Determination of the optimal quantity of crop residues for energy in sugarcane crop management using linear programming in variety selection and planting strategy

Sartori, Maria Márcia Pereira; Florentino, Helenice de Oliveira; Basta, Cesar; Leão, Alcides Lopes

doi:10.1016/s0360-5442(01)00052-4

Cited by 29 publications

(12 citation statements)

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“…The varieties should display desirable features such as high yield, high sugar content, capacity to reshoot, no tendency to fall, and resistance to pests and diseases. The moment one chooses one variety to be planted, one must note its features and adaptation to the environment; otherwise, the productive and quality potentials may be compromised [29].…”

Section: Selection Of the Sugarcane Varietiesmentioning

confidence: 99%

“…Optimized biomass allows for improved economic results and helps to implant the residue in the mill's energy production system. According to Sartori et al [29], in an attempt to minimize the environmental impact and the influences affecting productivity, and hence the sugar-ethanol mill's profitability, researchers have persisted in choosing the sugarcane variety that produces stalks with a higher calorific value and a low harvesting cost without losing its yield features. Only in this manner will it be feasible to utilize this residue for energy co-generation.…”

Section: Utilization Of Sugarcane Residual Biomassmentioning

confidence: 99%

“…Florentino and Sartori [13] linked the two problems proposed by Sartori et al [29] with a BLP model to support variety selection and planting quantity of sugarcane in order to reduce crop residue, maximize energy generated by this residue, and satisfy the demand of the mill. They solved the conflict between these objectives by using nonzero-sum game theory.…”

Section: Problemmentioning

confidence: 99%

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Production and Management of Sugarcane Biomass — Process Optimization

Florentino

Pato²,

Jones³

et al. 2015

Biomass Production and Uses

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Section: Selection Of the Sugarcane Varietiesmentioning

confidence: 99%

Section: Utilization Of Sugarcane Residual Biomassmentioning

confidence: 99%

Section: Problemmentioning

confidence: 99%

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Production and Management of Sugarcane Biomass — Process Optimization

Florentino

Pato²,

Jones³

et al. 2015

Biomass Production and Uses

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“…Agronomic data were taken from the literature (Ripoli and Ripoli, 2004;Torrezan, 2003;Sartori et al, 2001) and from an agricultural study by Lima (2009) to implement the model. They included data from 10 varieties (SP701284, SP706163, SP701143, SP711416, RB835486, RB72454, RB855536, SP791011, RB855113, RB711406) and 16 plots as per Tables 1-3. The results were obtained using the e-constraint method with different e values, which was implemented by utilizing the MATLAB software (The Mathworks Inc.).…”

Section: Computational Implementation Of the Modelmentioning

confidence: 99%

Multiobjective 0-1 integer programming for the use of sugarcane residual biomass in energy cogeneration

Florentino

Lima

Carvalho

et al. 2011

International Transactions in Operational Research

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It is well known that Brazil is the largest producer of sugarcane in the world. Nevertheless, a great concern exists about the crop system used, because the most common practice is manual harvesting with prior straw burning. The Brazilian authorities have approved a law prohibiting the burning of sugarcane crop residue before harvesting. However, mechanized harvesting creates the new problem of having to deal with the residue. Many studies have indeed proposed the use of this residue as an energy source. A major difficulty in using this residue is how to economically transport sugarcane harvest biomass from a farm to a processing centre. Besides transport costs, another concern is knowing whether the energy generated by the straw offsets the energy used, in terms of fuel, in the process. This study proposes a multiobjective integer linear programming optimization model to choose sugarcane varieties so as to minimize costs in the use of crop residue and simultaneously maximize the energy balance in such a process. Computational results are presented and discussed.

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“…Observa-se em SARTORI et al (2001) que a escolha de variedades para o plantio da cultura de cana-deaçúcar pode ser auxiliada por modelos matemáticos de otimização que minimizam a quantidade de resíduo de colheita ou maximizam a energia contida nesses resíduos. Além do potencial energético dessa biomassa, contam a favor dessa energia as questões ambientais, a manutenção de empregos e a projeção de vida limitada para os recursos energéticos de fontes naturais (EID et al, 1998).…”

Section: Introductionunclassified

Modelos de minimização de biomassa residual

Sartori

Florentino

2002

Bragantia

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RESUMONo Brasil, a biomassa residual do cultivo de cana-de-açúcar é representada por folhas, palhas, ponteiros e frações de colmo que somam uma produção aproximada de 108 milhões de toneladas por ano; quantidade que permitiria a produção de 10,2 MWh de energia. Existem muitas cultivares como opção de plantio resultantes de programas de melhoramento visando à resistência a pragas, a doenças e à adaptação ao tipo de solo, cuja escolha é feita em virtude da produtividade física, bem como da produção de sacarose. Essa seleção pode ser auxiliada por modelos de otimização, visando minimizar a quantidade de resíduo de colheita, com ou sem imposições sobre a quantidade de energia obtida da biomassa. Pode, também, ser auxiliada pela maximização da quantidade de energia da biomassa residual com imposições sobre a quantidade de resíduo a ser gerada. A decisão sobre qual modelo deve ser usado é determinada pelo administrador da empresa com auxílio de alguns critérios. O objetivo deste trabalho é apresentar três modelos e o lucro alcançado com o uso da energia gerada por essa biomassa. Os resultados indicaram o modelo III, que prevê a maximização da geração de energia pela biomassa na escolha de cultivares, considerando a área disponível para o plantio, a produção de sacarose e a produção de biomassa em quatro anos de cultivo. O lucro obtido com o uso desse modelo foi calculado em 939 US$/ha.ano. Palavras-chave: resíduo de colheita, otimização, cana-de-açúcar. ABSTRACT MODELS OF MINIMIZATION OF RESIDUAL BIOMASSIn Brazil, the residual biomass of the sugarcane cultivation is represented by leaves, straw, tips and stalk fractions that together represent a production of about 108 million tons per year. Such amount could allow the production of 10.2 MWh of energy. There are many sugarcane cultivars resulting from improvement programs seeking resistance to pests, diseases and adaptation to the soil type. Their choice is made in function of the physical productivity as well as the sucrose production. That selection can be aided by optimization models, seeking to minimize the amount of crop residue with or without impositions about the amount of obtained energy from the biomass. It can also be aided by the maximization of the amount of energy of the residual biomass with impositions on the amount of residue to be generated. The decision on which model should be used is determined by the company administrator. Such decision can be made with aid of some approaches. The objective of this work is to present the profit in the use of the energy generated by that biomass as a decision criteria in the choice of the models. The results indicated the model III, that foresees the maximization of energy generation from the biomass with choice of cultivars taking into account the available area for the plantation, the sucrose production and the biomass production in four years of cultivation. The profit with the use of that model was calculated as being 939 US$/ha.year.

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Determination of the optimal quantity of crop residues for energy in sugarcane crop management using linear programming in variety selection and planting strategy

Cited by 29 publications

References 1 publication

Production and Management of Sugarcane Biomass — Process Optimization

Production and Management of Sugarcane Biomass — Process Optimization

Multiobjective 0-1 integer programming for the use of sugarcane residual biomass in energy cogeneration

Modelos de minimização de biomassa residual

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