Farm and socio-economic characteristics of smallholder milk producers and their influence on technology adoption in Central Mexico

In order to identify the factors influencing adoption of technologies promoted by government to small-scale dairy farmers in the highlands of central Mexico, a field survey was conducted. A total of 115 farmers were grouped through cluster analysis (CA) and divided into three wealth status categories (high, medium and low) using wealth ranking. Chi-square analysis was used to examine the association of wealth status with technology adoption. Four groups of farms were differentiated in terms of farms’ dimensions, farmers’ education, sources of incomes, wealth status, management of herd, monetary support by government and technological availability. Statistical differences (p < 0.05) were observed in the milk yield per herd per year among groups. Government organizations (GO) participated little in the promotion of the 17 technologies identified, six of which focused on crop or forage production and 11 of which were related to animal husbandry. Relatives and other farmers played an important role in knowledge diffusion and technology adoption. Although wealth status had a significant association (p < 0.05) with adoption, other factors including importance of the technology to farmers, usefulness and productive benefits of innovations together with farmers’ knowledge of them, were important. It is concluded that the analysis of the information per group and wealth status was useful to identify suitable crop or forage related and animal husbandry technologies per group and wealth status of farmers. Therefore the characterizations of farmers could provide a useful starting point for the design and delivery of more appropriate and effective extension.

Evaluation of different foliar fertilizers on the crop production of sugarcane

Influence of different foliar fertilizers (phosphite, micronutrients, biostimulant, phosphite + micronutrients, phosphite + biostimulant, micronutrients + biostimulant and phosphite + micronutrients + biostimulant) on yield of sugarcane was evaluated after fertilization at 30, 90 and 150 days after harvesting two-year-old sugarcane. The experiment was carried out in a commercial crop employing a randomized block design in four replicates. Higher stalk masses were observed for fertilization at 30 days after harvest, and the higher content of sucrose, total recoverable sugar and Brix degrees were observed for sugarcane fertilized after 150 days. Statistical analysis (Duncan's test) revealed no significant variation (P & 0.05) in Brix degree, sucrose content and total recoverable sugar. For total recoverable sugar x stalk weight (the main payment type for sugarcane producers), the following sequence (time treatment, fertilizer composition) 30-days, micronutrient + biostimulant; 150-days, biostimulant; and 90-days, biostimulant increased 11%, 17%, and 21% the yield of sugarcane. © 2013 Copyright Taylor and Francis Group, LLC.

Seasons of desiccant application in the soybean crop: water content and productivity

The herbicides glyphosate and paraquat have been used by Brazilian soybean producers to obtain crop desiccation and to anticipate and uniformity at harvest. However, improper use of herbicides can to occasion problems in agronomic and physiologic characteristics of crop. This study aimed to evaluate the use of the glyphosate and paraquat herbicides as a desiccant for growing soybeans. The experiment was conducted in 2005/06 crop year, in an experimental design of randomized blocks with four replications. Treatments were arranged in two factorial design, 3x3x5x2 and 3x2x5x2: two desiccants (glyphosate and paraquat) and control (without drying), three and two growth stages (R6, R7 and R8) and (R7 and R8) for varieties MSOY 6101 of superprecocious cycle, and MG / BR 46 (Conquista) of precocious cycle, respectively, five sampling times (2, 4, 6, 8 and 10 days after application) and two positions in the plants on the ground assessment (apex and base). Was evaluated for seed Production, mass and water content of 100 seeds. Desiccants tested were effective in reducing the water content of seeds, without affecting productivity and mass of 100 seeds.

Fusarium species responsible for mycotoxin production in wheat crop: involvement in food safety

Fusarium Head Blight (FHB) is a worldwide cereal disease responsible of significant yield reduction, inferior grain quality, and mycotoxin accumulation. Fusarium graminearum and F. culmorum are the prevalent causal agents. FHB has been endemic in Italy since 1995, while there are no records about its presence in Syria. Forty-eight and forty-six wheat kernel samples were collected from different localities and analyzed for fungal presence and mycotoxin contamination. Fusarium strains were identified morphologically but the molecular confirmation was performed only for some species. Further differentiation of the chemotypes for trichothecene synthesis by F. graminearum and F. culmorum strains was conducted by PCR assays. Fusarium spp. were present in 62.5% of Syrian samples. 3Acetyl-Deoxynivalenol and nivalenol chemotypes were found in F. culmorum whilst all F. graminearum strains belonged to NIV chemotype. Italian samples were infected with Fusarium spp for 67.4%. 15Ac-DON was the prevalent chemotype in F. graminearum, while 3Ac-DON chemotype was detected in F. culmorum. The 60 Syrian Fusarium strains tested for mycotoxin production by HPLC-MS/MS have shown the prevalence of zearalenone while the emerging mycotoxins were almost absent. The analysis of the different Syrian and Italian samples of wheat kernels for their mycotoxin content showed that Syrian kernels were mainly contaminated with storage mycotoxins, aflatoxins and ochratoxin whilst Italian grains with mainly Fusarium mycotoxins. The aggressiveness of several Syrian F. culmorum isolates was estimated using three different assays: floret inoculation in growth chamber, ear inoculation in the field and a validated new Petri-dish test. The study of the behaviour of different Syrian wheat cultivars, grown under different conditions, has revealed that Jory is a FHB Syrian tolerant cultivar. This is the first study in Syria on Fusarium spp. associated to FHB, Fusarium mycotoxin producers and grain quality.

