Indian Farms Research Articles

MSP and Cost of Cultivation of Crops in Relation to Mechanisation of Cultivation of Crops

Agricultural cost is the key to finding the farmers’ cost for a particular crop. India is a nation where a sizable section of the population relies on the agriculture sector, yet it is the only industry that consistently experiences challenges and produces at a rate that is lower than what is anticipated. Indian farms must be mechanised in order to boost input usage effectiveness, decrease human labour-intensive tasks, raise production and productivity of food-grains, lower production costs, and handle difficulties with labour shortages in agriculture and timely farm operations. The use of engineering and technology in agricultural operations to perform a task more effectively and increase production is known as farming mechanization. Mechanization will be used in various stages of the cultivation process where the human intervention will be reduced. Improving crop production involves a combination of factors ranging from selecting the right crop varieties and implementing effective agricultural practices to managing resources efficiently and mitigating risks. Mechanization in the process of cultivation involves the use of various machines and equipment to perform agricultural tasks more efficiently and effectively. Here's how mechanization is applied at different stages of the cultivation process: land preparation, planting, weed control, irrigation, fertilization, crop monitoring, harvesting etc.

Assessment of Economic Efficiency and Its Determents for Mixed Crop Livestock Production under Dryland Agriculture System in the Western Zone of Tamil Nadu, India

In order to accomplish economic, social, and environmental objectives, farm diversification is a significant feature in India’s agricultural systems and rural development. It is crucial to examine factors impacting farm productivity, such as socio, structural, and Circular Economy (CE) factors, in order to ensure the sustainability of varied farms. A decision to follow a farm circularity approach is required to increase agricultural production, return on investment, and achieve sustainability, so the current study was designed to move forward in identifying farm efficiency and their influencing drivers in production systems for the successful execution of circularity in future farms. The objective of this paper is to find the existing operational efficiency of farms, variables that impact a farm’s efficiency, the disparities in farm efficiency, and variables dominating farm efficiency. The efficiency behaviours of Indian farms operating in 2020–2022 were studied and regressed against the factors influencing farm performance. A two-step technique and survey data were employed. To assess variations in the relevance of drivers, an input-oriented Data Envelopment Analysis was employed; in the second stage, efficiency ratings were used as a dependent variable in a Tobit regression analysis. Explanatory variables for enhancing farm performance included social, structural, and Circular Economy (CE) drivers. The age of the farmer, total farm area, and dryland area as socio-structural variables, and reduce, recycle, and redesign as CE variables, have proven to affect the farm’s efficiencies significantly. Managerial implications in terms of technical, allocative, cost efficiency, and their drivers have been drawn from study findings. CE has been confirmed to be the strategy over which the farmer has complete control and has been found to have a more significant impact on farm efficiency. Social structural determents are second in terms of their impact. Farmers in the region have cushy access to inputs; however, they are not utilized to their maximum effect. Therefore, the study indicates that inefficient dryland farmers could increase their production by concentrating on a circular economy strategy.

Estimation of technical efficiency of Indian farms for major crops during 2013–2014 and 2017–2018: a stochastic Frontier production approach

Estimation of technical efficiency of Indian farms for major crops during 2013–2014 and 2017–2018: a stochastic Frontier production approach

Design Development and Evaluation of Mini Tractor Operated Trencher

The mechanization of Indian farms is imperative to enhance input use efficiency, reduce human drudgery, cost of production and to address issues of labour scarcity and timeliness of farm operations. Digging of trenches for laying pvc pipes in sprinkler and drip irrigation system has become drudgery by human labour, more expensive and time consuming. Commercially available machines are high capacity, more cost of operation and not affordable to the small and marginal farmers. To overcome this problems, a small tractor operated trencher was designed and developed. The developed trencher was evaluated in the field at a 1.5,2,2.5 km/h forward speeds. During field trails it was observed increase in forward speed from 1.5 to 2.5 km/h resulted in decrease in depth of trench, fuel consumption and capacity of auger. Increased in forward speed resulted in increase in length of trench.

