Avaliação de discos de corte de semeadora-adubadora em diferentes quantidades de cobertura vegetal

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Desempenho de discos de corte de semeadora-adubadora em diferentes quantidades de cobertura vegetal

The quality and efficiency in straw cutting are determinants in the sowing process, according to the occurrence of "tamp" and stops, the magnitude of the straw removal or even the known effects of the seed "envelopment" where the cutting mechanism can not cut the remaining straw. Thus, the objective of this study was to evaluate the performance of different mechanisms for straw cutting of a seeder individualized in different amounts of crop coverage artificially added in a clay soil. The experiment was conducted at Unesp – Sao Paulo State University in the Experimental Farm Lageado, belonging to the College of Agricultural Sciences - Unesp, Botucatu. The experimental design was split plot with four replications, with main plots consisting of five quantities of black oat straw, in area with no-tillage system and subplots of three opening furrows mechanisms, which are: plane disk (PD), corrugated disk (CD) and wavy disk (WD). The wavy disk provided greater rolling resistance, reducing the speed of the set (tractor and equipment). The plane cutting disk showed the highest values of mobilized soil area, deeper penetration into the soil, requiring lower values of vertical force and higher values of lateral force. Regarding the type of waste and doses used, they offered no resistance to cutting and there was no change in the horizontal force on straw.

Influence of the Premium Subsidy on Farmers’ Crop Insurance Coverage Decisions, April 2005

The Agricultural Risk Protection Act greatly increased the expected marginal net benefit of farmers buying high-coverage crop insurance policies by coupling premium subsidies to coverage level. This policy change, combined with cross-sectional variations in expected marginal net benefits of high-coverage policies, is used to estimate the role that premium subsidies play in farmers’ crop insurance decisions. We use county data for corn, soybeans, and wheat to estimate regression equations that are then used to obtain insight into two policy scenarios. We first estimate that eventual adoption of actuarially fair incremental premiums, combined with current coupled subsidies, would increase farmers’ purchase of high-coverage policies by almost 400 percent from 1998 levels across the three crops and two plans of insurance included in the analysis. We then estimate that a return to decoupled subsidies would decrease farmers’ high-coverage purchase decisions by an average of 36 percent.

Get a GRIP: Should Area Revenue Coverage Be Offered through the Farm Bill or as a Crop Insurance Program? 2007

The successful expansion of the U.S. crop insurance program has not eliminated ad hoc disaster assistance. An alternative currently being explored by members of Congress and others in preparation of the 2007 farm bill is to simply remove the “ad hoc” part of disaster assistance programs by creating a standing program that would automatically funnel aid to hard-hit regions and crops. One form such a program could take can be found in the area yield and area revenue insurance programs currently offered by the U.S. crop insurance program. The Group Risk Plan (GRP) and Group Risk Income Protection (GRIP) programs automatically trigger payments when county yields or revenues, respectively, fall below a producer-elected coverage level. The per-acre taxpayer costs of offering GRIP in Indiana, Illinois, and Iowa for corn and soybeans through the crop insurance program are estimated. These results are used to determine the amount of area revenue coverage that could be offered to farmers as part of a standing farm bill disaster program. Approximately 55% of taxpayer support for GRIP flows to the crop insurance industry. A significant portion of this support comes in the form of net underwriting gains. The expected rate of return on money put at risk by private crop insurance companies under the current Standard Reinsurance Agreement is approximately 100%. Taking this industry support and adding in the taxpayer support for GRIP that flows to producers would fund a county target revenue program at the 93% coverage level.

An image segmentation based on a genetic algorithm for determining soil coverage by crop residues

Determination of the soil coverage by crop residues after ploughing is a fundamental element of Conservation Agriculture. This paper presents the application of genetic algorithms employed during the fine tuning of the segmentation process of a digital image with the aim of automatically quantifying the residue coverage. In other words, the objective is to achieve a segmentation that would permit the discrimination of the texture of the residue so that the output of the segmentation process is a binary image in which residue zones are isolated from the rest. The RGB images used come from a sample of images in which sections of terrain were photographed with a conventional camera positioned in zenith orientation atop a tripod. The images were taken outdoors under uncontrolled lighting conditions. Up to 92% similarity was achieved between the images obtained by the segmentation process proposed in this paper and the templates made by an elaborate manual tracing process. In addition to the proposed segmentation procedure and the fine tuning procedure that was developed, a global quantification of the soil coverage by residues for the sampled area was achieved that differed by only 0.85% from the quantification obtained using template images. Moreover, the proposed method does not depend on the type of residue present in the image. The study was conducted at the experimental farm “El Encín” in Alcalá de Henares (Madrid, Spain).

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.

