Higher yield and economic benefits are achieved in the macadamia crop by irrigation and intercropping with coffee

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Influence of Crop Load on Tree Growth, Yield, and Fruit Quality of Scab Resistant Apples at Harvest

Apple scab, caused by Venturia inaequalis, is a major disease affecting apple production. Breeding programs have developed over 30 releases of scab-resistant cultivars since 1970 with recent ones having much improved quality. Redfree and GoldRush are from a cooperative breeding program involving Purdue, Rutgers, and Illinois universities while Liberty was introduced from the Cornell University breeding program. For these cultivars to gain better acceptance, more information is needed on their cropping capacities and the effect of crop load on fruit quality attributes. Our study was conducted to determine the relationship between increasing crop load on tree growth, fruit size, and fruit quality variables of the three cultivars under Iowa conditions.

Long-term Tillage and Crop Rotation Effects on Yield

Tillage system and crop rotation have a major long-term effect on soil productivity and soil quality components such as soil carbon and other soil physical, biological, and chemical properties. In addition, both tillage and crop rotation have effects on weed and soil disease control. There is a need for well-defined, longterm tillage and crop rotation studies across the different soils and climate conditions in the state. The objective of this study was to evaluate the long-term effects of different tillage systems and crop rotations on soil productivity.

Yield, nutrient utilization and soil properties in a melon crop amended with wine-distillery waste

In Spain, large quantities of wine are produced every year (3,339,700 tonnes in 2011) (FAO, 2011) with the consequent waste generation. During the winemaking process, solid residues like grape stalks are generated, as well as grape marc and wine lees as by-products. According to the Council Regulation (EC) 1493/1999 on the common organization of the wine market, by-products coming from the winery industry must be sent to alcohol-distilleries to generate exhausted grape marc and vinasses. With an adequate composting treatment, these wastes can be applied to soils as a source of nutrients and organic matter. A three-year field experiment (2011, 2012 and 2013) was carried out in Ciudad Real (central Spain) to study the effects of wine-distillery waste compost application in a melon crop (Cucumis melo L.). Melon crop has been traditionally cultivated in this area with high inputs of water and fertilizers, but no antecedents of application of winery wastes are known. In a randomized complete block design, four treatments were compared: three compost doses consisted of 6.7 (D1), 13.3 (D2) and 20 t compost ha-1 (D3), and a control treatment without compost addition (D0). The soil was a shallow sandy-loam (Petrocalcic Palexeralfs) with a depth of 0.60 m and a discontinuous petrocalcic horizon between 0.60 and 0.70 m, slightly basic (pH 8.4), poor in organic matter (0.24%), rich in potassium (410 ppm) and with a medium level of phosphorus (22.1 ppm). During each growing period four harvests were carried out and total and marketable yield (fruits weighting <1 kg or visually rotten were not considered), fruit average weight and fruit number per plant were determined. At the end of the crop cycle, four plants per treatment were sampled and the nutrient content (N, P and K) was determined. Soil samplings (0-30 cm depth) were carried before the application of compost and at the end of each growing season and available N and P, as well as exchangeable K content were analyzed. With this information, an integrated analysis was carried out with the aim to evaluate the suitability of this compost as organic amendment.

Examining wheat yield sensitivity to temperature and precipitation changes for a large ensemble of crop models using impact response surfaces

Impact response surfaces (IRSs) depict the response of an impact variable to changes in two explanatory variables as a plotted surface. Here, IRSs of spring and winter wheat yields were constructed from a 25-member ensemble of process-based crop simulation models. Twenty-one models were calibrated by different groups using a common set of calibration data, with calibrations applied independently to the same models in three cases. The sensitivity of modelled yield to changes in temperature and precipitation was tested by systematically modifying values of 1981-2010 baseline weather data to span the range of 19 changes projected for the late 21st century at three locations in Europe.

A simple regional-scale model for forecasting sorghum yield across North-Eastern Australia

Sorghum is the main dryland summer crop in NE Australia and a number of agricultural businesses would benefit from an ability to forecast production likelihood at regional scale. In this study we sought to develop a simple agro-climatic modelling approach for predicting shire (statistical local area) sorghum yield. Actual shire yield data, available for the period 1983-1997 from the Australian Bureau of Statistics, were used to train the model. Shire yield was related to a water stress index (SI) that was derived from the agro-climatic model. The model involved a simple fallow and crop water balance that was driven by climate data available at recording stations within each shire. Parameters defining the soil water holding capacity, maximum number of sowings (MXNS) in any year, planting rainfall requirement, and critical period for stress during the crop cycle were optimised as part of the model fitting procedure. Cross-validated correlations (CVR) ranged from 0.5 to 0.9 at shire scale. When aggregated to regional and national scales, 78-84% of the annual variation in sorghum yield was explained. The model was used to examine trends in sorghum productivity and the approach to using it in an operational forecasting system was outlined. (c) 2005 Elsevier B.V. All rights reserved.

