Recomendação de adubação potássica para trigo, milho e soja sob sistema plantio direto no Paraguai

A ferramenta mais utilizada para se recomendar adubação é a análise de solo. Com ela é possível avaliar o estado de fertilidade do solo e determinar a quantidade de nutrientes necessária para o adequado crescimento e desenvolvimento das plantas. Para que isso seja possível, é necessário ter tabelas de interpretação e recomendação elaboradas a partir de experimentos realizados em campo. Um sistema de recomendação de adubação normalmente visa suprir a demanda das culturas e elevar os teores no solo ao nível de suficiência. Com o objetivo de obter informações para elaboração de uma tabela de interpretação de teores no solo e recomendação de adubação potássica para solos cultivados em plantio direto, foram realizados sete experimentos em rede em quatro Departamentos do Paraguai: dois no departamento de Missiones, dois no Departamento de Itapúa, dois no Departamento de Alto Paraná e um no Departamento de Amanbay. O delineamento experimental utilizado foi de blocos ao acaso, com três repetições. Os tratamentos consistiram de cinco doses de K2O (0, 25, 50, 75 e 100 kg ha-1) aplicadas em superfície antes da semeadura das culturas. As adubações de N e P foram constantes e satisfatórias para atender as necessidades das culturas, utilizando-se a dose de 100 kg ha-1 de P2O5 para trigo, milho e soja, 60 kg ha-1 de N para o trigo e 180 kg ha-1 de N para o milho. Foram determinados o teor de K no solo pelo método Mehlich-1 após cada cultura, e o rendimento de grãos de trigo, milho e soja. Foi calculado o rendimento relativo para cada experimento e cultura, e utilizou-se a equação de Mitscherlich para descrever a relação entre os teores de K no solo e os valores de rendimento relativo (curva de calibração). O teor crítico médio para as três culturas, definido como o valor do nutriente no solo para a probabilidade de resposta de aproximadamente 90 % do rendimento máximo, foi de 75 mg dm-3. Foi necessário aplicar 5 kg ha-1 de K2O para elevar em 1 mg dm-3 o teor de K no solo. Em teores no solo acima de 150 mg dm-3, as plantas apresentaram baixa resposta à aplicação de fertilizantes potássicos.

Parasitofauna de cachara cultivado em tanque-rede no rio Paraguai

O objetivo deste trabalho foi descrever a fauna parasitária de cachara (Pseudoplatystoma reticulatum) cultivado em tanque-rede, no rio Paraguai. Dez peixes com peso médio de 598,0±81,3 g e comprimento total médio de 38,6±1,6 cm foram examinados. Todos os peixes necropsiados apresentaram infestação por pelo menos duas espécies de parasitos. Entre os parasitos, foram encontrados Ichthyophthirius multifiliis (Ciliophora), Myxobolus sp. e Henneguya sp. (Myxozoa), Monogenoidea, Choanoscolex abscissus e Nominoscolex sudobim (Cestoda), Dolops carvalhoi (Crustacea) e Digenea. O protozoário Ichthyophthirius multifiliis foi o parasito com maior prevalência.

Análise espaço-temporal da cobertura vegetal e uso da terra na Interbacia do Rio Paraguai Médio-MT, Brasil

O objetivo deste estudo foi realizar uma análise espaço-temporal da cobertura vegetal e do uso da terra na Interbacia do Rio Paraguai Médio-MT, Brasil, pelo geoprocessamento de imagens Landsat TM, dos anos 1991, 2001 e 2011. As imagens foram georreferenciadas, classificadas e processadas no software Spring e as classes temáticas, quantificadas e editadas no software ArcGis. Foram mapeadas sete classes, sendo as mais expressivas a vegetação nativa, a pastagem e a cana-de-açúcar. Os resultados indicaram alterações em todas as classes durante os últimos 20 anos, com a diminuição de 22,89% da vegetação nativa, relacionada com o aumento de 58,42% da pastagem e 490,26% de monocultura de cana-de-açúcar. Foi verificado o conflito de uso da terra, principalmente em áreas de mata ciliar, fato que pode influenciar negativamente na conservação da interbacia e, consequentemente, do pantanal mato-grossense.

Determination of management zones from normalized and standardized equivalent produtivity maps in the soybean culture

Through the site-specific management, the precision agriculture brings new techniques for the agricultural sector, as well as a larger detailing of the used methods and increase of the global efficiency of the system. The objective of this work was to analyze two techniques for definition of management zones using soybean yield maps, in a productive area handled with localized fertilization and other with conventional fertilization. The sampling area has 1.74 ha, with 128 plots with site-specific fertilization and 128 plots with conventional fertilization. The productivity data were normalized by two techniques (normalized and standardized equivalent productivity), being later classified in management zones. It can be concluded that the two methods of management zones definition had revealed to be efficient, presenting similarities in the data disposal. Due to the fact that the equivalent standardized productivity uses standard score, it contemplates a better statistics justification.