Economic Analysis of Dryland Integrated Production System in Western Agroclimatic Zone of Tamil Nadu, India: A DEA Approach

Background: Efficiency of production system is calculated by the input spent to amount of output produced. The Agronomic efficiency has been found to be below 48% than the world efficiency standard of 40 kg ha-1. The average fertilizer usage of India is 133 kg ha-1, 232% higher than the global standard fertilizer of 40 kg ha-1. The certified seeds and agriculture machinery usage has been increased by 15% and 13% in India but the efficiency of farm stays behind. Methods: With this back ground the present study applied cost approach variable return to scale Data Envelopment Analysis (DEA) model to evaluate the Indian farms resource using 200 rural farms of Tamil Nadu state. The data envelopment analysis models have the advantage of simultaneous measure of technical, allocative and cost efficiency of the individual farms. Result: The cost efficiency among the respondents ranged from 0 to 1 with a mean efficiency of 0.66. The study found that Decision-Making Units (DMU) have cost inefficiency, suggesting that most of the DMU operated very far away from the efficiency frontier. Allocative inefficiency (0.55) is worse than the technical inefficiency (0.80), implying that the lower economic efficiency is the result of high allocative inefficiency.

Application of Renewable Energy in Indian agriculture

Energy plays a key role in agricultural production, post-production, rural domestic and livestock raising sectors, both directly as different forms of energy and fuel inputs for various purposes like operation of machinery, equipment, lighting, etc., and indirectly, for seed, fertilizers and chemicals production used in rural activities. India needs a secure, affordable and sustainable energy system to power effective economic growth well supported with renewable energy sources. Engineering interventions for effective (functionally, energetically and economically) systems is utmost needed for rural India. There is need for a revolution in mechanized agriculture, so that new energy efficient systems and machines can be recommended and introduced for small and marginal farmers. There is need to enhance the power availability and optimize the energy input to the rural sector to obtain the better income to agro-rural producers, traders and industrialists. Energy interventions are needed to use the locally available energy sources curtailing the use of fossil energies. The major targets in Indian perspective are the use of available and developed renewable and conventional energy sources and gadgets in rural society and agro-industry using all kinds of available biomass resources including solar electricity, heating and pumping at decentralised mode. We need to employ recent advanced technologies like plasma technology, nano-technology, IoT, artificial intelligence and robotics for effective generation of energy and valued products from rural local renewable resources. Research on solar energy use for production agriculture is challenging due to fluctuating need of torque depending on the agricultural field conditions. The use of batteries for storing and releasing power is another concern for long term use of solar photovoltaic (SPV) gadgets. Bio-CNG has emerged as an option for ex-situ management of crop residue. Thermo-chemical and bio-chemical conversion based electrical power routes are available and there is a need to promote these with better incentives. Energy efficient functionally improved mechanical systems to be introduced in the Indian farms need to be evolved.

Effect of inoculum spraying on rice (Oryza sativa) residue decomposition kinetics

Rice (Oryza sativa L.) residues on Indian farms have remained a major challenge due to its voluminous and unmanageable quantity and short window for sowing successive crops. A study was carried out at research farm of the ICAR-Indian Agricultural Research Institute, New Delhi during 2019–21, to develop a microbial inoculum spraying system for efficient decomposition of rice residues. The study involved the evaluation of flood nozzles at different operational parameters like operating pressure (1.5, 2.5 and 3.5 kg/cm2), nozzle heights (50, 60 and 70 cm) and forward speeds (2.5 and 3 km/h). The inoculum spray was characterized in terms of Volume Median Diameter (VMD), Number Median Diameter (NMD) and Droplet Density (DD). The decomposition kinetics was studied in terms of total organic carbon, total nitrogen, phosphorus, potassium and N-acetyl glucosamine observed at an interval of 10 days and 20 days after inoculums application. VMD and NMD were found in the range of 347–243 μm and 77.67–87.8 μm respectively, whereas droplet density ranging from 252.5–403.9 droplets/cm2 to spray microbial inoculum using flood nozzle. The C:N ratio of rice residue was reduced by 19.96% and 36.77% respectively after 10 and 20 days of rice residue decomposition compared to control. Carbon content reduced from 47.98–41.24% and total nitrogen content increased from 0.532–0.728 % after 20 days of decomposition. The N-acetyl glucosamine content of rice residue increased from 0.77–3.53 mg/g after 20 days indicating that target-oriented microbial inoculum spraying accelerates the decomposition kinetics of rice residues.

