Geração de zonas de manejo para cafeicultura usando sensor SPAD e análise foliar

• Ano de defesa: 2008
• Autor(a) principal: Rodrigues Junior, Francelino Augusto
• Orientador(a): Vieira, Luciano Baião
• Banca de defesa: Fernandes, Haroldo Carlos , Santos, Nerilson Terra , Teixeira, Mauri Martins
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Viçosa
• Programa de Pós-Graduação: Mestrado em Engenharia Agrícola
• Departamento: Construções rurais e ambiência; Energia na agricultura; Mecanização agrícola; Processamento de produ
• País: BR
• Palavras-chave em Português: Agricultura de precisão; Zonas de manejo; Sensor de clorofila
• Palavras-chave em Inglês: Precision agriculture; Management zones; Chlorophyll meter
• Área do conhecimento CNPq: CNPQ::CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA
• Link de acesso: http://locus.ufv.br/handle/123456789/3511

One of the critical problems of the precision agriculture is the need of a dense sampling in order to detect the spatial variability of the attribute in study, allowing the generation of maps. One of the solutions for this problem is being the generation of management zones. The objective of this work was: a) to define management zones for coffee crop using K- Means and Fuzzy C-Means methods, based on determinations accomplished with chlorophyll meter and leaf analysis; b) to analyze the correlation between the values of the chlorophyll meter and the results of the leaf analysis of nutrients and c) to evaluate the management zones obtained using the two clustering methods. This work was carried out at Fazenda Jatobá, located in Paula Cândido, MG, during November 2007. The evaluated area had 2.1 ha cultivated with Coffea Arabic L., Catuaí variety, in a soil characterized as Argissolo Vermelho-Amarelo. The rate sampling for the SPAD was made in an alternate way in relation to the row planting, sampling one each four plants, a total of 1145 plants were sampled. The leaves collection was submitted to the leaf analysis to each 10 plants used for SPAD reading. Therefore, this tenth point consisted of simultaneous determinations of SPAD and leaf analysis in laboratory. A total 114 plants were sampled in this way. The correlation between the values of SPAD and the macro and micronutrient leaf concentrations of leaf were analyzed through the Pearson s correlation. The management zones generated using the two clustering methods based on the SPAD values were compared to the ones generated using the results from the N, P and K leaf concentrations; the N and Ca leaf concentrations; the N leaf concentrations; the N, Zn and B leaf concentrations; the N, P, K, Ca and S leaf concentrations; the N, Ca and S leaf concentrations. The correlation found between SPAD values and N leaf concentration in this commercial farm was 34%. This result is smaller than the 94% to 98% found in the literature for experiments in controlled environments. The clustering methods K-Means and Fuzzy C-Means did not present differences in the generation of the management zones. There was low similarity among the management zones generated with use of SPAD and nutrient leaf concentration.