Management zones in agriculture acording to the soil and landscape variables

The study of spatial variability of soil and plants attributes, or precision agriculture, a technique that aims the rational use of natural resources, is expanding commercially in Brazil. Nevertheless, there is a lack of mathematical analysis that supports the correlation of these independent variables and their interactions with the productivity, identifying scientific standards technologically applicable. The aim of this study was to identify patterns of soil variability according to the eleven physical and seven chemical indicators in an agricultural area. It was used two multivariate techniques: the hierarchical cluster analysis (HCA) and the principal component analysis (PCA). According to the HCA, the area was divided into five management zones: zone 1 with 2.87ha, zone 2 with 0.8ha, zone 3 with 1.84ha, zone 4 with 1.33ha and zone 5 with 2.76ha. By the PCA, it was identified the most important variables within each zone: V% for the zone 1, CTC in the zone 2, levels of H+Al in the zone 4 and sand content and altitude in the zone 5. The zone 3 was classified as an intermediate zone with characteristics of all others. According to the results it is concluded that it is possible to separate into groups (management zones) samples with the same patterns of variability by the multivariate statistical techniques.

Management zones definition using soil chemical and physical attributes in a soybean area

Several equipments and methodologies have been developed to make available precision agriculture, especially considering the high cost of its implantation and sampling. An interesting possibility is to define management zones aim at dividing producing areas in smaller management zones that could be treated differently, serving as a source of recommendation and analysis. Thus, this trial used physical and chemical properties of soil and yield aiming at the generation of management zones in order to identify whether they can be used as recommendation and analysis. Management zones were generated by the Fuzzy C-Means algorithm and their evaluation was performed by calculating the reduction of variance and performing means tests. The division of the area into two management zones was considered appropriate for the present distinct averages of most soil properties and yield. The used methodology allowed the generation of management zones that can serve as source of recommendation and soil analysis; despite the relative efficiency has shown a reduced variance for all attributes in divisions in the three sub-regions, the ANOVA did not show significative differences among the management zones.

Management zones using fuzzy clustering based on spatial-temporal variability of soil and corn yield

Clustering soil and crop data can be used as a basis for the definition of management zones because the data are grouped into clusters based on the similar interaction of these variables. Therefore, the objective of this study was to identify management zones using fuzzy c-means clustering analysis based on the spatial and temporal variability of soil attributes and corn yield. The study site (18 by 250-m in size) was located in Jaboticabal, São Paulo/Brazil. Corn yield was measured in one hundred 4.5 by 10-m cells along four parallel transects (25 observations per transect) over five growing seasons between 2001 and 2010. Soil chemical and physical attributes were measured. SAS procedure MIXED was used to identify which variable(s) most influenced the spatial variability of corn yield over the five study years. Basis saturation (BS) was the variable that better related to corn yield, thus, semivariograms models were fitted for BS and corn yield and then, data values were krigged. Management Zone Analyst software was used to carry out the fuzzy c-means clustering algorithm. The optimum number of management zones can change over time, as well as the degree of agreement between the BS and corn yield management zone maps. Thus, it is very important take into account the temporal variability of crop yield and soil attributes to delineate management zones accurately.

Redundant variables and the quality of management zones

ABSTRACT Precision agriculture (PA) allows farmers to identify and address variations in an agriculture field. Management zones (MZs) make PA more feasible and economical. The most important method for defining MZs is a fuzzy C-means algorithm, but selecting the variable for use as the input layer in the fuzzy process is problematic. BAZZI et al. (2013) used Moran’s bivariate spatial autocorrelation statistic to identify variables that are spatially correlated with yield while employing spatial autocorrelation. BAZZI et al. (2013) proposed that all redundant variables be eliminated and that the remaining variables would be considered appropriate on the MZ generation process. Thus, the objective of this work, a study case, was to test the hypothesis that redundant variables can harm the MZ delineation process. BAZZI This work was conducted in a 19.6-ha commercial field, and 15 MZ designs were generated by a fuzzy C-means algorithm and divided into two to five classes. Each design used a different composition of variables, including copper, silt, clay, and altitude. Some combinations of these variables produced superior MZs. None of the variable combinations produced statistically better performance that the MZ generated with no redundant variables. Thus, the other redundant variables can be discredited. The design with all variables did not provide a greater separation and organization of data among MZ classes and was not recommended.