Analysis of classification algorithms for crop detection using LANDSAT 8 images

Remote sensing - the acquisition of information about an object or phenomenon without making physical contact with the object - is applied in a multitude of different areas, ranging from agriculture, forestry, cartography, hydrology, geology, meteorology, aerial traffic control, among many others. Regarding agriculture, an example of application of this information is regarding crop detection, to monitor existing crops easily and help in the region’s strategic planning. In any of these areas, there is always an ongoing search for better methods that allow us to obtain better results. For over forty years, the Landsat program has utilized satellites to collect spectral information from Earth’s surface, creating a historical archive unmatched in quality, detail, coverage, and length. The most recent one was launched on February 11, 2013, having a number of improvements regarding its predecessors. This project aims to compare classification methods in Portugal’s Ribatejo region, specifically regarding crop detection. The state of the art algorithms will be used in this region and their performance will be analyzed.

Grasses and legumes as cover crop in no-tillage system in northeastern Pará Brazil

Studies to select one or more species of coverage plants adapted to Amazonian soil and climate conditions of the Amazon are a promising strategy for the improvement of environmental quality, establishing no-till agricultural systems, and thereby reducing the impacts of monoculture farming. The aim of this study was to assess the persistence time, half-life time, macronutrient content and accumulation, and C:N ratio of straw coverage in a Ultisol in northeastern Pará. Experimental design was randomized blocks with five treatments and five replicates. Plants were harvested after 105 days, growth and biomass production was quantified. After 84 days, soil coverage was 97, 85, 52, 50, and 15% for signalgrass (Brachiaria brizantha) (syn. Urochloa), dense crowngrass (Panicum purpurascens), jack bean (Canavalia ensiformes), pearl millet (Pennisetum americanum) and sunn hemp (Crotalaria juncea,), respectively. Signalgrass yielded the greatest dry matter production (9,696 kg ha-1). It also had high C:N ratio (38.4), long half-life (86.5 days) and a high persistence in the field. Jack bean also showed high dry matter production (8,950 kg ha-1), but it had low C:N ratio (17.4) and lower half-life time (39 days) than the grasses. These attributes indicate that signalgrass and jack bean have a high potential for use as cover plants in no-till agricultural systems in the State of Pará.

Soil water evaporation under densities of coverage with vegetable residue

This study was conducted at the Agronomic Institute of Paraná (IAPAR) in Londrina, State of Paraná (PR), Brazil (latitude 23º18'S, longitude 51º09'W and average altitude of 585 m). The local climate, according to the classification of Köeppen, is Cfa type, i.e., humid subtropical climate, with rain in all seasons and can occur dry seasons during the winter. It was determined soil evaporation (E) under different coverage densities with residue from the wheat crop. The treatments were installed in weighting lysimeters of 2.66 m² and 1.3 m deep, which allows to determine E by the mass difference with measuring precision of 0.1mm at one hour intervals. Treatments consisted of 0; 2.5; 5 and 10 t ha-1 of wheat crop residues, placed evenly over each lysimeter. In the first cycle (September 22nd to October 20th, 2008), the reduction of E, as compared to a bare soil, was 4; 15 and 24%, while in the second cycle (December 1st to 30th, 2008), the reduction was of 15; 22 and 25%, respectively, for the treatments of 2.5; 5 and 10 t ha-1.

Desiccation time of the spring sorghum as a predecessor crop for summer soybean and autumn bean in a no-tillage system

ABSTRACT Several authors have been questioned the desiccation interval between the coverage plants and sowing plants for the soybean crop. Therefore, this study aimed to evaluate the desiccation time of the spring sorghum as a predecessor crop for summer soybean and then for autumn bean, focusing on the straw formation for maintenance of the no-tillage system and to evaluate the yield of soybeans and beans grain, as well as analyzing the interference of sorghum straw in these cultures. The experiment was developed in the Teaching and Research Farm of FE/UNESP located in Ilha Solteira/SP where it was used an experimental design of randomized blocks with five treatments and six repetitions. The treatments consisted of five different intervals between sorghum desiccation and soybean sowing (being with D7 - Drying sorghum seven days before the soybean sowing; and successively for D14, D21, D28 and D35). In order to analyze the results, it was used the Tukey test for a 10% level of significance and the statistical program called Sisvar. The "Cober Crop" sorghum exerted influence on soybean yield but this effect was not lasting for the bean crop in succession to the soybeans.