Neither Corporate, Nor Family: The Indian “Patronal” Farm

After the disappearance of socialist State farms and cooperatives, the diversity of farms in the world seemed to have been reduced to a simple dichotomy: family farms on the one hand and corporate farming on the other. The former category, the dominant model on the planet, includes undertakings where labor is provided by the family, while corporate farming that was long limited to South America, is exclusively based on hired labor. This reading grid, however, turns out to be particularly problematic when looking at the Indian case. Despite their small size, a considerable number of Indian farms make use of a combination of family and hired labor. Based on an analysis of national statistics and fieldwork in 13 small regions, this article characterizes agricultural work and how family and hired labor function together on Indian farms. It shows that alongside family farms where wage labor (either hiring or being hired) serves to ensure full employment for family labor, there is another type of farm, which we define as “patronal farm”, where hiring agricultural laborers increases the income earned by family labor. In our surveys, this is systematically the case for irrigated agriculture, where wages paid to laborers are lower than the agricultural labor productivity per workday. After describing the characteristics of this original model, the article discusses its coherence with India's political economy and questions its sustainability.

Gender and mechanization: Evidence from Indian agriculture

AbstractTechnological change in production processes with gendered division of labor across tasks, such as agriculture, can have a differential impact on women's and men's labor. Using exogenous variation in the extent of loamy soil, which is more amenable to deep tillage than clayey soil and therefore more likely to see adoption of tractor‐driven equipment for primary tilling, we show that mechanization led to significantly greater decline in women's than men's labor on Indian farms during 1999–2011. Reduced demand for labor in weeding, a task often undertaken by women, explains our findings. The estimates suggest that a 10% increase in mechanized tilling led to a 5% fall in women's farm labor use, with no accompanying increase in their non‐farm sector employment. Our results highlight the gendered impact of technological change in contexts where there is task based gender division of labor with limited opportunities for women to diversify their workforce participation.

Are There Too Many Farms in the World? Labor Market Transaction Costs, Machine Capacities, and Optimal Farm Size

We show that labor market transaction costs explain why the smallest farms are more efficient than slightly larger farms in most low-income countries and that increases in machine capacity with operational scale result in the globally observed rising upper tail of productivity. We find evidence consistent with these mechanisms using Indian data, and we show that if all Indian farms were at the minimum scale required to maximize the return on land, the number of farms would be reduced by 82% and income per farm worker would rise by 68%.

Delineating virulence of Vibrio campbellii: a predominant luminescent bacterial pathogen in Indian shrimp hatcheries

