Impact of Optimal Cropping Patterns on Incomes in a Punjab District

1976 ◽  
Vol 15 (2) ◽  
pp. 218-221
Author(s):  
M. Arshad Chaudhry
Keyword(s):  
Developing Countries ◽  
Linear Programming ◽  
Short Note ◽  
Cropping Pattern ◽  
Small Farms ◽  
Cropping Patterns ◽  
Punjab Province ◽  
Optimal Cropping

To improve farm incomes in developing countries, the foremost question that the farmer must address himself to is: what cropping pattern best uses the fixed resources in order to get the highest returns? During the last decade, the agricultural economists have shown great interest in applying the tools of linear programming to individual farms. Most of the studies conducted elsewhere have shown that, under existing cropping pattern, farm resources were not being utilized optimally on the small farms.[l, 4]. We conducted a survey in the canal-irrigated areas of the Punjab province of Pakistan1 to investigate into the same problem. This short note aims at identifying the opti¬mal cropping pattern and to estimate the increase in farm incomes as a result of a switch towards it on the sampled farms.

Optimal crop planning using a chance constrained linear programming model

Water Policy ◽  
2011 ◽  
Vol 13 (5) ◽  
pp. 734-749 ◽  
Author(s):  
V. Jothiprakash ◽  
R. Arunkumar ◽  
A. Ashok Rajan
Keyword(s):  
Linear Programming ◽  
Probability Distribution ◽  
Programming Model ◽  
Linear Programming Model ◽  
Cropping Pattern ◽  
Net Benefit ◽  
Cropping Patterns ◽  
Time Period ◽  
Irrigation Intensity ◽  
Optimal Cropping

A monthly time-stepped chance constrained linear programming (CCLP) model was developed to derive optimal cropping patterns and optimal operational strategies for the Sri Ram Sagar Project, with stochastic inflows. The stochastic nature of the inflows was incorporated into the model in its equivalent deterministic form. These equivalent deterministic inflow values were estimated from the annual and monthly probability distribution of observed inflows, and named the chance constrained linear programming model-annual and chance constrained linear programming model-monthly, respectively. The models were solved for nine different dependable inflow levels, namely for 50, 55, 60, 65, 70, 75, 80, 85 and 90% in each CCLP. The results of the models were compared with respect to net benefit, irrigation intensity, total cropped area, optimal cropping pattern, optimal releases, evaporation loss and initial storages. Based on the results obtained, it can be concluded that, in CCLP optimization, the probability distribution of ‘model time period’ (t-month in this case) should be considered rather than the probability of ‘planning time period’ (year in this case).

scholarly journals Self-adaptive multi-population-based Jaya algorithm to optimize the cropping pattern under a constraint environment

2019 ◽  
Vol 22 (2) ◽  
pp. 368-384
Author(s):  
Vijendra Kumar ◽  
S. M. Yadav
Keyword(s):  
Population Based ◽  
Cropping Pattern ◽  
Jaya Algorithm ◽  
Net Benefit ◽  
Invasive Weed ◽  
Cropping Patterns ◽  
Net Benefits ◽  
Optimal Cropping ◽  
Teaching Learning ◽  
Self Adaptive

Abstract Increasing population around the world, especially in India and China, has resulted in a drastic increase in water intake in both domestic and agricultural sectors. This, therefore, requires that water resources be planned and controlled wisely and effectively. With this consideration, the aim of the study is to achieve an optimal cropping pattern under a constrained environment. The objective is to maximize the net benefits with an optimum use of water. For optimization, a self-adaptive multi-population Jaya algorithm (SAMP-JA) has been used. For the Karjan reservoir in Gujarat State, India, two different models, i.e. maximum and average cropping patterns, were formulated based on the 75 per cent dependable inflow criteria. These two model scenarios are developed in such a way that either model can be selected by the farmer based on the crop area and its respective net benefits. Invasive weed optimization (IWO), particle swarm optimization (PSO), differential evolution (DE) and the firefly algorithm (FA) were compared to the results. The results show that the SAMP-JA obtained the maximum net benefit for both the models. The findings of the research are also compared with the actual cropping pattern. A significant increase has been noted in the cultivation of sugarcane, groundnut, wheat, millet, banana and castor. SAMP-JA has been noted to converge faster and outperforms PSO, DE, IWO, FA, teaching–learning-based optimization (TLBO), the Jaya algorithm (JA), elitist-JA and elitist-TLBO.

