Development of a decision-making application for optimum soybean and maize fertilization strategies in Mato Grosso

2022 ◽  
Vol 193 ◽  
pp. 106659
Author(s):  
José L. Rotundo ◽  
Rafael Rech ◽  
Marcelo Moraes Cardoso ◽  
Yinan Fang ◽  
Tom Tang ◽  
...  
Keyword(s):  
Decision Making ◽  
Mato Grosso ◽  
Maize Fertilization

Containing destruction from Brazil's Amazon highways: now is the time to give weight to the environment in decision-making

2006 ◽  
Vol 33 (3) ◽  
pp. 181-183 ◽  
Author(s):  
PHILIP F. FEARNSIDE
Keyword(s):  
Decision Making ◽  
Federal Government ◽  
Cost Savings ◽  
The State ◽  
Future Plan ◽  
Mato Grosso ◽  
Soybean Production ◽  
The Road ◽  
Economic Argument

The BR-163 Highway (Fig. 1) was originally built by the Brazilian Army in 1973 and 1974. It has remained passable since, although poor road conditions in the unpaved portion (the 646-km portion in the state of Pará from the border with Mato Grosso to Trairão) impede use of the road as a significant export route. Reconstructing the highway has been a (so-far unimplemented) part of an evolving series of plans for massive expansion of infrastructure: Brasil em Ação (Brazil in Action) for 1996–1999, Avança Brasil (Forward Brazil) for 2000–2003, and the Pluriannual Plan for 2004–2007 (Laurance et al. 2001; Fearnside 2002). Soybean plantations in the northern part of the state of Mato Grosso have been rapidly expanding, partly in anticipation of the BR-163 being reconstructed and paved (Fearnside 2001). The governor of Mato Grosso since 2003 is Brazil's largest soybean entrepreneur and a major force in inducing the federal government to pave the road. With the construction of the BR-163, northern Mato Grosso would be linked to the ports of Miritituba and Santarém (Fig. 1), halving the current distance for transportation, as currently soybeans from northern Mato Grosso are exported through the port of Paranaguá in the state of Paraná. A future plan would take the soybeans by rail from Cuiabá to Santos. Cost savings for soybean export of US$ 11.6 per tonne relative to the rail route through Santos (Alencar et al. 2005) provide an economic argument for the BR-163 project. Soybean production in northern Mato Grosso was 3.61 million tonnes in 2004 (Alencar et al. 2005), worth approximately US$ 813 million. Nevertheless, even with substantial monetary benefits for the BR-163, the various forms of impact from the project must be quantified and compared to the benefits before a decision is made (Fearnside 2005).

scholarly journals ON-FARM TRADE-OFFS FOR OPTIMAL AGRICULTURAL PRACTICES IN MATO GROSSO, BRAZIL

2017 ◽  
Vol 15 (3) ◽  
Author(s):  
Marcelo Carauta ◽  
Affonso Amaral Dalla Libera ◽  
Anna Hampf ◽  
Rafael Felice Fan Chen ◽  
José Maria Ferreira Jardim Silveira ◽  
...  
Keyword(s):  
Decision Making ◽  
Simulation Experiment ◽  
Crop Yields ◽  
Agricultural Practices ◽  
Economic Behavior ◽  
Decision Making Process ◽  
Mato Grosso ◽  
Double Cropping ◽  
Trade Offs ◽  
Decision Variables

To keep yield advances, farmers in Mato Grosso (MT) have been adopting several technological innovations. Therefore, agricultural production systems in MT have become complex and dynamic since farmers have to consider the increase of decision variables when planning and implementing their farming practices. These variables are widely spread across many distinct topics, bringing them together and summarizing information from diverse fields of research has become a difficult task in farmers’ decision-making process. Therefore, we performed an Integrated Assessment simulation experiment with a region-specific bio-economic component to assess trade-offs between different agricultural practices in a double cropping system. The simulation experiment was carried out with MPMAS, a multi-agent software package developed for simulating farm-based economic behavior and human-environment interactions in agriculture. Crop yields were simulated with the Model of Nitrogen and Carbon dynamics in Agro-ecosystems (MONICA). Our simulation results show a trade-off between lower soybean yields with the flexibility of double cropping when soybean with shorter maturity cycle is introduced. Results also captured regional differences in terms of land use share of different crops and farm configurations of double cropping. These results provide key insights into a farmer’s decision-making process depending on a multitude of decision variables.

scholarly journals Advance of soy commodity in the southern Amazonia with deforestation via PRODES and ImazonGeo: a moratorium-based approach