Luminescent vibriosis is a major bacterial disease in shrimp hatcheries and causes up to 100% mortality in larval stages of penaeid shrimps. We investigated the virulence factors and genetic identity of 29 luminescent Vibrio isolates from Indian shrimp hatcheries and farms, which were earlier presumed as Vibrio harveyi. Haemolysin gene-based species-specific multiplex PCR and phylogenetic analysis of rpoD and toxR identified all the isolates as V. campbellii. The gene-specific PCR revealed the presence of virulence markers involved in quorum sensing (luxM, luxS, cqsA), motility (flaA, lafA), toxin (hly, chiA, serine protease, metalloprotease), and virulence regulators (toxR, luxR) in all the isolates. The deduced amino acid sequence analysis of virulence regulator ToxR suggested four variants, namely A123Q150 (AQ; 18.9%), P123Q150 (PQ; 54.1%), A123P150 (AP; 21.6%), and P123P150 (PP; 5.4% isolates) based on amino acid at 123rd (proline or alanine) and 150th (glutamine or proline) positions. A significantly higher level of the quorum-sensing signal, autoinducer-2 (AI-2, p = 2.2e−12), and significantly reduced protease activity (p = 1.6e−07) were recorded in AP variant, whereas an inverse trend was noticed in the Q150 variants AQ and PQ. The pathogenicity study in Penaeus (Litopenaeus) vannamei juveniles revealed that all the isolates of AQ were highly pathogenic with Cox proportional hazard ratio 15.1 to 32.4 compared to P150 variants; PP (5.4 to 6.3) or AP (7.3 to 14). The correlation matrix suggested that protease, a metalloprotease, was positively correlated with pathogenicity (p > 0.05) and negatively correlated (p < 0.05) with AI-2 and AI-1. The syntenic organization of toxS-toxR-htpG operon in V. campbellii was found to be similar to pathogenic V. cholerae suggesting a similar regulatory role. The present study emphasizes that V. campbellii is a predominant pathogen in Indian shrimp hatcheries, and ToxR plays a significant role as a virulence regulator in the quorum sensing—protease pathway. Further, the study suggests that the presence of glutamine at 150th position (Q150) in ToxR is crucial for the pathogenicity of V. campbellii.

An ergonomic intervention for manual load carrying on Indian farms

The farm inputs like seeds, fertilizers and produce are handled manually in most of the low-income and underdeveloped countries. Such practice of manual load carrying is one of the dominant contributors to back pain and associated physiological problems.In the present study, it was found that volume, quantum and distance determine the mode of load carrying. Bulky or voluminous commodities like harvested cereal crops and fodder are carried on the head. Heavy loads of paddy and vegetables filled in gunny bags, which limits the volume to bag size are carried on the back. Carrying the load on the head is by and large prevailing mode because it does not introduce eccentricity and postures remain balanced., In the present study, an attempt is made to develop a harness, which does not alter the head loading but prevents the loading of the spine. Three approaches considered were: Approach-I (harness H1): load passing through shoulders only (one path only); Approach II (harness H2): load passing through head and shoulder (through two paths only); Approach III (harness H3): Load passing through head and shoulder (through two paths), but in this approach, load on the cervical spine was limited to 10 kg and rest of the load was transferred to shoulder with proper stability. The outcome of ergonomic studies showed that Approach-III is the most metaboliclly economical, compared to other developed approaches and could be adopted for Indian agricultural farm load carriage for various purposes.

Enhancing integration of Indigenous agricultural knowledge into USDA Natural Resources Conservation Service cost-share initiatives

Agricultural management practices drawn from Indigenous agricultural knowledge (IAK) have supported people in the North American desert Southwest for thousands of years. Techniques developed and refined from generation to generation through careful observation and innovation have enhanced the sustainability and resilience of these delicate agroecosystems over millennia. USDA Natural Resources Conservation Service (NRCS) recognized the contributions of IAK practices to Environmental Quality Incentives (EQIP) and the Conservation Stewardship Programs (CSP) in the 2010 <i>Indigenous Stewardship Methods and NRCS Conservation Practices</i> (ISM) handbook. However, during fiscal year 2017 2% of EQIP and CSP contracts went to American Indian farms, which make up 2.9% of the total farms in the United States. NRCS would need to award nearly 400 more contracts to Indigenous farms to achieve proportional representation. This suggests significant potential exists for expanding American Indian participation in these conservation programs but barriers to their participation remain. For example, agriculturalists who wish to employ IAK management practices must go through an ad hoc process defined in the 2010 ISM handbook. This adds further complexity to the application process, in which applicants must navigate unique land tenure/ownership issues and tribal/federal interactions. Here we present examples of Indigenous conservation practices embedded in agricultural systems of Hopi dryland farmers, the La Courte Oreilles Band of Lake Superior Chippewa wild rice (<i>Zizania palustris</i>) harvesters, and Menominee tribal foresters to demonstrate the compatibility of IAK practices with NRCS conservation outcomes and to argue for full inclusion of Indigenous agricultural practices into something equivalent to the NRCS Field Office Technical Guides. Expansion of Indigenous agriculturalists and producers in NRCS programs can help preserve important ecosystems and help support Indigenous cultures and time-tested concepts of stewardship. Incorporation and support of IAK practices is beneficial to all stakeholders because expansion of partnerships between the NRCS and Indigenous agriculturalists and producers will help expand Indigenous conservation and agriculture practices and further the NRCS mission of “Helping People Help the Land.”