Soil water evaporation under densities of coverage with vegetable residue

O presente estudo foi realizado no Instituto Agronômico do Paraná (IAPAR), em Londrina, Estado do Paraná (latitude de 23º18'S, longitude de 51º09'W e altitude média de 585 m). O clima local, segundo a classificação do Köppen, é do tipo Cfa, ou seja, subtropical úmido, com chuvas em todas as estações, podendo ocorrer secas no período de inverno. Determinou-se a evaporação (E) da água do solo sob diferentes densidades de cobertura com resíduo da cultura de trigo. Os tratamentos foram instalados em lisímetros de pesagem de 2,66 m² e 1,3 m de profundidade, que permitem determinar E por diferença de massa com precisão equivalente a 0,1 mm em intervalos de uma hora. Os tratamentos consistiram em 0; 2,5; 5 e 10 t ha-1 de resíduos da cultura do trigo, colocadas de forma homogênea em cada lisímetro. No primeiro ciclo (22/09 a 20/10/2008), a redução de E em relação ao solo descoberto foi de 4; 15 e 24%, enquanto no segundo ciclo (01/12 a 30/12/2008), a redução foi de 15; 22 e 25%, respectivamente, para os tratamentos 2,5; 5 e 10 t ha-1.

Effects of different soil tillage systems and coverages on soybean crop in the Botucatu Region in Brazil

Nowadays, agricultural practices should combine high yields with a sustainable use of resources. Different tillage practices and crop covers, if combined, may help to achieve both objectives. In this work, several traits of a soybean (Glycine max L. Merr) cultivar were studied under different conditions of tillage and previous soil coverages. The experiment was installed at Lageado Research Station, Botucatu county, SP, Brazil, on a Paleudult. It consisted of nine treatments (combining three systems of soil tillage and three cover crops) and 4 replicates, yielding 36 plots of a randomized block experimental design. The soil tillage systems considered were: (i) conventional tillage with two heavy harrowing and a levelling harrowing; (ii) chiseling, and (iii) no-tillage with chemical drying of vegetation. The three cover crops used were: black oat, sorghum and spontaneous vegetation. Analyzed variables were: plant height, initial and final plant densities, height of first pod insertion, weight of a thousand grains, number of pods per plant, number of grains per pod, and crop yield. No significant differences were observed for most of the analyzed variables; however, conventional tillage produced significantly heavier grains and a higher number of pods per plant. The selected covers were considered an excellent coverage prior to planting soybean in a crop rotation. The three tillage systems can be used for deployment of culture without compromising the development of soybean.

Percent cropland coverage for sub-Saharan Africa

The dataset contains a cropland percent coverage map for Africa created through the combination of five existing land cover products: GLC-2000, MODIS Land Cover, GlobCover, MODIS Crop Likelihood and AfriCover. A synergy map was created in which the products are ranked by experts, which reflects the likelihood or probability that a given pixel is cropland. The cropland map was calibrated with national and sub-national crop statistics using a novel approach. Preliminary validation of the map was undertaken. The resulting cropland map has an accuracy of 83%, which is higher than the accuracy of any of the individual maps. The cropland percent coverage map for Africa is available for overlay on Google Earth or for download at http://agriculture.geo-wiki.org.

A waypoint-based mission planner for a farmland coverage with an aerial robot - a precision farming tool

Remote sensing (RS) with aerial robots is becoming more usual in every day time in Precision Agriculture (PA) practices, do to their advantages over conventional methods. Usually, available commercial platforms providing off-the-shelf waypoint navigation are adopted to perform visual surveys over crop fields, with the purpose to acquire specific image samples. The way in which a waypoint list is computed and dispatched to the aerial robot when mapping non empty agricultural workspaces has not been yet discussed. In this paper we propose an offline mission planner approach that computes an efficient coverage path subject to some constraints by decomposing the environment approximately into cells. Therefore, the aim of this work is contributing with a feasible waypoints-based tool to support PA practices

Assessment of insurance coverage and claims in rainfall related risks in processing tomato in Western Spain

An extension of guarantees related to rainfall-related risks in the insurance of processing tomato crops has been accompanied with a large increase in claims in Western Spain, suggesting that damages may have been underestimated in previous years. A database was built by linking agricultural insurance records, meteorological data from local weather stations, and topographic data. The risk of rainfall-related damages in processing tomato in the Extremenian Guadiana river basin (W Spain) was studied using a logistic model. Risks during the growth of the crop and at harvesting were modelled separately. First, the risk related to rainfall was modelled as a function of meteorological, terrain and management variables. The resulting models were used to identify the variables responsible for rainfall-related damages, with a view to assess the potential impact of extending insurance coverage, and to develop an index to express the suitability of the cropping system for insurance. The analyses reveal that damages at different stages of crop development correspond to different hazards. The geographic dependence of the risk influences the scale at which the model might have validity, which together with the year dependency, the possibility of implementing index based insurances is questioned.