Variabilidade espacial e correlações entre atributos de solo e produtividade na agricultura de precisão

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Estimativa de densidade amostral para elaboração de mapas de produtividade

Yield mapping represents the spatial variability concerning the features of a productive area and allows intervening on the next year production, for example, on a site-specific input application. The trial aimed at verifying the influence of a sampling density and the type of interpolator on yield mapping precision to be produced by a manual sampling of grains. This solution is usually adopted when a combine with yield monitor can not be used. An yield map was developed using data obtained from a combine equipped with yield monitor during corn harvesting. From this map, 84 sample grids were established and through three interpolators: inverse of square distance, inverse of distance and ordinary kriging, 252 yield maps were created. Then they were compared with the original one using the coefficient of relative deviation (CRD) and the kappa index. The loss regarding yield mapping information increased as the sampling density decreased. Besides, it was also dependent on the interpolation method used. A multiple regression model was adjusted to the variable CRD, according to the following variables: spatial variability index and sampling density. This model aimed at aiding the farmer to define the sampling density, thus, allowing to obtain the manual yield mapping, during eventual problems in the yield monitor.

Modern viticulture in southern Europe: Vulnerabilities and strategies for adaptation to water scarcity

Water is now considered the most important but vulnerable resource in the Mediterranean region. Nev ertheless, irrigation expanded fast in the region (e.g. South Portugal and Spain) to mitigate environmental stress and to guarantee stable grape yield and quality. Sustainable wine production depends on sustain able water use in the wine’s supply chain, from the vine to the bottle. Better understanding of grapevine stress physiology (e.g. water relations, temperature regulation, water use efficiency), more robust crop monitoring/phenotyping and implementation of best water management practices will help to mitigate climate effects and will enable significant water savings in the vineyard and winery. In this paper, we focused on the major vulnerabilities and opportunities of South European Mediterranean viticulture (e.g. in Portugal and Spain) and present a multi-level strategy (from plant to the consumer) to overcome region’s weaknesses and support strategies for adaptation to water scarcity, promote sustainable water use and minimize the environmental impact of the sector.

Modern viticulture in southern Europe: vulnerabilities and strategies for adaptation to water scarcity

Water is now considered the most important but vulnerable resource in the Mediterranean region. Nevertheless, irrigation expanded fast in the region (e.g. South Portugal and Spain) to mitigate environmental stress and to guarantee stable grape yield and quality. Sustainable wine production depends on sustainable water use in the wine’s supply chain, from the vine to the bottle. Better understanding of grapevine stress physiology (e.g. water relations, temperature regulation, water use efficiency), more robust crop monitoring/phenotyping and implementation of best water management practices will help to mitigate climate effects and will enable significant water savings in the vineyard and winery. In this paper, we focused on the major vulnerabilities and opportunities of South European Mediterranean viticulture (e.g. in Portugal and Spain) and present a multi-level strategy (from plant to the consumer) to overcome region’s weaknesses and support strategies for adaptation to water scarcity, promote sustainable water use and minimize the environmental impact of the sector.

WINE GRAPE QUALITY OF GRAPEVINES GROWN IN THE CERRADO ECOREGION OF BRAZIL

Aims: Geographical indication plays an important role in the improvement of wine quality. In this context, the search for new grape growing areas has been constant. The Sao Francisco River Valley in the cerrado of Minas Gerais State (Brazil) has been pointed out in the Geoviticulture Multicriteria Climatic Classification System (MCC System) as a potentially winegrowing region, especially considering the autumn-winter period when night temperatures are favorable to grape ripening. In this work, we studied the maturation curves and fruit composition of four wine grape varieties (Syrah, Merlot, Cabernet-Sauvignon and Cabernet Franc) in two growing seasons in order to validate the state of Minas Gerais as a new winegrowing region in Brazil. Methods and results: Quality parameters (berry weight, pH, titratable acidity and total soluble solids) were measured weekly from veraison to harvest, and sugar, organic acid, anthocyanin and phenolic concentrations were determined in must and berry skins and seeds at harvest. Syrah berries showed the highest weight throughout maturation which contributed to higher yield (8.92 ton ha(-1)), followed closely by Merlot (8.07 ton ha(-1)). Bern, sugar concentrations were higher and malic acid levels were lower than the values usually observed in wine grapes harvested during summer in traditional winegrowing regions in Brazil. Cabernet Franc showed lower levels of anthocyanins and skin phenolics per kg berries and the highest values of seed phenolics, which were not affected by growing season. Conclusion: Weather conditions of the cerrado of Minas Gerais State in Brazil during winter allowed complete maturation of Cabernet-Sauvignon, Cabernet Franc, Merlot and Syrah cultivars as revealed by the satisfactory sugar, anthocyanin and skin phenolic accumulation. Significance and impact of the study: This study revealed the potential of the cerrado ecoregion in the northeast of Minas Gerais to become a new winemaking region in Brazil.