Conservation Reserve Program to Row Crop Demonstration

The demonstration project was designed to examine one way of preparing Conservation Reserve Program (CRP) land for row crop production. Many producers have successfully converted CRP land for this purpose; additionally, there was an opportunity for the research farm to gain experience in this area. The goal of the project was to document one way of going through the process.

Economic efficiency of smallholder maize producers in Western Kenya:a DEA meta-frontier analysis

Maize is the main staple food for most Kenyan households, and it predominates where smallholder, as well as large-scale, farming takes place. In the sugarcane growing areas of Western Kenya, there is pressure on farmers on whether to grow food crops, or grow sugarcane, which is the main cash crop. Further, with small and diminishing land sizes, the question of productivity and efficiency, both for cash and food crops is of great importance. This paper, therefore, uses a two-step estimation technique (DEA meta-frontier and Tobit Regression) to highlight the inefficiencies in maize cultivation, and their causes in Western Kenya.

Climate change adaptation strategies of maize producers of the Central Rift Valley of Ethiopia

The impacts of climate change are considered to be strong in countries located in tropical Africa that depend on agriculture for their food, income and livelihood. Therefore, a better understanding of the local dimensions of adaptation strategies is essential to develop appropriate measures that will mitigate adverse consequences. Hence, this study was conducted to identify the most commonly used adaptation strategies that farm households practice among a set of options to withstand the effects of climate change and to identify factors that affect the choice of climate change adaptation strategies in the Central Rift Valley of Ethiopia. To address this objective, Multivariate Probit model was used. The results of the model indicated that the likelihood of households to adapt improved varieties of crops, adjust planting date, crop diversification and soil conservation practices were 58.73%, 57.72%, 35.61% and 41.15%, respectively. The Simulated Maximum Likelihood estimation of the Multivariate Probit model results suggested that there was positive and significant interdependence between household decisions to adapt crop diversification and using improved varieties of crops; and between adjusting planting date and using improved varieties of crops. The results also showed that there was a negative and significant relationship between household decisions to adapt crop diversification and soil conservation practices. The paper also recommended household, socioeconomic, institutional and plot characteristics that facilitate and impede the probability of choosing those adaptation strategies.

The Iowa Grain Flow Survey: Where and How Iowa Grain Producers and Country Elevators Shipped Corn and Soybeans During September 1, 1999 - August 31, 2000, 2001

In September 1996, a grain flow survey consisting of two parts was completed and published. One part was a farm-to-market survey from a sample of Iowa grain producers, and the second was a survey of all Iowa country elevators. An updated survey for the crop year September 1, 1999 -August 31, 2000, was initiated in September 2000. The results of the two updated surveys are presented in this report. The purpose of the surveys is to estimate the amount of Iowa corn and soybeans that are shipped from each crop reporting district to each major market. Copies of the two questionnaires are presented in the appendices.

Federal Crop Insurance Program Expands in 2016 and 2017 to Cover More Organic Crops

Organic agriculture represents one of the fastest growing segments of U.S. agriculture (USDA-RMA). With this in mind, the USDA’s Risk Management Agency (RMA) continues to expand crop insurance options for organic growers. In 2016 and 2017, organic producers in Maryland will see additional crops with organic crop insurance options. Increasing crop insurance options will allow this segment of producers new opportunities to manage their risks.

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.

