Coffee is highly tolerant to cadmium, nickel and zinc: Plant and soil nutritional status, metal distribution and bean yield

Sewage sludge has been used to fertilize coffee, increasing the risk of metal contamination in this crop. The aim of this work was to study the effects of Cd, Zn and Ni in adult coffee plants growing under field conditions. Seven-year-old coffee plants growing in the field received one of three;loses of Cd, Zn or Ni: 15,45 and 90 g Cd plant(-1); 35, 105 and 210 g Ni plant(-1); and 100, 300 and 600 g Zn plant(-1), with all three metals in the form of sulphate salts. After three months, we noticed good penetration of the three metals into the soil, especially in the first 50 cm, which is the region where most coffee plant roots are concentrated. Leaf concentrations of K, Ca, Mg, S, B, Cu, Fe and Mn were nor affected. N levels did not change with the application of Ni or Zn but were reduced with either 45 or 90 g Cd plant(-1). Foliar P concentrations decreased with the addition of 45 and 90 g Cd plant(-1) and 600 g Zn plant(-1). Zn levels in leaves were not affected by the application of Cd or Ni. The highest concentrations. of Zn were found in branches (30-230 mg kg(-1)), leaves (7-35 mg kg(-1)) and beam (4-6.5 mg kg(-1)); Ni was found in leaves (4-45 mg kg(-1)), branches (3-18 mg kg(-1)) and beans (1-5 mg kg(-1)); and Cd was found in branches (0-6.2 mg kg(-1)) and beans (0-1.5 mg kg(-1)) but was absent in leaves. The mean yield of two harvests was not affected by Ni, but it decreased at the highest dose of Zn (600 g plant(-1)) and the two higher doses of Cd (45 and 90 g plant(-1)). Plants died when treated with the highest dose of Cd and showed symptoms of toxicity with the highest dose of Zn. Nevertheless, based on the amounts of metal used and the results obtained, we conclude that coffee plants are highly tolerant to the three metals tested. Moreover, even at high doses, there was very little transport to the beans, which is the part consumed by humans. (C) 2011 Elsevier B.V. All rights reserved.

STOCHASTIC MODEL FOR SIMULATING MAIZE YIELD

Maize is one of the most important crops in the world. The products generated from this crop are largely used in the starch industry, the animal and human nutrition sector, and biomass energy production and refineries. For these reasons, there is much interest in figuring the potential grain yield of maize genotypes in relation to the environment in which they will be grown, as the productivity directly affects agribusiness or farm profitability. Questions like these can be investigated with ecophysiological crop models, which can be organized according to different philosophies and structures. The main objective of this work is to conceptualize a stochastic model for predicting maize grain yield and productivity under different conditions of water supply while considering the uncertainties of daily climate data. Therefore, one focus is to explain the model construction in detail, and the other is to present some results in light of the philosophy adopted. A deterministic model was built as the basis for the stochastic model. The former performed well in terms of the curve shape of the above-ground dry matter over time as well as the grain yield under full and moderate water deficit conditions. Through the use of a triangular distribution for the harvest index and a bivariate normal distribution of the averaged daily solar radiation and air temperature, the stochastic model satisfactorily simulated grain productivity, i.e., it was found that 10,604 kg ha(-1) is the most likely grain productivity, very similar to the productivity simulated by the deterministic model and for the real conditions based on a field experiment.

Rootstocks for high fruit yield and quality of 'Tahiti' lime under rain-fed conditions

Despite considerable research conducted on 'Tahiti' lime [Citrus latifolia (Yu Tanaka) Tanaka] in several countries, few long-term studies have focused on rootstock effects on fruit production and quality under non-irrigated conditions. As for many other fruit crops, rootstock studies for 'Tahiti' lime are often based on the evaluation of several horticultural responses simultaneously, instead of considering multivariate statistical approaches which may provide with more comprehensive information. Consequently, a trial was installed to evaluate the horticultural performance of non-irrigated 'Tahiti' lime trees budded onto the following 12 rootstocks: 'HRS 801' and 'HRS 827' hybrids; 'Rubidoux', 'FCAV' and 'Flying Dragon' trifoliates; 'Sun Chu Sha Kat' and 'Sunki' mandarins; 'Cravo Limeira' and 'Cravo FCAV' 'Rangpur' limes; 'Carrizo' citrange, 'Swingle' citrumelo, and 'Orlando' tangelo. The trial was installed in 2001, in an 8 m x 5 m spacing with no supplementary irrigation. Measurements of yield, fruit quality oriented to different consuming markets, canopy volume and tree tolerance to drought, were performed. A multivariate cluster analysis identified both 'Rangpur' lime rootstocks as those inducing larger cumulative yield and higher percentage of fruits for the domestic market, with highest drought tolerance to the trees. Despite of their high susceptibility to drought stress under non-irrigated conditions, the 'Flying Dragon' and 'FCAV' trifoliate rootstocks performed outstandingly for 'Tahiti' lime, inducing higher yield efficiency, early bearing and larger percentage of high-quality fruits for foreign markets, with smaller trees more suitable for high-density plantings. (c) 2012 Elsevier B.V. All rights reserved.

Yield mapping, soil fertility and tree gaps in an orange orchard

The current high competition on Citrus industry demands from growers new management technologies for superior efficiency and sustainability. In this context, precision agriculture (PA) has developed techniques based on yield mapping and management systems that recognize field spatial variability, which contribute to increase profitability of commercial crops. Because spatial variability is often not perceived the orange orchards are still managed as uniform and adoption of PA technology on citrus farms is low. Thus, the objective of the present study was to characterize the spatial variability of three factors: fruit yield, soil fertility and occurrence of plant gaps caused by either citrus blight or huanglongbing (HLB) in a commercial Valencia orchard in Brotas, São Paulo State, Brazil. Data from volume, geographic coordinates and representative area of the bags used on harvest were recorded to generate yield points that were then interpolated to produce the yield map. Soil chemical characteristics were studied by analyzing samples collected along planting rows and inter-rows in 24 points distributed in the field. A map of density of tree gaps was produced by georeferencing individual gaps and later by counting the number of gaps within 500 m² cells. Data were submitted to statistical and geostatistical analyses. A t test was used to compare means of soil chemical characteristics between sampling regions. High variation on yield and density of tree gaps was observed from the maps. It was also demonstrated overlapping regions of high density of plant absence and low fruit yield. Soil fertility varied depending on the sampling region in the orchard. The spatial variability found on yield, soil fertility and on disease occurrence demonstrated the importance to adopt site specific nutrient management and disease control as tools to guarantee efficiency of fruit production.