Biochemistry of grape berries: post-genomics approaches to uncover the effects of water deficits on ripening

Dissertation presented to obtain the Ph.D degree in Biochemistry, Plant Physiology

Valorization of grape pomace through hot compressed water extraction/hydrolysis

The world energy consumption is expected to increase strongly in coming years, because of the emerging economies. Biomass is the only renewable carbon resource that is abundant enough to be used as a source of energy Grape pomace is one of the most abundant agro-industrial residues in the world, being a good biomass resource. The aim of this work is the valorization of grape pomace from white grapes (WWGP) and from red grapes (RWGP), through the extraction of phenolic compounds with antioxidant activity, as well as through the extraction/hydrolysis of carbohydrates, using subcritical water, or hot compressed water (HCW). The main focus of this work is the optimization of the process for WWGP, while for RWGP only one set of parameters were tested. The temperatures used were 170, 190 and 210 °C for WWGP, and 180 °C for RWGP. The water flow rates were 5 and 10 mL/min, and the pressure was always kept at 100 bar. Before performing HCW assays, both residues were characterized, revealing that WWGP is very rich in free sugars (around 40%) essentially glucose and fructose, while RWGP has higher contents of structural sugars, lignin, lipids and protein. For WWGP the best results were achieved at 210 °C and 10 mL/min: higher yield in water soluble compounds (69 wt.%), phenolics extraction (26.2 mg/g) and carbohydrates recovery (49.3 wt.% relative to the existing 57.8%). For RWGP the conditions were not optimized (180 °C and 5 mL/min), and the values of the yield in water soluble compounds (25 wt.%), phenolics extraction (19.5 mg/g) and carbohydrates recovery (11.4 wt.% relative to the existing 33.5%) were much lower. The antioxidant activity of the HCW extracts from each assay was determined, the best result being obtained for WWGP, namely for extracts obtained at 210 °C (EC50=20.8 μg/mL; EC50 = half maximum effective concentration; EC50 = 22.1 μg/mL for RWGP, at 180 ºC).

Regions of rationality: Maps for bounded agents

An important problem in descriptive and prescriptive research in decision making is to identify regions of rationality, i.e., the areas for which heuristics are and are not effective. To map the contours of such regions, we derive probabilities that heuristics identify the best of m alternatives (m > 2) characterized by k attributes or cues (k > 1). The heuristics include a single variable (lexicographic), variations of elimination-by-aspects, equal weighting, hybrids of the preceding, and models exploiting dominance. We use twenty simulated and four empirical datasets for illustration. We further provide an overview by regressing heuristic performance on factors characterizing environments. Overall, sensible heuristics generally yield similar choices in many environments. However, selection of the appropriate heuristic can be important in some regions (e.g., if there is low inter-correlation among attributes/cues). Since our work assumes a hit or miss decision criterion, we conclude by outlining extensions for exploring the effects of different loss functions.