scholarly journals PLANO ÓTIMO DE CULTIVO NO PROJETO DE IRRIGAÇÃO MORADA NOVA, CEARÁ, UTILIZANDO MODELO DE PROGRAMAÇÃO LINEAR

Irriga ◽  
2000 ◽  
Vol 5 (3) ◽  
pp. 167-187
Author(s):  
José Aurélio Lucena Rodrigues ◽  
Raimundo Nonato Távora Costa ◽  
José Antônio Frizzone ◽  
José Vanglésio de Aguiar
Keyword(s):  
Linear Programming ◽  
Water Supply ◽  
Programming Model ◽  
Linear Programming Model ◽  
Water Volume ◽  
Land Resource ◽  
Cropping Pattern ◽  
Irrigation Project ◽  
Optimal Cropping Pattern ◽  
Optimal Cropping

PLANO ÓTIMO DE CULTIVO NO PROJETO DE IRRIGAÇÃO  MORADA NOVA, CEARÁ, UTILIZANDO MODELO DE PROGRAMAÇÃO LINEAR  José Aurélio Lucena RodriguesDepartamento Nacional de Obras Contra as Secas – Av. Duque de Caxias.CEP 60000-000 – Fortaleza-CERaimundo Nonato Távora CostaUniversidade Federal do Ceará – Departamento de Engenharia Agrícola. Campus do Pici. Bloco 804.CEP 60455-760 – Fortaleza-CEJosé Antônio FrizzoneEscola Superior de Agricultura Luiz de Queiroz – Departamento de Engenharia Rural,  Av. Pádua Dias, 11 – Caixa Postal 11. 13418-900 – Piracicaba-SPJosé Vanglésio de AguiarUniversidade Federal do Ceará – Departamento de Engenharia Agrícola. Campus do Pici. Bloco 804.CEP 60455-760 – Fortaleza-CE  1 RESUMO O objetivo do trabalho foi desenvolver um modelo de programação linear para quantificar as variáveis do processo de produção, que otimizem a operação do Projeto de Irrigação Morada Nova (PIMN). O modelo procura estabelecer um plano ótimo de cultivo, objetivando a maximização da sua receita líquida anual. Na análise do modelo foram incorporadas as restrições de volume de água mensal, volume de água anual, terra, mercado. Com base nas culturas estudadas,  nas restrições de área cultivada, nos preços e nos custos de produção, os resultados permitiram as seguintes conclusões: 1) o modelo de programação linear recomendou os cultivos de 1050 ha de arroz semeado em fevereiro, 1050 ha de arroz semeado em agosto, 750 ha de feijão semeado em julho, 130 ha de milho (espiga) semeado em janeiro, 155 ha de banana e 112 ha de coco para um volume de água utilizado de 30.285.5460 m3;  2) modelo de otimização desenvolvido projetou uma receita líquida 19,06 % maior que a obtida com o  plano de cultivo do PIMN e um volume anual utilizado inferior em 47,3 %, considerando o ano agrícola de 1997; 3) a ocupação da terra foi baixa, com percentuais médios anuais de 41,4% e 40,3% respectivamente, para o modelo proposto e o plano de cultivo do PIMN; 4) a análise de sensibilidade do recurso terra apresentou preço sombra zero, indicando que esse recurso não foi restritivo; 5) mantendo-se o volume mensal disponível em 7.516.400 m3 e  9.730.700 m3 respectivamente, para os períodos de janeiro a junho e julho a dezembro, volumes anuais superiores a 30.285.560 m3 não contribuíram para o  aumento da  receita líquida do PIMN. UNITERMOS: Programação linear, padrão de cultivo, irrigação.  RODRIGUES, J. A .L., COSTA, R. N. T., FRIZZONE, J. A., AGUIAR, J. V. OPTIMAL CROPPING PATTERN IN THE “MORADA NOVA” IRRIGATION PROJECT USING LINEAR PROGRAMMING MODEL 2 ABSTRACT The main objective of this work was to develop a linear programming model, in order to quantify the process variables which optimize the irrigation project operation. The model establishes optimal cropping pattern in the irrigation project “Morada Nova” (MNIP), aiming to maximize the net annual income. Restrictions to the model were monthly water supply, anual water supply, land and market system. Based on the water-yield considered, cultivated land restrictions, production cost and product prices, the following conclusions were reached: 1) the model rresulted a optimal cropping pattern comprising 1050 ha  of  rice cultivated in February, 1050 ha of rice cultivated in August, 750  ha of beans (vigna) cultivated in July, 130 ha of corn (cob) cultivated in January, 155 ha of banana and 112 ha of cocunut, for a total annual utilized water of 30.285.560 m3; 2) the optimization model presented, estimated a net income of 19,06 % higher than  cropping pattern used in the MNIP, using an  annual water volume 47,3 % lower,  considering the agricultural year of 1997; 3)  the land occupation was low with annual average percentages of 41,4% e 40,3% respectively, to the presented model and the cropping pattern used in the MNIP; 4)  the sensibility analysis to the land resource revealed dual price zero, indicating that this recource was not restrictive; 5) maintaining the total monthly availability of 7.516.400 m3 and 9.730.700 m3 respectively, in the periods from January until June and from July  until December respectively, annual volumes higher than 30.285.560 m3, did not increase the  return of the MNIP. KEYWORDS: Linear programming, cropping pattern, irrigation.