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Thais Lourençoni ◽  
Carlos Antonio da Silva Junior ◽  
Mendelson Lima ◽  
Paulo Eduardo Teodoro ◽  
Tatiane Deoti Pelissari ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Decision Making ◽  
Kernel Density ◽  
Cloud Platform ◽  
Mato Grosso ◽  
Monitoring Programs ◽  
Data Variability ◽  
Southern Amazonia ◽  
Remote Sensing Techniques ◽  
Crop Enhancement

AbstractThe guidance on decision-making regarding deforestation in Amazonia has been efficient as a result of monitoring programs using remote sensing techniques. Thus, the objective of this study was to identify the expansion of soybean farming in disagreement with the Soy Moratorium (SoyM) in the Amazonia biome of Mato Grosso from 2008 to 2019. Deforestation data provided by two Amazonia monitoring programs were used: PRODES (Program for Calculating Deforestation in Amazonia) and ImazonGeo (Geoinformation Program on Amazonia). For the identification of soybean areas, the Perpendicular Crop Enhancement Index (PCEI) spectral model was calculated using a cloud platform. To verify areas (polygons) of largest converted forest-soybean occurrences, the Kernel Density (KD) estimator was applied. Mann–Kendall and Pettitt tests were used to identify trends over the time series. Our findings reveal that 1,387,288 ha were deforested from August 2008 to October 2019 according to PRODES data, of which 108,411 ha (7.81%) were converted into soybean. The ImazonGeo data showed 729,204 hectares deforested and 46,182 hectares (6.33%) converted into soybean areas. Based on the deforestation polygons of the two databases, the KD estimator indicated that the municipalities of Feliz Natal, Tabaporã, Nova Ubiratã, and União do Sul presented higher occurrences of soybean fields in disagreement with the SoyM. The results indicate that the PRODES system presents higher data variability and means statistically superior to ImazonGeo.

scholarly journals Combining Value-Focused Thinking and PROMETHEE Techniques for Selecting a Portfolio of Distributed Energy Generation Projects in the Brazilian Electricity Sector

2021 ◽  
Vol 13 (19) ◽  
pp. 11091
Author(s):  
Mirian Bortoluzzi ◽  
Marcelo Furlan ◽  
Simone Geitenes Colombo ◽  
Tatiele Martins Amaral ◽  
Celso Correia de Souza ◽  
...  
Keyword(s):  
Decision Making ◽  
Portfolio Management ◽  
Decision Model ◽  
Energy Generation ◽  
Preference Ranking ◽  
Distributed Energy ◽  
Numerical Application ◽  
Mato Grosso ◽  
Value Focused Thinking ◽  
Distributed Energy Generation

This article aims to propose a multi-criteria model to support decision-making from a portfolio in selecting technologies for Distributed Generation of Energy (DGE) projects based on the characteristics of the geographic space in Brazil. The decision model involves using multi-criteria to support the evaluation, prioritization, and selection of projects under a multistage decision-making process that fits into a strategic management cycle within the energy sector of Mato Grosso do Sul (Brazil). The over-classification techniques Preference Ranking Organization Technique for Enrichment Evaluations (PROMETHEE) II and V were applied under the Value-Focused Thinking (VFT) approach, reflecting the decision-maker or manager preferences among several conflicting criteria in the investment context of sustainable distributed energy generation projects. Based on real data, a numerical application is employed to view the steps of this decision model and illustrate the adequacy and effectiveness in practical issues of portfolio management.

scholarly journals Applying analytic hierarchy process (AHP) to identify decision-making in soybean supply chains: a case of Mato Grosso production

2022 ◽  
Vol 60 (2) ◽  
Author(s):  
Rodrigo Carlo Toloi ◽  
João Gilberto Mendes dos Reis ◽  
Marley Nunes Vituri Toloi ◽  
Oduvaldo Vendrametto ◽  
José António Sarsfield Pereira Cabral
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Agricultural Production ◽  
Analytic Hierarchy ◽  
Mato Grosso ◽  
Soybean Production ◽  
Financing Cost ◽  
Hierarchy Process ◽  
The Empirical Analysis ◽  
Rural Production

Abstract: This paper aims to identify and analyze the factors that influence the decision of Mato Grosso’s farmers to produce soybean using the Analytic Hierarchy Process (AHP). We found evidence that decision-making of soybean production is related to rural production aspects such as climate, financing, cost of inputs, and soil quality rather than marketing and logistics. The novelty of this paper is the empirical analysis of the decision-making in agricultural production using AHP. The decision model was created and tested considering 21 farmers and 19 experts linked to the soybean production. Three different scenarios were considered: farmers' view, experts' view, and combined view. Our findings indicate that farmers and experts agree with rural aspects are predominant in the decision to plant soybean. Moreover, logistics have been used as an important flag of soybean competitiveness on international trade by soybean stakeholders in Brazil. However, our results show that logistics impact in the soybean decision-making process is low. Due to data limitation access, this study focuses only on Mato Grosso. However, this study has an exploratory character and presents empirical results that may help to understand soybean production over the country.

