method is used to examine the projected food-grain production and yield. Findings : Empirical results infer that most climatic factors have a negative impact on food-grain production and yield in different weather seasons. Projected results are suggested that food-grain production is expected to be declined by 5.25%, 6.64%, 8.03% and 9.57% by 2040, 2060, 2080 and 2100 respectively. Food-grain yield is likely to be decreased by 1.05%, 1.96%, 2.87% and 5.07% by the aforesaid years. Research Limitations : This study could not capture impact of inter-states disparities in socio-economic condition of farmers, geographical conditions, agriculture policies and public spending on agriculture and rural development on food-grain production and yield. It also could not include factors such as solar radiation, sun intensity, wind speed and heat wave in empirical investigation. Originality/ Value : It compiles state-wise panel of food-grain production and yield as dependent variables, and climatic variables and non-climatic factors as explanatory variables during 1977-2014. It examines the projected food-grain production and yield.

Growth and Instability Analysis of India’s Food Grain Sector in the Post Liberalisation Period

Background: Having a population growing at an annual average rate of 1.2 per cent and more than half of its total size depend on primary sector for their livelihood, agricultural sector occupy significant role in the economy of India. The extent of area, production and productivity of food grains and their instability therefore attracts special attention. The present study thus analyses the performance of agricultural sector in India in terms of trend in growth and instability of area, production and productivity of food grain during the three decades of liberalisation. The specific objectives are (i) to examine the growth rate and instability in area, production and yield of food grains in India and (ii) to explain the decomposing changes in the variability of food grains production in India. Methods: In this field-laboratory investigation during 1990-91 to 2018-19, official secondary data has been utilized. Statistical tools like Least Square Growth Rate, Coefficient of Variation of area, production, and yield etc. have been applied for analysis. Result: The study highlighted that area under food grain cultivation remained almost stagnant. However, the overall food grain production registered growth rate of 2 per cent while the production instability was 15.88 per cent. The trend lines fitted to the production of foodgrains shows positive growth rate. The co-efficient of determination (R2) shows 87 percent for production and 92 percent for productivity which determines scope for further production for India. But in area it shows just 3.9 per cent. The result of the study shows that the production of food grains has increased with due instability during given the time period. It also calls for adopting alternate production technologies which will further improve the productivity of food grains to meet increasing demand from the growing population.

An Empirical Analysis on India’s Food Grain Cultivation, Production and Yield in Pre & Post Globalisation

Globalization is, directly and indirectly, contributing to its effect in all sectors of an economy. The agricultural sector is not exempted from the effect of change due to globalization as a component of the primary sector and a prime sector for human survival needs. The status of self-sufficient in the production of food grain will lead a nation to make a walk of pride among the other member globally. India is an agro-economy. In other words, agriculture is the backbone of the Indian economy. So the production of food grain and its cultivation and yield should be normally high to meet out the demand of a growing population. Also, with the implementation of a policy of globalization, there might be some change in cultivation, production, and yield of food grains in India. In this paper, an attempt was made to examine/ identify the change in area under cultivation, yield, and production by using the secondary sources of data from 1970 to 2017. The selected breakeven point of time was 1991-1992. The annual growth rate pictured the change in a particular point of time; the linear and quadratic model gave the growth over the period selected for the study, and dummy used regression model presented the difference in structural change. AGR results dominated by the negative growth rate; the linear growth model for production depicts that 3.6 percentage of tons of production will be move when a year moves upward. The area under cultivation is deteriorating in AGR, and other models used gave a weakness in explanatory level concerning time for the area under cultivation of food grain. Regarding the obtained results for yield reflect that a positive change exists after globalization, even though a reduction in area under cultivation.

Using Artificial Neural Networks (ANNs) to Improve Agricultural Knowledge Management System (KMS)

Agriculture is an important sector of the Indian economy. In the present paper an attempt has been made to theoretically explore the development of an agricultural knowledge management system (KMS) in respect of various micro irrigation techniques for agriculture, as well as relevant crop-/region-specific agricultural practices in different regions of the country, as the same has been observed to be very much necessary for the overall benefits of wider cross section of farmers, agricultural scientists, economists, and other stakeholders in the domain. It is further observed that artificial neural networks (ANNs), which are a part of soft computing techniques, can be used as a KMS tool for effective management of various sub sectors of agriculture. In this context, it has been shown that use of ANNs as a KMS tool can improve the effectiveness of applications of the above mentioned agricultural KMS by accurately forecasting the year-wise estimated yield of food grains of India with the help of past data of various relevant parameters.