scholarly journals Studi Optimasi Pola Tanam Daerah Irigasi Gong Gang Kecamatan Parang Kabupaten Magetan

2016 ◽  
Vol 14 (1) ◽  
pp. 51
Author(s):  
Ernawan Setyono ◽  
Safik Mucharom
Keyword(s):  
Linear Programming ◽  
Spatial Patterns ◽  
Food Production ◽  
Cropping Pattern ◽  
Water Requirements ◽  
Cropping Intensity ◽  
Cropping Patterns ◽  
Optimization Study ◽  
Planting Season

Along with the increasing population growth, the need for food also increased. To meet that need for optimization studies of the factors that influence spatial patterns of planting in order to increase the volume of food production. Determination of the cropping pattern that will be used after the first known dependable flow and water requirements. Through the design cropping pattern is expected cropping intensity can be enhanced and existing water sources can be used optimally. linear programming used in this optimization study using QM for Windows 4 software. The most optimal results from the optimization that has been done is an alternative was began on November  cropping patterns : rice-palawija-sugarcane season crops beginning 1st week of November, profits amounted to Rp 106.729.700.000 to the area that can be cultivated for the planting season I: Rice = 1990 ha, palawija = 307 ha sugarcane = 89 ha, planting season II: Rice = 1990 ha, palawija = 307 ha sugarcane = 89 ha, and planting season III:  Rice = 258,2753 ha Palawija = 2038,725 ha, sugarcane = 89 ha

scholarly journals Optimal Land And Water Allocation Model For The Maximization of Net Agricultural Return In Drought Prone Regions

2021 ◽  
Author(s):  
Mulu Sewinet Kerebih ◽  
Ashok Kumar Keshari
Keyword(s):  
Water Resources ◽  
Rainfall Variability ◽  
Resources Allocation ◽  
Command Area ◽  
Cropping Pattern ◽  
Water Resources Allocation ◽  
Allocation Model ◽  
Cropping Patterns ◽  
The Government ◽  
Optimal Cropping

