No abstract

RESUMO:Áreas com diferentes potenciais de rendimento dentro de uma lavoura necessitam ser manejadas separadamente, para fins de aplicação da adubação nitrogenada em cobertura. O equipamento baseado em sensoriamento remoto terrestre (GreenSeeker) é um dos instrumentos utilizados para separar diferentes zonas de manejo. Para fazer isso, o sensor permite a definição de classes para estimar o potencial produtivo de forma ágil, precisa e em tempo real. Com o instrumento, foi desenvolvido um modelo para estimativa do potencial produtivo em trigo e cevada, correlacionando o Índice de Vegetação por Diferença Normalizada (NDVI) com a biomassa seca acumulada na parte aérea, por ocasião da emissão da sexta folha do colmo principal. A base do modelo foi a formação de classes de potencial produtivo correspondentes a zonas específicas de manejo da lavoura. Essas classes não necessitam ser específicas para diferentes cultivares e/ou espécies, visto que não se detectaram diferenças que justificassem a formação de grupos para elas. As superfícies de fundo (resíduos de restevas de soja e milho) tiveram efeitos significativos nas leituras do sensor. O modelo continua válido mesmo se as leituras de NDVI forem feitas antes ou após o período recomendado para tal, podendo ser ajustado com sub ou superestimação. As análises de variabilidade espacial, futuramente, podem avaliar se, as zonas de potencial produtivo estimadas pelas classes de NDVI propostas pelo modelo, correspondem à flutuação espacial da biomassa, doses de N aplicadas e rendimento de grãos. PALAVRAS-CHAVE: agricultura de precisão, adubação nitrogenada em taxa variável, NDVI. MODEL FOR YIELD POTENTIAL ESTIMATION IN WHEAT AND BARLEY USING THE GREENSEEKER SENSORABSTRACT: Areas with different yield potential within a field need to be managed separately as for nitrogen application in small grain cereals. Terrestrial remote sensing-based equipment such as the GreenSeeker sensor is one of the tools available to handle different management zones. To do this, the sensor allows the definition of classes to estimate yield potential. A model which correlated the Normalized Difference Vegetation Index (NDVI) to shoot dry biomass at the 6-leaf-stage was developed for estimating yield potential classes for wheat and barley. The model eliminated differences between species and cultivars as no correction for these factors is necessary. The effects of surface background (corn or soybean crop residues) were considered in this model. When readings are carried out before or after the recommended period, the model can be adjusted for under or overestimation. Spatial variability analysis may evaluate if yield potential zones estimated by the NDVI classes proposed in the model are related to spatial variability of shoot biomass, N rates applied and grain yield.

RESUMO Em decorrência da instabilidade da produtividade das principais culturas associada ao déficit hídrico, tem se tornado cada vez mais frequente a necessidade do uso de tecnologias como a irrigação e a agricultura de precisão (AP 2010/2011 and 2011/2012, in an area of 35ha managed under notill and center-pivot

RESUMO A adubação nitrogenada em trigo é baseada no potencial produtivo da cultura, teor de matéria orgânica do solo e cultura antecessora. A defi nição do potencial produtivo

BackgroundDrought is by far the most important environmental factor contributing to yield losses in crops, including soybeans [Glycine max (L.) Merr.]. To address this problem, a gene that encodes an osmotin-like protein isolated from Solanum nigrum var. americanum (SnOLP) driven by the UBQ3 promoter from Arabidopsis thaliana was transferred into the soybean genome by particle bombardment.ResultsTwo independently transformed soybean lines expressing SnOLP were produced. Segregation analyses indicated single-locus insertions for both lines. qPCR analysis suggested a single insertion of SnOLP in the genomes of both transgenic lines, but one copy of the hpt gene was inserted in the first line and two in the second line. Transgenic plants exhibited no remarkable phenotypic alterations in the seven analyzed generations. When subjected to water deficit, transgenic plants performed better than the control ones. Leaf physiological measurements revealed that transgenic soybean plants maintained higher leaf water potential at predawn, higher net CO2 assimilation rate, higher stomatal conductance and higher transpiration rate than non-transgenic plants. Grain production and 100-grain weight were affected by water supply. Decrease in grain productivity and 100-grain weight were observed for both transgenic and non-transgenic plants under water deficit; however, it was more pronounced for non-transgenic plants. Moreover, transgenic lines showed significantly higher 100-grain weight than non-transgenic plants under water shortage.ConclusionsThis is the first report showing that expression of SnOLP in transgenic soybeans improved physiological responses and yield components of plants when subjected to water deficit, highlighting the potential of this gene for biotechnological applications.

This paper aims to discuss the impact of the introduction of pastures and grazing animals in agricultural systems. For the purposes of this manuscript, we focus on within-farm integrated crop-livestock systems (ICLS), typical of Southern Brazil. These ICLS are designed to create and enhance the synergisms and emergent properties have arisen from agricultural areas where livestock activities are integrated with crops. We show that the introduction of the crop component will affect less the preceding condition than the introduction of the livestock component. While the introduction of crops in pastoral systems represents increasing diversity of the plant component, the introduction of animals would represent the entry of new flows and interactions within the system. Thus, given the new complexity levels achieved from the introduction of grazing, the probability of arising emergent properties is theoretically much higher. However, grazing management is vital in determining the success or failure of such initiative. The grazing intensity practiced during the pasture phase would affect the canopy structure and the forage availability to animals. In adequate and moderate grazing intensities, it is possible to affirm that livestock combined with crops (ICLS) has a potential positive impact. As important as the improvements that grazing animals can generate to the soil-plant components, the economic resilience remarkably increases when pasture rotations are introduced compared with purely agriculture systems, particularly in climate-risk situations. Thus, the integration of the pastoral component can enhance the sustainable intensification of food production, but it modifies simple, pure agricultural systems into more complex and knowledge-demanding production systems.

RESUMO

-Grazing livestock in integrated crop-livestock systems can cause impacts in the subsequent crop cycle. Aiming to investigate how grazing could affect soybean, the 9th crop cycle of a pasture/soybean rotation was assessed. Treatments were grazing intensities (10, 20, 30 and 40 cm of sward height) applied since 2001 in a mixed of oat and annual ryegrass; and an additional no grazing area as control. Treatments were arranged in a completely randomized block design with three replicates. Grazing affected soybean population and the mass of individual nodules (P<0.05), while the number and mass of nodules per plant were similar (P>0.05). Soybean yield showed differences among treatments, but no difference was found between grazed and non-grazed areas. Grazing intensities impact the coverage and frequency of weeds (P>0.05). In conclusion, grazing intensity impacts different parameters of soybean yield and development, but only the grazing intensity of 10 cm can jeopardize the succeeding soybean crop.