Validation of the Deardorff model for estimating energy balance components for a sugarcane crop

The quantification of the available energy in the environment is important because it determines photosynthesis, evapotranspiration and, therefore, the final yield of crops. Instruments for measuring the energy balance are costly and indirect estimation alternatives are desirable. This study assessed the Deardorff's model performance during a cycle of a sugarcane crop in Piracicaba, State of São Paulo, Brazil, in comparison to the aerodynamic method. This mechanistic model simulates the energy fluxes (sensible, latent heat and net radiation) at three levels (atmosphere, canopy and soil) using only air temperature, relative humidity and wind speed measured at a reference level above the canopy, crop leaf area index, and some pre-calibrated parameters (canopy albedo, soil emissivity, atmospheric transmissivity and hydrological characteristics of the soil). The analysis was made for different time scales, insolation conditions and seasons (spring, summer and autumn). Analyzing all data of 15 minute intervals, the model presented good performance for net radiation simulation in different insolations and seasons. The latent heat flux in the atmosphere and the sensible heat flux in the atmosphere did not present differences in comparison to data from the aerodynamic method during the autumn. The sensible heat flux in the soil was poorly simulated by the model due to the poor performance of the soil water balance method. The Deardorff's model improved in general the flux simulations in comparison to the aerodynamic method when more insolation was available in the environment.

Using Bayesian networks with rule extraction to infer the risk of weed infestation in a corn-crop

This paper describes the modeling of a weed infestation risk inference system that implements a collaborative inference scheme based on rules extracted from two Bayesian network classifiers. The first Bayesian classifier infers a categorical variable value for the weed-crop competitiveness using as input categorical variables for the total density of weeds and corresponding proportions of narrow and broad-leaved weeds. The inferred categorical variable values for the weed-crop competitiveness along with three other categorical variables extracted from estimated maps for the weed seed production and weed coverage are then used as input for a second Bayesian network classifier to infer categorical variables values for the risk of infestation. Weed biomass and yield loss data samples are used to learn the probability relationship among the nodes of the first and second Bayesian classifiers in a supervised fashion, respectively. For comparison purposes, two types of Bayesian network structures are considered, namely an expert-based Bayesian classifier and a naive Bayes classifier. The inference system focused on the knowledge interpretation by translating a Bayesian classifier into a set of classification rules. The results obtained for the risk inference in a corn-crop field are presented and discussed. (C) 2009 Elsevier Ltd. All rights reserved.

The impact of El Nino Southern Oscillation phases on off-season maize yield for a subtropical region of Brazil

In recent years, maize has become one of the main alternative crops for the autumn winter growing season in the central-western and southeastern regions of Brazil. However, water deficits, sub-optimal temperatures and low solar radiation levels are common problems that are experienced during this growing season by local farmers. One methodology to assess the impact of variable weather conditions on crop production is the use of crop simulation models. The goal of this study was to evaluate the effect of climate variability on maize yield for a subtropical region of Brazil. Specific objectives for this study were (1) to analyse the effect of El Nino Southern Oscillation (ENSO) on precipitation and air temperature for four locations in the state of Sao Paulo and (2) to analyse the impact of ENSO on maize grown off-season for the same four locations using a crop simulation model. For each site, historical weather data were categorised as belonging to one of three phases of ENSO: El Nino (warm sea surface temperature anomalies in the Pacific), La Nina (cool sea surface temperature anomalies) or neutral, based on an index derived from observed sea surface temperature anomalies. During El Nino, there is a tendency for an increase in the rainfall amount during May for the four selected locations, and also during April, mainly in three of the locations, resulting in an increase in simulated maize yield planted between February 15 and March 15. In general, there was a decrease in the simulated yield for maize grown off-season during neutral years. This study showed how a crop model can be used to assess the impact of climate variability on the yield of maize grown off-season in a subtropical region of Brazil. The outcomes of this study can be very useful for both policy makers and local farmers for agricultural planning and decision making. Copyright (C) 2009 Royal Meteorological Society