Trend and Instability in Area, Production and Productivity of Food Grains in Haryana Vis-A-Vis India

The Presented study is an attempt to examine the trend and instability in area, production and productivity of food grain crops in Haryana and India during period 1966-67 to 2012-13 and five sub periods i.e. P-I (1966-67 to 1975-76), P-II (1976-77 to 1985-86), P-III (1986-87 to 1995-96), P-IV (1996-97 to 2005-06) and P-V (2006-07 to 2012-13). The study is based on secondary data. The study reveals positive trends in area, production and yield of food grains for both Haryana and India. Production in Haryana and India increased mainly due to increase in yield. Similar results have been obtained on triennium bases. In Haryana, area, production and yield have shown positive growth rates in all the periods and the overall period except for area in Period-III, IV and V. In the case of India positive growth rates has obtained for production and yield of food grains while area has shown negative trend in Periods III, IV, V and entire period under study. The coefficient of variation (C.V.) in respect of the three components i.e. area, production and productivity of total food grains found to be higher in Haryana as compared to India in all the periods and the overall period except for yield in period-III, yield and production in period-IV and yield in Period-V. Similar results have been obtained for the instability indices.

Impact of agribusiness on food security and livelihood generation: A case study in Assam, India

Assam is predominantly a rural phenomenon, stemming principally from underperformance of the agriculture sector and lack of alternative employment avenues mainly in the rural areas. Decadal growth rate of population of Assam reflected a per square increase trend of population in the state. With increase population people below poverty line started increasing and average size of holding started to decrease. Area, Production and average yield of food grains in Assam found stagnant for a long period as a result per day per capita availability of most of the food grains found decreasing for the state. The study revealed that Assam has deficit in fish and livestock products as per nutritional demand. But has potentiality in horticultural crops. So to maintain the food security and livelihood to the people of Assam transition of agribusiness is very much required which will include cultivation of high yielding crop varieties, mechanization of agriculture, development of contact farming, establishment of food processing industry and development of cooperative fish and livestock farming in the state.

Cropping, Production and Yield Pattern of selected Crops in Solapur District of Maharashtra State, India

The main purpose of this research paper is to examine the cropping, production and yield pattern of selected crop in the Solapur district. This Research paper is based on secondary data and Relevant statistical data were collected from various government source. Among the food grain Jawar crop occupied highest area followed by wheat crop. In case of non-food grain crops the position of total oil seed crops showed that of the total gross cropped area 3.54 percent area was brought under these crops. According to output pattern in the study are of the total cereals, output of Jawar was commanding and next came maize. In the Solapur yields of Groundnut (1639.66 kg) maize (1281 kg), wheat (1181.67 kg) and Jawar (1065.33 kg) found in study area. Among the food grain crops, maize has occupied first rank in the District Per hector and then come the Wheat. Moreover, it was observed that during study, rice, Bajara, Jawar and wheat have shown negative change. While remaining all the crops have showed the positive change in the District. The yield of food grains crops increased by 17.13, where the growth in yield of cereals was 17.73 percent.

Sources of Growth and Instability in Agricultural Production in Western Odisha, India

This paper analyzes the nature and sources of agricultural instability in the Bolangir district of Western Odisha, India. The nature of instability in agricultural production is examined by determining the agricultural instability index (AII) of variables such as area, production and yield of food grains and paddy, irrigation coverage, and annual rainfall. The period covered by the study (1984–2009), which is characterized by greater technology dissemination, is categorized into two sub- periods: (1984–1993) and (1994–2009). The effects of a change in major inputs on the variability of crop productivity are assessed using a double-log model. The yield decomposition analysis is used to examine the role of drought risk factors and the amount and productivity of inputs in crop yield growth. The extent of instability in agricultural production and productivity in the region is found to be quite high on account of the high level of rainfall variability and the low irrigation coverage. The level of instability in food grain production is much larger during the second sub-period. The decomposition analysis reveals that about 84.4 percent of the total change in paddy yield growth is due to drought risk factors such as rainfall failure, rainfall variability, high temperature, and drought-induced pest attack, while the remaining change in paddy yield is due to the change in amount and productivity of major agricultural inputs such as labor, fertilizer, pesticides, and irrigation.

Impact of monsoon rainfall on the total foodgrain yield over India

The study focuses on understanding the variations of precipitation during summer monsoon season and its impact on Kharif and Rabi foodgrain yield over India. Total foodgrain yield over India during Kharif (summer) season is directly affected by variations in the summer monsoon precipitation (June–September). An increase (decrease) in rainfall is generally associated with an increase (decrease) in foodgrain yield. A similar correspondence during the Rabi (winter) foodgrain yield is not evident. The Rabi crop is not directly affected by variations in the post-monsoon precipitation (October–December) alone, also the summer season precipitation influences the Rabi crop through water and soil moisture availability over many parts of India. Though the reduction of rainfall activity during the entire summer monsoon season leads to reduction in crop yields, the occurrence of prolonged rainfall breaks also causes adverse effect on the crop growth resulting in reduced crop yields.