Drought stress amelioration in plants using green synthesised iron oxide nanoparticles

Abstract With rising air pollution and global warming, the threat of impending drought in agricultural areas is a frightful scenario. Mitigation of such types of drought stress in Indian context is all the more important as Climate Change induced drought is poised to affect Indian farms in the future. The alleviation of abiotic stress in plants by employing iron oxide nanoparticles (FeNp) is a novel approach, not much reported. Hence, in the present study we undertook green synthesis of Iron oxide nanoparticles/magnetite (Fe3O4-Np) from a marine algae Chaetomorpha antennina (green algae). Henceforth, two types of Iron oxide nanoparticles were synthesized, characterized and employed further – bare FeNp and citrate coated FeNp. The biogenic iron oxide nanoparticles have been employed as a nano-fertilizer. However its active mechanism in the amelioration of drought stress is unknown. Henceforth, we wanted to establish the role of FeNp under drought stressed conditions and by coating it further with citrate we observed an enhanced stress amelioration effect. Drought stressed Setaria italica plants were treated with green synthesised iron oxide nanoparticles, both bare as well as capped. These FeNp not only serve as a nanonutrient for the plant, but also enabled the plant to overcome drought stress. An overall increase in the plant (Setaria italica) growth was detected. It was also observed that with increasing concentrations of FeNp (Fe3O4), the seedlings showed a concomitant increase in chlorophyll as well as soluble sugar content, suggesting that the iron up taken by the plants were used up for producing photoassimilates. The iron, H2O2 as well as proline content in the plants was also estimated, which further confirmed that the plants readily uptook FeNp and overcame the drought stress. Thus we could conclude from our experiments that, FeNp (both capped as well as bare FeNp) are effective in conferring the plants, ability to ameliorate drought stress. Throughout the experiment no toxic effect was observed in the plants. This confirms the potential of green synthesized FeNp, as an eco-friendly fertilizer even under drought stressed conditions.

A hybrid model of generalized regression neural network and radial basis function neural network for wind power forecasting in Indian wind farms

Wind power generation is a major part of renewable energy but it suffers from uncertainty and variable nature of wind speed. In conquering the uncertainty, forecasting of wind power generation emerges as best solution. Accordingly, wind power forecasting assists the power grid to increase the grid reliability. In this paper, a generalized regression neural network (GRNN), a neural network of radial basis function (RBFN) and a hybrid of GRNN and RBFN are applied for estimation of wind power and their performance is compared in respect to short-term wind power forecasting. In comparison to RBFN, GRNN has simple and static architecture. Historical wind power and meteorological wind speed data of the year 2014 from Indian wind farms are employed for training and testing the neural networks. The research work carried in this article interprets that GRNN has consistently performed better than RBFN. The hybrid GRNN-RBFN has also depicted good accuracy in a week ahead wind power forecasting. In such cases, either GRNN or RBFN predicts with high errors the hybrid GRNN-RBFN is helpful in accurate wind power forecasting. The errors are calculated in terms of MAPE & RMSE. For GRNN approach MAPE ranges from 0.48 % to 10.53 % and RMSE ranges from 0.01 KW to 3.31 KW. Whereas the maximum MAPE is 25.6 % for RBFN and the maximum RMSE is much higher i.e 11.61KW. In fact, for any forecasting approach, reliability is a major concern. The work carried also includes reliability analysis of all three forecasting models proposed. To ensure the best performance of GRNN, confidence intervals of MAPE are computed for all three models implemented. Among all, GRNN is well perceived to be the best one with narrowest confidence intervals.