Wavelet analysis of MODIS time series to detect expansion and intensification of row-crop agriculture in Brazil

Since 2000, the southwestern Brazilian Amazon has undergone a rapid transformation from natural vegetation and pastures to row-crop agricultural with the potential to affect regional biogeochemistry. The goals of this research are to assess wavelet algorithms applied to MODIS time series to determine expansion of row-crops and intensification of the number of crops grown. MODIS provides data from February 2000 to present, a period of agricultural expansion and intensification in the southwestern Brazilian Amazon. We have selected a study area near Comodoro, Mato Grosso because of the rapid growth of row-crop agriculture and availability of ground truth data of agricultural land-use history. We used a 90% power wavelet transform to create a wavelet-smoothed time series for five years of MODIS EVI data. From this wavelet-smoothed time series we determine characteristic phenology of single and double crops. We estimate that over 3200 km(2) were converted from native vegetation and pasture to row-crop agriculture from 2000 to 2005 in our study area encompassing 40,000 km(2). We observe an increase of 2000 km(2) of agricultural intensification, where areas of single crops were converted to double crops during the study period. (C) 2007 Elsevier Inc. All rights reserved.

Economic viability of doses and split-applications of nitrogen fertilization in corn crop in a eutrophic Red Latosol

Nitrogen is the nutrient that is most absorbed by the corn crop, with the most complex management, and has the highest share on the cost of corn production. The objective of this work was to evaluate the economic viability of different rates and split-applications of nitrogen fertilization, as such as urea, in the corn crop in a eutrophic Red Latosol (Oxisol). The study was carried out in the Experimental Station of the Regional Pole of the Sao Paulo Northwest Agribusiness Development (APTA), in Votuporanga, State of Sao Paulo, Brazil. The experimental design was randomized complete blocks with nine treatments and four replications, consisting of five N rates: 0, 55, 95, 135 and 175 kg ha(-1), 15 kg ha-l applied in the seeding and the remainder in top dressing: 40 and 80 kg ha(-1) N at forty days after seeding (DAS), or 1/2 + 1/2 at 20 and 40 DAS; 120 kg ha-1 N split in 1/2 + 1/2 or 1/3 + 1/3 + 1/3 at 20, 40 or 60 DAS; 160 kg ha(-1) N split in 1/4 + 3/8 + 3/8 or 114 + 1/4 + 1/4 + 1/4 at 20, 40, 60 and 80 DAS. The application of 135 kg ha-l of N split in three times provided the best benefit/cost ratio. The non-application of N provided the lowest economic return, proving to be unviable.

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.

Leaching of nutrients from a sugarcane crop growing on an Ultisol in Brazil

Leaching is disadvantageous, both for economical and environmental reasons since it may decrease the ecosystem productivity and may also contribute to the contamination of surface and ground water. The objective of this paper was to quantify the loss of nitrogen and sulfur by leaching, at the depth of 0.9 m, in an Ultisol in Sao Paulo State (Brazil) with high permeability, Cultivated with sugarcane during the agricultural cycle of crop plant. The following ions were evaluated: nitrite, nitrate, ammonium, and sulfate. Calcium, magnesium, potassium, and phosphate were also evaluated at the same depth. The sugarcane was planted and fertilized in the furrows with 120 log ha(-1) of N-urea. In order to find out the fate of N-fertilizer, four microplots with (15)N-enriched fertilizer were installed. Input and output of the considered ions at the depth of 0.9 m were quantified from the flux density of water and the concentration of the elements in the soil solution at this soil depth: tensiometers, soil water retention curve and soil solution extractors were used for this quantification. The internal drainage was 205 mm of water, with a total loss of 18 kg ha(-1) of N and 10 kg ha(-1) of S. The percentage of N in the soil solution derived from the fertilizer (%NSSDF) was 1.34, resulting in only 25 g ha(-1) of N fertilizer loss by leaching during all agricultural cycle. Under the experimental conditions of this crop plant, that is, high demand of nutrients and high incorporation of crop residues, the leached N represented 15% of applied N and S leaching were not considerable; the higher amount of leached N was native nitrogen and a minor quantity from N fertilizer; and the leached amount of Ca, Mg, K and P did not exceed the applications performed in the crop by lime and fertilization. (C) 2009 Elsevier B.V. All rights reserved.

Bayesian ratemaking procedure of crop insurance contracts with skewed distribution

Over the years, crop insurance programs became the focus of agricultural policy in the USA, Spain, Mexico, and more recently in Brazil. Given the increasing interest in insurance, accurate calculation of the premium rate is of great importance. We address the crop-yield distribution issue and its implications in pricing an insurance contract considering the dynamic structure of the data and incorporating the spatial correlation in the Hierarchical Bayesian framework. Results show that empirical (insurers) rates are higher in low risk areas and lower in high risk areas. Such methodological improvement is primarily important in situations of limited data.