Use of farmer-prioritized vertisol management options for enhanced green gram and tomato production in central Kenya

Green grams (Phaseolus aures L.) and tomato (Solanum lycopersicum L) are widely grown in the vertisols of the Mwea Irrigation Scheme alongside the rice fields. Green grams can fix nitrogen (biological nitrogen fixation) and are grown for its highly nutritious and curative seeds while tomatoes are grown for its fruit rich in fibres, minerals and vitamins. The two can be prepared separately or together in a variety of ways including raw salads and/or cooked/fried. They together form significant delicacies consumed with rice which is the major cash crop grown in the black cotton soils. The crops can grow well in warm conditions but tomato is fairly adaptable except under excessive humidity and temperatures that reduce yields. Socio-economic prioritization by the farming community and on-farm demonstrations of soil management options were instituted to demonstrate enhanced green gram and tomato production in vertisol soils of lower parts of Kirinyaga County (Mwea East and Mwea West districts). Drainage management was recognized by the farming community as the best option although a reduced number of farmers used drainage and furrows/ridges, manure, fertilizer and shifting options with reducing order of importance. Unavailability of labour and/or financial cost for instituting these management options were indicated as major hindrances to adopt the yield enhancing options. Labour force was contributed to mainly by the family alongside hiring (64.2%) although 28% and 5.2% respectively used hired or family labour alone. The female role in farming activities dominated while the male role was minimal especially at weeding. The youth role remained excessively insignificant and altogether absent at marketing. Despite the need for labour at earlier activities (especially when management options needed to be instituted) it was at the marketing stage that this force was directed. Soils were considered infertile by 60% but 40% indicated that their farms had adequate fertility. Analysis showed that ridging and application of farm yard manure and fertilizer improved fertility, crop growth and income considerably. Phosphate and zinc enhancement reduced alkalinity and sodicity. Green gram and tomato yields increased under ridges and farm yard manure application by 17-25% which significantly enhanced household income.

Your crop-share-cash farm lease /

"Issued June 1961."

RP97-75 Fixed and Flexible Cash Rental Arrangements for Your Farm

The kind of rental arrangements for cropland vary widely in each locality and from one geographic area to another. What is desirable for one particular landlord/tenant relationship is not acceptable for others. The purpose of this publication is to help tenants and landlords develop fair cash-rent arrangements and assist them in making sound decisions based on a fair evaluation of resources. The first section addresses whether a fixed cash-rent lease arrangement should be used. Part II discusses how to develop a fair fixed cash rental rate, while Part III provides information on setting rent for other cropland, pasture, and buildings. Part IV outlines the advantages and disadvantages of flexible cash-leasing arrangements. Part V discusses the importance of developing a written lease agreement. A sample lease form also is included.

RP94-217 No. 18 Use of Crop Futures and Options by the Nontrader

Crop producers make a number of decisions that are market related. They may be categorized as financial decisions, production decisions, or marketing decisions. All three decisions depend on what prices are likely to be at some specific time in the future. The marketing decisions is complex. This research publication discusses the number of alternatives that are available even for the producer who does not directly buy or sell futures or options contracts.

EC94-852 Cash Flow Planning Form

This extension circular covers the following areas of a cash flow planning form: Beginning Cash Balance, Operating Sales (crop and hay, market livestock, livestock product, custom work); Capital Sales (breeding livestock, machinery and equipment); Personal Income (wages, interest); Operating Expenses (car/truck, chemicals, conservation, custom hire, feed purchased, fertilizers and lime, freight and trucking, gasoline, fuel and oil, insurance, labor hired, rents and leases, repairs and maintenance, seeds and plants, storage, warehousing, supplies, taxes, utilities, veterinary, breeding fees and medicine, feeder livestock); Capital Purchases (breeding livestock, machinery and equipment, family living withdrawals, personal investments, income and social security, term loan payments); Net Cash Available (operating loan borrowings, operating loan payments); and Ending Operating Loan Balance. Along with the Cash Flow Planning Form is a Projected Income Statement Form which covers Projected Business Income (operating sales, breeding livestock, estimated cash income adjustments, estimated gross revenues, estimated value of production); Project Business Expenses (cash operating, esimated operating, prepaid and supplies, cash investment in growing crops, accounts payable); Projected Net Income Summary (estimated net income from operations, estimated net business income, estimated net income after taxes, estimated earned net worth change); and a Physical Inventory Flows Worksheet.

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.

Spatio-temporal modeling of agricultural yield data with an application to pricing crop insurance contracts

This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Parana (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited.

Parametric and nonparametric statistical modelling of crop yield: implications for pricing crop insurance contracts

This article considers alternative methods to calculate the fair premium rate of crop insurance contracts based on county yields. The premium rate was calculated using parametric and nonparametric approaches to estimate the conditional agricultural yield density. These methods were applied to a data set of county yield provided by the Statistical and Geography Brazilian Institute (IBGE), for the period of 1990 through 2002, for soybean, corn and wheat, in the State of Paran. In this article, we propose methodological alternatives to pricing crop insurance contracts resulting in more accurate premium rates in a situation of limited data.

Crop rotation in center-pivot for phytonematode control: density variation, pathogenicity and crop loss estimation

Crop rotation in center-pivot for phytonematode control: density variation, pathogenicity and crop loss estimation A field study conducted over three consecutive years, on a farm using crop rotation system under center-pivot and infested with the nematodes Pratylenchus brachyurus, P. zeae, Meloidogyne incognita, Paratrichodorus minor, Helicotylenchus dihystera, Mesocriconema ornata and M. onoense, demonstrated that intensive crop systems provide conditions for the maintenance of high densities of polyphagous phytonematodes. Of the crops established on the farm (cotton, maize, soybean and cowpea), cotton and soybean suffered the most severe crop losses, caused respectively by M. incognita and P. brachyurus. Since maize is a good host for both nematodes, but tolerant of M. incognita, its exclusion from cropping system would be favorable to the performance of cotton, soybean and cowpea. Results from experiments carried out in controlled conditions confirmed the pathogenicity of P. brachyurus on cotton. Additional management with genetic resistance was useful in fields infested with M. incognita, although the soybean performance was affected by low resistance of the cultivars used for P. brachyurus. In conclusion, crop rotation must be carefully planned in areas infested with polyphagous nematodes, specifically in the case of occurrence of two or more major pathogenic nematodes.

Host suitability of oats for Pratylenchus brachyurus

Host suitability of oats for Pratylenchus brachyurus Black oat (Avena strigosa), white oat (A. sativa) and Algerian oat (A. byzantina) are extensively cultivated in the south of Brazil for grain, forage, hay and silage production, or as cover crop in no-tillage and crop-pasture integration systems. In both systems, the genotypes of oat used as cover crop must be nonhosts or poor hosts of damaging nematodes for summer cash crops. Taking into account the relevance of Pratylenchus brachyurus as a pathogen for many cash crops in Brazil, two experiments were carried out in a glasshouse in order to evaluate the host suitability of selected oat cultivars to this nematode. The initial population inoculated (Pi) were 92 specimens/plot in experiment 1, and 270 in experiment 2. At the end of experimental periods (86 days after inoculation in experiment 1 and 67 days in experiment 2), the final population (Pf) of P. brachyurus was estimated and the reproductive factor (RF = Pf/Pi) was calculated. The results demonstrated that black oat (RF = 0.04-1.03) is more valuable than Algerian oat (RF = 2.63-2.88) or white oat (RF = 1.37-1.93) for the management of P. brachyurus.