Local influence for spatial analysis of soil physical properties and soybean yield using student's t-distribution

The modeling and estimation of the parameters that define the spatial dependence structure of a regionalized variable by geostatistical methods are fundamental, since these parameters, underlying the kriging of unsampled points, allow the construction of thematic maps. One or more atypical observations in the sample data can affect the estimation of these parameters. Thus, the assessment of the combined influence of these observations by the analysis of Local Influence is essential. The purpose of this paper was to propose local influence analysis methods for the regionalized variable, given that it has n-variate Student's t-distribution, and compare it with the analysis of local influence when the same regionalized variable has n-variate normal distribution. These local influence analysis methods were applied to soil physical properties and soybean yield data of an experiment carried out in a 56.68 ha commercial field in western Paraná, Brazil. Results showed that influential values are efficiently determined with n-variate Student's t-distribution.

Spatial relationships between soil attributes and corn yield in no-tillage system

Soil properties play an important role in spatial variability of crop yield. However, a low spatial correlation has generally been observed between maps of crop yield and of soil properties. The objectives of the present investigation were to assess the spatial pattern variability of soil properties and of corn yield at the same sampling intensity, and evaluate its cause-and-effect relationships. The experimental site was structured in a grid of 100 referenced points, spaced at 10 m intervals along four parallel 250 m long rows spaced 4.5 m apart. Thus, points formed a rectangle containing four columns and 25 rows. Therefore, each sampling cell encompassed an area of 45 m² and consisted of five 10 m long crop rows, in which the referenced points represented the center. Samples were taken from the layers 0-0.1 m and 0.1-0.2 m. Soil physical and chemical properties were evaluated. Statistical analyses consisted of data description and geostatistics. The spatial dependence of corn yield and soil properties was confirmed. The hypothesis of this study was confirmed, i.e., when sampling the soil to determine the values of soil characteristics at similar to sampling intensity as for crop yield assessments, correlations between the spatial distribution of soil characteristics and crop yield were observed. The spatial distribution pattern of soil properties explained 65 % of the spatial distribution pattern of corn yield. The spatial distribution pattern of clay content and percentage of soil base saturation explained most of the spatial distribution pattern of corn yield.

Wheat yield and physical properties of a brown latosol under no-tillage in south-central Paraná

Soil management influences the chemical and physical properties of soil. Chemical conditions have been thoroughly studied, while the role of soil physical conditions regarding crop yield has been neglected. This study aimed to analyze the wheat yield and its relationship with physical properties of an Oxisol under no-tillage (NT). The study was carried out between 2010 and 2011, in Reserva do Iguaçu, State of Paraná, Brazil, on the Campo Bonito farm, after 25 years of NT management. Based on harvest maps of barley (2006), wheat (2007) and maize (2009) of a plot (150 ha), zones with higher and lower yield potential (Z1 and Z2, respectively) were identified. Sampling grids with 16 units (50 x 50 m) and three sampling points per unit were established. The wheat grain yield (GY) and water infiltration capacity (WIC) were evaluated in 2010. Soil samples with disturbed and undisturbed structure were collected from the 0.00-0.10 and 0.10-0.20 m layers. The former were used to determine soil organic carbon (Corg) levels and the latter to determine soil bulk density (BD), total porosity (TP), macroporosity (Mac), and microporosity (Mic). Soil penetration resistance (PR) and water content (SWC) were also evaluated. The wheat GY of the whole plot was close to the regional average and the yield between the zones differed significantly, i.e. 22 % higher in Z1 than in Z2. No significant variation in Mic was observed between zones, but Z1 had higher Corg levels, SWC, TP and Mac and lower BD than Z2 in both soil layers, as well as a lower PR than Z2 in the 0.00-0.10 m layer. Therefore, soil physical conditions were more restrictive in Z2, in agreement with wheat yield and zone yield potential defined a priori, based on the harvest maps. Soil WIC in Z1 was significantly higher (30 %) than in Z2, in agreement with the results of TP and Mac which were also higher in Z1 in both soil layers. The correlation analysis of data of the two layers showed a positive relationship between wheat GY and the soil properties TP, SWC and WIC.

