Beaufils ranges to assess the cotton nutrient status in the southern region of Mato Grosso

The relationships between nutrient contents and indices of the Diagnosis and Recommendation Integrated System (DRIS) are a useful basis to determine appropriate ranges for the interpretation of leaf nutrient contents. The purpose of this study was to establish Beaufils ranges from statistical models of the relationship between foliar concentrations and DRIS indices, generated by two systems of DRIS norms - the F value and natural logarithm transformation - and assess the nutritional status of cotton plants, based on these Beaufils ranges. Yield data from plots (average acreage 100 ha) and foliar concentrations of macro and micronutrients of cotton (Gossypium hirsutum r. latifolium) plants, in the growing season 2004/2005, were stored in a database. The criterion to define the reference population consisted of plots with above-average yields + 0.5 standard deviation (over 4,575 kg ha-1 seed cotton yield). The best-fitting statistical model of the relationship between foliar nutrient concentrations and DRIS indices was linear, with R² > 0.8090, p < 0.01, except for N, with R² = 0.5987, p < 0.01. The two criteria were effective to diagnose the plant nutritional status. The diagnoses were not random, but based on the effectiveness of the chi-square-tested method. The agreement between the methods to assess the nutritional status was 92.59-100 %, except for S, with 74.07 % agreement.

Estimating soybean crop areas using spectral-temporal surfaces derived from MODIS images in Mato Grosso, Brazil

The objective of this work was to evaluate the application of the spectral-temporal response surface (STRS) classification method on Moderate Resolution Imaging Spectroradiometer (MODIS, 250 m) sensor images in order to estimate soybean areas in Mato Grosso state, Brazil. The classification was carried out using the maximum likelihood algorithm (MLA) adapted to the STRS method. Thirty segments of 30x30 km were chosen along the main agricultural regions of Mato Grosso state, using data from the summer season of 2005/2006 (from October to March), and were mapped based on fieldwork data, TM/Landsat-5 and CCD/CBERS-2 images. Five thematic classes were considered: Soybean, Forest, Cerrado, Pasture and Bare Soil. The classification by the STRS method was done over an area intersected with a subset of 30x30-km segments. In regions with soybean predominance, STRS classification overestimated in 21.31% of the reference values. In regions where soybean fields were less prevalent, the classifier overestimated 132.37% in the acreage of the reference. The overall classification accuracy was 80%. MODIS sensor images and the STRS algorithm showed to be promising for the classification of soybean areas in regions with the predominance of large farms. However, the results for fragmented areas and smaller farms were less efficient, overestimating soybean areas.

Blueberry production in Chile: current status and future developments

Chile has become a major actor in the blueberry industry as the most important supplier of off-season fresh fruit for the northern hemisphere. Blueberry exports passed from US$ 30 million (around 4,000 tons) in 2000 to US$ 380 million (94,000 tons) in 2011. The characteristics of the major blueberry growing regions (North, Central, South-central and South) are presented in terms of acreage, varieties, management practices, extension of the harvest season, and soil and climatic conditions. Most fruit is from highbush varieties, picked by hand and exported fresh by boat to United States. Largest proportion of fruit is exported from mid December to late January, which coincides with lowest prices. The south-central region (latitudes 34º50' to 38º15' S) was in 2007 the most important one with 5,075 ha (51.1% of area planted). Among the challenges for the Chilean blueberry industry in the near future are: 1. Lower profitability due to lower rates of currency exchange and higher costs, 2 - Greater scarcity and higher cost of labor, 3.- Need for higher productivity and sustainable production practices, 4- Fruit of high and consistent quality, and 5.- Greater investment in research. As a case study the article presents three approaches that can help identify areas with low availability of labor and improve its efficiency. The article shows the use of geomatic tools to establish labor availability, application of growth regulators to reduce crop load, increase fruit size and improve harvest efficiency, and the use of shakers to harvest fresh fruit for long distance markets. More research is needed to improve yields, reduce costs and give greater economical and ecological sustainability to the Chilean blueberry industry.