scholarly journals Análise da eficiência das indústrias de açúcar e álcool com a análise envoltória de dados

2020 ◽  
Vol 11 (1) ◽  
pp. 351-361
Author(s):  
Valdir Antonio Balbino ◽  
Celso Correia de Souza ◽  
Daniel Massen Frainer
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Mato Grosso ◽  
Mato Grosso Do Sul ◽  
Decision Making Units

Este artigo teve como objetivo determinar a eficiência produtiva das indústrias sucroalcooleiras situadas no estado de Mato Grosso do Sul (MS) e verificar quais indústrias eficientes podem ser referências às ineficientes. Utilizou-se de metodologia quantitativa com dados secundários, obtidos de organismos oficiais, tais como: Instituto Brasileiro de Geografia e Estatística (IBGE) e União da Indústria de Cana-de-Açúcar (UNICA), com uso da Análise Envoltória de Dados (DEA – sigla em inglês de Data Envelopment Analysis) ferramenta não paramétrica que avalia a eficiência técnica relativa de unidades produtivas. Os anos analisados foram 2000, 2005, 2010 e 2015, com um insumo (cana-de-açúcar) e dois produtos (açúcar e etanol). Esses períodos foram escolhidos seguindo preceitos do IBGE, com fins de determinar se as empresas se encontram em comparação a períodos passados e, também, em razão de apurar as (in) eficiências no decorrer dos períodos nas Unidades Tomadoras de Decisão (DMU, da sigla em inglês Decision Making Units). O modelo DEA-CCR com orientação de entrada foi escolhido para obter a classificação das indústrias de cana-de-açúcar. Os resultados mostraram que as empresas instaladas apresentaram de média a alta eficiência no uso de cana-de-açúcar. As conclusões apontaram que a eficiência média caiu entre os períodos analisados, no entanto, nenhuma das unidades apresentou baixa eficiência, nem mesmo aquelas que estavam paralisando as atividades.

Discarding optimality: Throwing out the baby with the bathwater?

2018 ◽  
Vol 41 ◽  
Author(s):  
Patrick Simen ◽  
Fuat Balcı
Keyword(s):  
Decision Making ◽  
Perceptual Decision Making ◽  
Reward Rate ◽  
Perceptual Decision ◽  
Standard Observer ◽  
Rate Maximization ◽  
Reward Rate Maximization ◽  
Descriptive Standard ◽  
Observer Model

AbstractRahnev & Denison (R&D) argue against normative theories and in favor of a more descriptive “standard observer model” of perceptual decision making. We agree with the authors in many respects, but we argue that optimality (specifically, reward-rate maximization) has proved demonstrably useful as a hypothesis, contrary to the authors’ claims.

LPCD framework: Analytical tool or psychological model?

2018 ◽  
Vol 41 ◽  
Author(s):  
David Danks
Keyword(s):  
Decision Making ◽  
Analytical Tool ◽  
Mathematical Framework ◽  
Bayesian Decision ◽  
Perceptual Decision Making ◽  
Psychological Model ◽  
Psychological Reality ◽  
Psychological Theories ◽  
Target Article ◽  
Bayesian Decision Making

AbstractThe target article uses a mathematical framework derived from Bayesian decision making to demonstrate suboptimal decision making but then attributes psychological reality to the framework components. Rahnev & Denison's (R&D) positive proposal thus risks ignoring plausible psychological theories that could implement complex perceptual decision making. We must be careful not to slide from success with an analytical tool to the reality of the tool components.

Elaborating the role of reflection and individual differences in the study of folk-economic beliefs

2018 ◽  
Vol 41 ◽  
Author(s):  
Kevin Arceneaux
Keyword(s):  
Decision Making ◽  
Individual Differences ◽  
Cognitive Processes ◽  
Evolutionary History ◽  
Behavioral Responses ◽  
History Of ◽  
Economic Beliefs

AbstractIntuitions guide decision-making, and looking to the evolutionary history of humans illuminates why some behavioral responses are more intuitive than others. Yet a place remains for cognitive processes to second-guess intuitive responses – that is, to be reflective – and individual differences abound in automatic, intuitive processing as well.

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