Abstract In this study, the land and water resources allocation model was developed to determine optimal cropping patterns and water resources allocations at different rainfall probability exceedance levels (PEs) to ensure maximum agricultural return in the Hormat-Golina valley irrigation command area, Ethiopia. To account the uncertainty of rainfall variability, the monthly dependable rainfall was estimated at three levels of reliability (20, 50 and 80% PEs) which are representing wet, normal and dry seasons based on regional experience. The irrigation water demand which was used as an input to the optimization model was estimated at each level of reliability by using CROPWAT model. The net annual returns of optimal cropping patterns were estimated as 181, 179 and 175 million Ethiopia Birr at 20 %, 50 % and 80 % PEs, respectively. The result of the optimal cropping pattern indicates that, the net annual return of the command area was increased to 45.75%, 45.84% and 47.01% than the Government targeted at 20%, 50% and 80% PEs, respectively. The findings reveal that the optimal land and water resources allocation model is very useful to the planners and decision makers to maximize the agricultural return particularly in areas where land and water resources are limited.

scholarly journals Use of Linear Programming Model to Determine the Optimum Cropping Pattern for an Irrigation Scheme in Masvingo, Zimbabwe

2013 ◽  
Vol 1 (4) ◽  
pp. 450-452
Author(s):  
Majeke F ◽  
Mubvuma S M T ◽  
J. Chirima, K. Makaza ◽  
T. Hungwe R. Gwazan ◽  
Nyoni ◽  
...  
Keyword(s):  
Linear Programming ◽  
Optimization Problems ◽  
Programming Model ◽  
Optimal Solution ◽  
Linear Programming Model ◽  
No Production ◽  
Cropping Pattern ◽  
Irrigation Scheme ◽  
Irrigation Planning ◽  
Optimal Cropping

Agricultural systems are often faced by challenges such as crop selection and irrigation planning which can be formulated as optimization problems. Decisions have to be made on the proper set of crops to be cultivated and a proper irrigation scheme. The objectives of such decisions are to maximize net profit or to minimize water waste. In this study, a linear programming model was developed that helped to determine the optimal cropping pattern for an irrigation scheme in Masvingo, Zimbabwe. Crops which considered were wheat, sugar beans for winter and cotton and maize for summer for the 2012/13 agricultural season. The linear programming model was solved by using Microsoft Excel (2007). The model recommended no production of wheat and cotton. Sugar beans and maize gained acreage by 50 percent and 88 percent respectively. On the whole, the optimal cropped acreage did not change as compared to the existing cropping plan. As a result of the optimal solution, a farmer‘s income could be increased by $1,668.60. The optimal income increased from existing level of $1,919.40 to $3,588.00 showing an improvement of 87 percent. The results show that LP models solutions are worthy implementing.

scholarly journals Optimization of irrigation cropping pattern by using linear programming: Case study on irrigation area of Parsanga, Madura Island, Indonesia

2018 ◽  
Vol 39 (1) ◽  
pp. 51-60 ◽  
Author(s):  
Pitojo T. Juwono ◽  
Lily Montarcih Limantara ◽  
Fathor Rosiadi
Keyword(s):  
Linear Programming ◽  
Water Discharge ◽  
Agricultural Product ◽  
Cropping Pattern ◽  
Optimization Analysis ◽  
Cropping Patterns ◽  
Irrigation Area ◽  
Maximum Benefit ◽  
Production Benefit

AbstractThe irrigation area of Parsanga is located in Sumenep Regency, Madura Island of Indonesia. This irrigation area is 500 ha and the existing cropping pattern is paddy–paddy–second crop. There is water discharge deficiency due to the existing cropping pattern mainly in the dry season. Thus, this study intends to optimize the cropping pattern for 3 condition so that it can produce the maximum benefit of agricultural product. The first cropping pattern is paddy/second crop–second crop–paddy/second crop; the second proposition is paddy/second crop –paddy/second crop–second crop; and the third proposition is paddy–second crop–paddy/second crop. The optimization analysis is carried out by using the linear programming. The suggested three cropping patterns are not only able to solve the water deficiency; they can also present the more production benefit than the existing condition.

scholarly journals Multi Crop Optimization Using Linear Programming Model for Maximum Net Benefit