Sugarcane trash management assessed by the interaction of yield with soil properties

Currently, sugarcane plays an important global role, particularly with a view to alternative energy sources. Thus, in a sugarcane field of the mill Vale do Paraná S/A Álcool e Açúcar, Rubineia, São Paulo State, managed under two green cane harvest systems (cane trash left on and cane trash removed from the soil), Pearson and spatial correlations between the sugarcane yield (variety RB855035 in the third cut) and soil physical and chemical properties were studied to identify the property best correlated with stalk yield and the best harvest method. For this purpose, two geostatistical grids (121 sampling points on 1.30 ha) were installed on a eutrophic Red Argisol (homogeneous slope of 0.065 m m-1), in 2011, to determine the properties: stalk yield and sugarcane plant population, and soil resistance to penetration, gravimetric moisture, bulk density, and carbon stock, in the layers 0-0.20 and 0.20-0.40 m. The data were analyzed by descriptive, linear correlation and geostatistical analysis. In both treatments, the property stand density was best correlated with sugarcane yield (r = 0.725 in the trash mulching treatment - TM and r = 0.769 in the trash removal treatment - TR). However, in relation to the soil properties, bulk density (0-0.20 m) was best correlated (r = 0.305 in TM, r = 0.211 in TR). Similarly, from the spatial point of view, stand density was the property that best explained the sugarcane yield. However, in the TM treatment the density (0.20-0.40 m) was the only soil property spatially correlated with stalk yield. The carbon stock in the soil of the TM was 11.5 % higher than in the TR treatment. Results of the TM treatment were best, also with regard to soil management and conservation.

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.

A mechanistic approach to methylene blue sorption on two vegetable wastes: Cork bark and grape stalks

Two vegetable wastes, cork bark and grape stalks, were investigated for the removal of methylene blue from aqueous solution. The effects of contact time, dye concentration, pH, and temperature on sorption were studied relative to adsorption on a commercially-activated carbon. The highest adsorption yield was obtained within the pH range 5 to 10 for grape stalks and 7 to 10 for cork bark. The sorption kinetics of dye onto activated carbon and grape stalks was very fast. Kinetics data were fitted to the pseudo-first and second order kinetic equations, and the values of the pseudo-second-order initial rate constants were found to be 1.69 mg g-1 min-1 for activated carbon, 2.24 mg g-1 min-1 for grape stalks, and 0.90 mg g-1 min-1 for cork bark. Langmuir maximum sorption capacities for activated carbon, grape stalks, and cork bark for methylene blue estimated by the Orthogonal Distance Regression method (ODR) were 157.5 mg g-1, 105.6 mg g-1, and 30.52 mg g-1, respectively. FTIR spectra indicated that carboxylic groups and lignin play a significant role in the sorption of methylene blue. Electrostatic forces, n-p interactions, cation-p, and p-p stacking interactions contribute to methylene blue sorption onto grape stalks and cork bark. Grape stalks can be considered an efficient biosorbent and as a viable alternative to activated carbon and ion-exchange resins for the removal of methylene blue

Spatial variability of yield and other parameters associated with pear trees

In the last few years, precision agriculture has become commonly used with many crops, particularly cereals, and there is also interest in precision horticulture. Pear is a seasonal fruit and well appreciated by Brazilian people, although it is mostly imported. Brazilian farmers are nowadays trying to increase pear production. Thus, this research aimed at mapping the yield of pear trees in order to study the spatial variability of yield as well as its comparison with spatial variability of soil and plant attributes. The experimental field had 146 pear trees, variety 'Pêra d'água', distributed on a 1.24 ha. Four harvests were performed according to the fruit ripening and from each tree; only the ripe fruits were harvested. In each harvest, all the fruits were weighed and the total yield was obtained based on the sum of each harvest. The soil attributes analyzed were P, K, Ca, Mg, pH in CaCl2, C, Cu, Zn, Fe, Mn and base saturation, and the plant attributes were fruit length, diameter and yield. Yield had low correlation with soil and plant attributes. An index of spatial variability was suggested in this study and helped in classifying levels of spatial dependence of the various soil and plant attributes: very low (fruit length); low (P, fruit diameter), medium (Mg, pH, Cu, Zn, Fe), high (Ca, K, base saturation and yield), and very high (Mn and C).