A heterogeneidade tecnológica da pecuária leiteira em Minas Gerais

Simões, André Rozemberg Peixoto; Reis, Janderson Damaceno dos; Avelar, Patrícia Silva

doi:10.30612/agrarian.v10i37.6782

Cited by 10 publications

(4 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Milk production occurs on 1.2 million farms (23% of all farms) that are widely dispersed throughout the country, reflecting a diverse set of social, cultural, and climatic factors (IBGE, 2017). As a result, dairy farms are heterogeneous in terms of technology adoption intensity and production scale (Silva et al, 2016;Simões et al, 2017;Telles et al, 2017). According to Gomes (2006) 'technological duality' is a prominent feature in Brazilian milk production because farmers using higher-productivity technology operate side by side with farmers using low-input, low-output systems with limited adoption of newer available technologies.…”

Section: Introductionmentioning

confidence: 99%

Dynamic impacts of farm-level technology adoption on the Brazilian dairy supply chain

Simões

Nicholson

Novaković

et al. 2020

IFAM

View full text Add to dashboard Cite

Agricultural technology adoption that increases individual firm productivity is generally assumed to improve competitiveness and profitability. However, technology that is adopted by many firms in an industry can shift the basic supply relationship, increasing total production while lowering farm prices. While generally beneficial to consumers, this result can reduce (or completely offset) benefits for farmers, especially late or non-adopters. Our objective is to assess the market dynamics of alternative assumptions about exogenous productivity-enhancing technology adoption by Brazilian dairy farms. Of particular interest is the distributional impact on farm incomes and on the proportion of milk production for different farm size classes. To achieve this objective, we developed an empirical System Dynamics model that evaluates market and farm profitability impacts from 2006 to 2016. We simulated six counterfactual scenarios comprising three rates of adoption (slow, medium and fast) by two farm size categories (small and large). Technology adoption impact differs in the short- and long-term and depending on the assumed rates and farm sizes. Non-adopters of technology can experience lower incomes and a smaller production and income shares when other farms adopt. The underlying causal structure of farm profitability and the herd management decisions suffices to explain the potential market exclusion of non-adopting farms (especially small-scale farms) when others adopt.

show abstract

Section: Introductionmentioning

confidence: 99%

Dynamic impacts of farm-level technology adoption on the Brazilian dairy supply chain

Simões

Nicholson

Novaković

et al. 2020

IFAM

View full text Add to dashboard Cite

show abstract

“…Esta padronização consistiu em adquirir médias iguais a zero (0,0) e desvios padrões iguais a um (1,0). Desta forma é possível evitar problemas decorrentes de desigualdade das unidades de medidas das variáveis e estabilizar as variâncias para a determinação das cargas fatoriais (FIELD, 2009;SIMÕES et al, 2017). A tabela 10 demonstra a correlação altamente significativa (P<0,01) entre as variáveis estudadas, onde foi estimado um score fatorial para cada tratamento através da multiplicação do valor das variáveis padronizadas pelo coeficiente do score fatorial correspondente (FÁVERO et al, 2009;HAIR et al, 2009).…”

Section: Resultsunclassified

EXTRACCION Y PROPIEDADES TECNOFUNCIONALES DE PROTEINA DE QUINUA (Chenopodium quínoa willd) DE LAS VARIEDADES BLANCA JUNIN Y ROSADA JUNIN

Lujan¹,

Acosta²,

Carrión³

et al. 2023

Ciencias Agrarias: Estudios Sistemáticos E Investigación Avanzada

View full text Add to dashboard Cite

Editora Direitos para esta edição cedidos à Atena Editora pelos autores. Open access publication by Atena Editora Todo o conteúdo deste livro está licenciado sob uma Licença de Atribuição Creative Commons. Atribuição-Não-Comercial-NãoDerivativos 4.0 Internacional (CC BY-NC-ND 4.0). O conteúdo dos artigos e seus dados em sua forma, correção e confiabilidade são de responsabilidade exclusiva dos autores, inclusive não representam necessariamente a posição oficial da Atena Editora. Permitido o download da obra e o compartilhamento desde que sejam atribuídos créditos aos autores, mas sem a possibilidade de alterála de nenhuma forma ou utilizá-la para fins comerciais.Todos os manuscritos foram previamente submetidos à avaliação cega pelos pares, membros do Conselho Editorial desta Editora, tendo sido aprovados para a publicação com base em critérios de neutralidade e imparcialidade acadêmica.A Atena Editora é comprometida em garantir a integridade editorial em todas as etapas do processo de publicação, evitando plágio, dados ou resultados fraudulentos e impedindo que interesses financeiros comprometam os padrões éticos da publicação. Situações suspeitas de má conduta científica serão investigadas sob o mais alto padrão de rigor acadêmico e ético.

show abstract

“…The four factors made similar contributions to explaining the total variance of the dataset and, consequently, the variability between dairy farms of the studied region. Previous studies have shown that similar technological aspects are important in distinguishing dairy farms in Brazil (Gabbi et al, 2013;Neumann et al, 2016;Simões et al, 2017;Zimpel et al, 2017) and other developing countries (García et al, 2012;Janssen & Swinnen, 2017;Rangel et al, 2020).…”

Section: Discussionmentioning

confidence: 98%

Inseparability of Dairy Farming Technologies and Their Impacts on Milk Production Systems in Brazil

Lima

Damasceno

Simões

et al. 2022

Trop. Anim. Sci. J.

View full text Add to dashboard Cite

Several studies have analyzed the impact of one technology on the productive performance of dairy systems. However, analyses that consider the impact of joint technologies are scarce. This study was aimed to analyze the inseparability of a set of technologies and their impacts on dairy farm performance. Questionnaires were applied on-site with 155 dairy farmers in Paraná State, Brazil. We collected 17 technological variables related to milk production and variables related to dairy farms' production. Data analysis was performed in three steps: descriptive analysis, exploratory factor analysis (EFA), and multiple regression. Descriptive analysis was applied to characterize the sample, EFA was applied to generate factors related to the technological variables, and multiple regression was used to compare technological factors with productivity variables -farm performance. Four factors were defined: (i) Forage and farm structure, (ii) management, (iii) genetics, breeding strategies, and concentrate feeding, and (iv) animal health. The four factors significantly explained the differences in milk productivity between dairy farms. Technologies grouped under the factor of genetics were the most important in explaining milk yield per lactating cow, land productivity, and dairy herd reproductive efficiency.

show abstract

A heterogeneidade tecnológica da pecuária leiteira em Minas Gerais

Cited by 10 publications

References 2 publications

Dynamic impacts of farm-level technology adoption on the Brazilian dairy supply chain

Dynamic impacts of farm-level technology adoption on the Brazilian dairy supply chain

EXTRACCION Y PROPIEDADES TECNOFUNCIONALES DE PROTEINA DE QUINUA (Chenopodium quínoa willd) DE LAS VARIEDADES BLANCA JUNIN Y ROSADA JUNIN

Inseparability of Dairy Farming Technologies and Their Impacts on Milk Production Systems in Brazil

Contact Info

Product

Resources

About