2018 ◽  
Vol 7 (3.12) ◽  
pp. 797
Author(s):  
Shreedhar R
Keyword(s):  
Linear Programming ◽  
Water Resources ◽  
Water Availability ◽  
Programming Model ◽  
Optimization Techniques ◽  
Cropping Pattern ◽  
Economic Returns ◽  
Net Benefit ◽  
Use Of Resources ◽  
Optimal Cropping

The water used for agriculture is 70% globally. This has resulted in new methods of saving water. Hence water saving techniques has to be practiced.  In water resources planning and management, optimization techniques is used for limited use of resources such as such as water, land, production cost, manpower, fertilizers, seeds, and pesticides. For cultivating each crop, the land area needs to be planned properly. Hence the crop pattern has to be decided optimally depending on available water resources and on economic basis. Therefore farmer needs to be educated to adopt optimum cropping pattern which maximises the economic returns. Hence the study is taken up to optimize the allocation of land areas to crops. The objective function for multi crop model were formulated using linear programming for maximizing the net benefits. The study resulted in optimal cropping pattern for different water availabilities ranging from 2000 Ha-m to 5500 Ha-m. The maximum net benefit for the study area varied from Rs. 53.2 Crores for 2000 Ha-m water availability to Rs.78 Crores at 5000 Ha-m water availability.  

scholarly journals Economic analysis to optimize food plant patterns in Paloh Sub-district, Sambas District

2021 ◽  
Vol 306 ◽  
pp. 02049
Author(s):  
Juliana C. Kilmanun ◽  
Rusli Burhansyah ◽  
Riki Warman
Keyword(s):  
Linear Programming ◽  
Analytical Method ◽  
Mung Bean ◽  
Rainy Season ◽  
Dry Season ◽  
Food Crop ◽  
Cropping Patterns ◽  
Crop Farming ◽  
Optimal Cropping ◽  
Farm Inputs

The potential of land in The Paloh sub-district for the development of rice-mung beans is quite large. The rice and mung bean cropping patterns have been cultivated by farmers. The problems faced by farmers are the use of fertilizers that are not optimal, the use of superior seeds is still low. This study aims to (1) study the use of farm inputs, costs, and income, (2) analyze the optimal cropping patterns in food crop farming in The Paloh Sub-District. Sambas District. The analytical method used is farm analysis and optimization of cropping patterns using linear programming. The results showed that the rainy season rice cropping patterns and the dry season rice cropping patterns resulted in an income of IDR 87,071,580 per year. Based on the optimization results, it was found that the rainy season rice was 0.61 ha and dry season rice was 0.88 ha.

scholarly journals Using Fuzzy Time Series (FTS) and Linear Programming for Production Planning and Planting Pattern Scheduling Red Onion

2019 ◽  
Vol 125 ◽  
pp. 23007 ◽  
Author(s):  
Aries Dwi Indriyanti ◽  
Dedy Rahman Prehanto ◽  
Ginanjar Setyo Permadi ◽  
Chamdan Mashuri ◽  
Tanhella Zein Vitadiar
Keyword(s):  
Time Series ◽  
Linear Programming ◽  
Production Planning ◽  
Fuzzy Time Series ◽  
Planning System ◽  
Cropping Pattern ◽  
Market Demand ◽  
Time Data ◽  
Cropping Patterns ◽  
Data Production

This study discusses the production planning system and scheduling shallots planting patterns using fuzzy time series and linear programming methods. In this study fuzzy time series to predict the number of requests and the results of predictions from fuzzy time series methods become one of the variables in the calculation of linear programming. Using supporting variables, demand data, production data, employment data, land area data, production profit data, data on the number of seedlings and planting time data are indicators used in processing the system. The system provides recommendations for cropping patterns and the number of seeds that must be planted in one period. The age of harvesting onions is ± 3-4 months from the planting process, the number of planting seeds is adjusted to the number of requests that have been predicted by using fuzzy time series and cropping pattern calculation process is carried out using linear programming. The results of this system are recommendations for farmers to plant seedlings, planting schedules, and harvest schedules to meet market demand.

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