Yield loss caused by huanglongbing in different sweet orange cultivars in So Paulo, Brazil

Citrus huanglongbing (HLB) reduces an affected orchard`s economic life. This work aimed to characterize yield loss due to HLB for different sweet orange cultivars and determine the relationship between disease severity and yield. Disease severity and yield were assessed on 949 individual trees distributed in 11 different blocks from sweet orange cultivars Hamlin, Westin, Pera and Valencia. In each block, plants showing a range of HLB severity levels and asymptomatic plants were selected. Total yield (weight of harvested fruit), mean weight of asymptomatic and symptomatic fruit, relative yield (symptomatic tree yield/mean yield of asymptomatic trees from the same block) and relative number of fruits (fruit number from symptomatic tree/mean number of fruits from asymptomatic trees from the same block) were determined. The weight of symptomatic fruit was lower than the weight of asymptomatic fruit, but the weights of asymptomatic and symptomatic fruit were not correlated with disease severity, indicating that the effects of HLB were restricted to symptomatic branches. The relationship of the relative yield with HLB severity can be satisfactorily described by a negative exponential model. The rates of yield decrease as a function of disease severity were similar for all assessed cultivars. A relative yield (up to 19%) was observed even for trees where disease severity was 100%. The strong linear relationship between relative number of fruits per tree and the relative yield per tree suggested that the yield reduction was due primarily to early fruit drop or lack of fruit set on affected branches.

Analysis of genomic and functional RFLP derived markers associated with sucrose content, fiber and yield QTLs in a sugarcane (Saccharum spp.) commercial cross

Expressed sequence tags derived markers have a great potential to be used in functional map construction and QTL tagging. In the present work, sugarcane genomic probes and expressed sequence tags having homology to genes, mostly involved in carbohydrate metabolism were used in RFLP assays to identify putative QTLs as well as their epistatic interactions for fiber content, cane yield, pol and tones of sugar per hectare, at two crop cycles in a progeny derived from a bi-parental cross of sugarcane elite materials. A hundred and twenty marker trait associations were found, of which 26 at both crop cycle and 32 only at first ratoon cane. A sucrose synthase derived marker was associated with a putative QTL having a high negative effect on cane yield and also with a QTL having a positive effect on Pol at both crop cycles. Fifty digenic epistatic marker interactions were identified for the four traits evaluated. Of these, only two were observed at both crop cycles.

Water use and crop coefficient for hybrid DKB 390

Water use and crop coefficient for hybrid DKB 390. This work aims to characterize the water use of maize hybrid DKB 390 under suitable conditions of irrigation for both sufficient and below-optimal situations of nitrogen supply. Crop coefficient values for different stages are also presented as a result, in order to provide the basis for crop water budget and management throughout the cycle. A field experiment was carried Out during the main season, in which biomass, soil moisture, leaf area, climate data and light transmittance were evaluated. These have allowed deriving water balance, use and efficiency. The mentioned genotype requires around 600 nun for high yield targets, being less efficient when led under below-optimal nitrogen fertilization.

Does maintaining green leaf area in sorghum improve yield under drought? I. Leaf growth and senescence

Production of sorghum [Sorghum bicolor (L.) Moench], an important cereal crop in semiarid regions of the world, is often limited by drought. When water is limiting during the grain-filling period, hybrids possessing the stay-green trait maintain more photosynthetically active leaves than hybrids not possessing this trait. To improve yield under drought, knowledge of the extent of genetic variation in green leaf area retention is required. Field studies were undertaken in north-eastern Australia on a cracking and self-mulching gray clay to determine the effects of water regime and hybrid on the components of green leaf area at maturity (GLAM). Nine hybrids varying in stay-green were grown under a fully irrigated control, postflowering water deficit, and terminal (pre- and postflowering) water deficit. Water deficit reduced GLAM by 67% in the terminal drought treatment compared with the fully irrigated control. Under terminal water deficit, hybrids possessing the B35 and KS19 sources of stay-green retained more GLAM (1260 cm(2) plant(-1)) compared with intermediate (780 cm(2) plant(-1)) and senescent (670 cm(2) plant(-1)) hybrids. RQL12 hybrids (KS19 source of stay-green) displayed delayed onset and reduced rate of senescence; A35 hybrids displayed only delayed onset. Visual rating of green leaf retention was highly correlated with measured GLAM, although this procedure is constrained by an inability to distinguish among the functional mechanisms determining the phenotype. Linking functional rather than phenotypic differences to molecular markers may improve the efficiency of selecting for traits such as stay-green.