Gendering Technological Change: Evidence from Agricultural Mechanization

Technological change in production processes with gendered division of labor across tasks, such as agriculture, can have a differential impact on women's and men's labor. Using exogenous variation in the extent of loamy soil, which is more amenable to deep tillage than clayey soil and therefore more likely to see adoption of tractor driven equipment for primary tilling, we show that mechanization has led to significantly greater decline in women's than men's labor on Indian farms. Reduced demand for labor in weeding, a task that requires precision and is thus more often undertaken by women, explains our findings. The estimates suggest that increased mechanized tilling led to a more than 22% fall in women's agricultural labor in India during 1999-2011. Our results highlight the gendered impact of technological change in contexts where there is sex-specific specialization of labor.

A Lateral Stability Monitor for Two Wheeled Tractor - Trailer System

The tractor and two wheeled trailer combination being the most popular load carrying vehicle of the Indian farms, is often susceptible to serious accidents due to lateral roll over. A simple PIC based lateral stability monitor was developed from basic principles for the tractor trailer combo. The system uses a commercial tilt sensor to detect the roll angle, a potentio-metric sensor to sense the turning radius and a hall effect sensor to measure the speed of travel. The control code calculates the lateral stability ratio and compares it to the stability limits. The code cautions the operator visually and audibly to take evasive action well before instability occurs. The monitor was tested in the field under various sloping terrains, turning speeds and payloads, and was found to function satisfactorily.

Development of solar powered knapsack sprayer

The small and marginal farmers in India are 83% with land holding of 46.1% and contribution of 51.2% in the production. On Indian farms, knapsack sprayers are very commonly used by small and marginal farmers for pest control because of affordability and ease of operation but with lower outputs. An attempt was made to develop a solar powered sprayer which had higher output (0.3 ha/hr) with lower physiological energy consumption and discomfort. An electronic control had been embedded for protection against deep discharge and over charging of battery for longer operational life. The system could be fully charged by solar energy within two hours of irradiation and can be operated continuously for six hours.This ensures quality spray with uniform droplet size in the swath. Anti-clogging filter had also been installed before the nozzle in nozzle head for trouble free operation as well as longer service life of nozzle.

Biomechanical model for energy consumption in manual load carrying on Indian farms

This study pertains to manually carrying load in Indian farms. Different modes are adopted for carrying farm inputs and farm produce; head, shoulder and back. A biomechanical model was developed and validated to predict metabolic energy consumption for carrying load manually by varying modes, loads and ground inclinations. The model developed incorporated operator, ground inclination and load parameters. Operator parameters included human efficiency, body weight and height of the worker. Load parameters considered were weight of load and mode of load carrying. Experiments on three modes (head, back and shoulder) and three loads (10, 15, 20 kg load) at three slopes (0, 5, 10%) were conducted in a laboratory set up. Twelve farm workers (six males and six females) working in local farms participated in the study. The model closely predicted energy and rest requirement for load carrying in different modes.

Adaptive and dynamic decision-making processes: A conceptual model of production systems on Indian farms

Farming systems are complex structures with several dimensions interacting in a dynamic and continuous manner around farmers' management strategies. This complexity peaks in semi-arid regions of India, where small farms encounter a highly competitive environment for markets and resources, especially unreliable access to water from rainfall and irrigation. To represent such strategies, we propose the conceptual model NAMASTE, which was conceived and based on data collected in the Berambadi watershed in southern India. The most relevant and novel aspects of NAMASTE are i) the system-based representation of farm production systems, ii) the description of dynamic processes through management flexibility and adaptation, and iii) the representation of steps in farmers' decision-making processes at various temporal and spatial scales. Since NAMASTE was designed in an extreme case of highly vulnerable agriculture, its generic framework and formalisms can be used to conceptually represent many other farm production systems.