Kharif foodgrain yield and daily summer monsoon precipitation over India

AbstractFoodgrain yield over India during kharif (summer) season is directly affected by day to day variations in summer monsoon precipitation (June through September). An increase (decrease) in foodgrain yield is generally associated with an increase (decrease) in rainfall. However, the reduction of rainfall or occurrence of heavy rainfall activity may cause adverse effect on the crop growth. This study is therefore aimed at understanding the impact of all possible values of daily precipitation from lowest to highest rainfall during summer monsoon on kharif foodgrain yield over India for the period 1966‐2003. The study also includes an impact of intense rainfall events (1 and 5 days maximum precipitation) on foodgrain yield. Analysis covers frequency of rainy days based on all fixed thresholds (1 mm and above) at the interval of 1 mm as well as percentile thresholds (1st percentile to 99th percentile) at the interval of 1 percentile. The study reveals that the kharif foodgrain yield increases with increase in all‐India summer monsoon precipitation and rainy days. Strong positive relationship (statistically significant at 1% level) is observed for lower range of threshold values from 1 to 50 mm (1st percentile to 90th percentile), and the magnitudes of correlation decreases with increase in threshold values. The negative impact of the heavy rainfall activity is more pronounced over the heavy rainfall regions of northeast India. It is found that the prolonged occurrence of intense rainfall activity increases their impact on the foodgrain yield. Normal (moderate) range of precipitation indices is seen to be associated with both positive and negative anomalies of foodgrain yield, which point towards the influence of other climatic factors in determining the better yield of kharif foodgrain. Copyright © 2012 Royal Meteorological Society

Statistical analysis of the relationship between summer monsoon precipitation extremes and foodgrain yield over India

AbstractThe Indian economy largely depends on agriculture which is highly influenced by the spatio‐temporal variability of precipitation. Kharif and rabi are the two main crop‐growing seasons which require major proportion of rainfall. Increase in heavy precipitation events, however, can have adverse effects on the crops. This study, therefore, is mainly focused on understanding the variation of extremes in precipitation during summer monsoon season and its impact on kharif foodgrain yield over India. For this, several objectively defined indices of observed precipitation extremes, in terms of frequencies and intensities, have been computed for the period 1951–2003 using daily gridded data of 1° latitude × 1° longitude resolution. Efforts have also been made to prepare the climatology of extremes in precipitation (1961–1990) to determine their basic characteristics over the Indian region.Correlation analysis reveals that a large part of the country exhibits positive relationship between kharif foodgrain yield and the indices of extreme precipitation, significant at 5% level. Correlations with the indices of frequencies defined as seasonal count of days when rainfall exceeds 85th, 75th, and 65th percentiles (and 30, 20, and 10 mm) show that spatial extent and strength of the positive relationship decreases with increase in threshold values. This indicates that very heavy daily rainfall is less useful than the moderate daily rainfall. Strong negative relationship between the yield and indices of extreme precipitation observed over heavy precipitation areas of northeastern parts of the country indicate that very heavy daily rainfall have an adverse effect on crop. The study also points out that increase in heavy rainfall activities during July are favourable for the yield, but correlations become weak and statistically insignificant during the month of August. Individual crops show similar results as that obtained from aggregate kharif foodgrain, however, magnitude of the correlations varies from crop to crop. Copyright © 2011 Royal Meteorological Society

Environmental impacts of increasing the world's food production

World demand for food is expanding more rapidly than ever before in history to rising population and increasing affluence. The urgency of increasing food production should not be underestimated. It is vitally important, however, to ensure that the strategies adopted to increase food production on short-term basis can be sustained and effectively integrated with long-term policies. With many of our present policies, there is a very real danger that in our efforts to increase food production in the short-run on a crisis basis, we may adopt strategies which are self-defeating in the long-run. Any strategy to increase food production on a sustained basis that does not explicitly consider environmental factors is doomed to failure, sooner or later. Strategies developed must work with nature and not against it. Within this philosophical framework, the major parameters that could improve yield of food grains and could possibly deteriorate the very ecological base on which food production depends, and thus ultimately jeopardize the production process itself, are discussed. Among the parameters reviewed are food loss and wastage during production, storage and distribution; environmental constraints in relation to the use of pesticides and fertilizers; problems arising due to improper land use planning and irrigation practices; effects of climatic changes on food production; and problems of technology transfer and use.

Crossing the"Yangtze River" in A Year Of Severe Drought

Upon entering Luan-ch'eng hsien in Hopei, the first thing that catches one's eye from the walls of large and small villages are the big character posters saying,"One who cannot reach the Great Wall is no hero; we vow to turn Luan-ch'eng into a fertile land like that south of Yangtze." This is the call to battle of the people of Luan-ch'eng to learn from Tachai and catch up with Hsi-yang. In 1972 Luan-ch'eng hsien suffered from a very severe drought. The Luan-ch'eng hsien CCP committee led the people of the whole hsien to turn this slogan into a reality through self-reliance and arduous struggle. On the basis of big-margin increases in successive years, the yield of food grains crossed the"Yangtze." The average per-mou yield increased from 701 catties in 1971 to 902 catties. Total yield increased from 210 million-odd catties of the previous year to 270 million-odd catties. Good harvests were reaped from 130,000 mou of cotton. And substantial development in forestry, livestock, and sideline production was achieved.

GREEN REVOLUTION IN INDIA∗

The introduction of hybrid seeds in India has doubled the yield of foodgrains. The High Yielding Variety Seed Program (H.V.P.) has contributed to serious interregional disparities in agriculture. Surplus production of foodgrains is not the true measure of success of the Green Revolution; many areas in India remain unaffected by this program, and are still vulnerable to famines.