Farm business survey 2008/09: horticulture Production in England

The report gives an overview of the horticultural industry in the United Kingdom, including a snapshot of the different sectors of production, together with other information of interest about the business of horticulture. The data includes the economic performance of horticultural businesses in Ebgland during 2008/09.

Farm business survey 2009/10: horticulture production in England

Thereport gives an overview of the horticultural industry in the United Kingdom, including a snapshot of the different sectors of production, together with other information of interest about the business of horticulture. The data includes the economic perforamnce of horticulture businesses in England during 2009/10

Farm business survey 2008/09: poultry production in England

The report provides a commentary on the UK poultry industry focusing on its structure, development and contribution to the UK agricultural economy. It also includes data on the economic performance of poultry businesses in England during 2008/09.

Farm business survey 2009/10: poultry production in England

A commentary on the UK poultry industry focusing on its structure, trends and development. Analysis includes the economic performance of poultry businesses in England during 2009/10.

Suitability of pesticide risk indicators for less developed countries: a comparison

Pesticide risk indicators provide simple support in the assessment of environmental and health risks from pesticide use, and can therefore inform policies to foster a sustainable interaction of agriculture with the environment. For their relative simplicity, indicators may be particularly useful under conditions of limited data availability and resources, such as in Less Developed Countries (LDCs). However, indicator complexity can vary significantly, in particular between those that rely on an exposure–toxicity ratio (ETR) and those that do not. In addition, pesticide risk indicators are usually developed for Western contexts, which might cause incorrect estimation in LDCs. This study investigated the appropriateness of seven pesticide risk indicators for use in LDCs, with reference to smallholding agriculture in Colombia. Seven farm-level indicators, among which 3 relied on an ETR (POCER, EPRIP, PIRI) and 4 on a non-ETR approach (EIQ, PestScreen, OHRI, Dosemeci et al., 2002), were calculated and then compared by means of the Spearman rank correlation test. Indicators were also compared with respect to key indicator characteristics, i.e. user friendliness and ability to represent the system under study. The comparison of the indicators in terms of the total environmental risk suggests that the indicators not relying on an ETR approach cannot be used as a reliable proxy for more complex, i.e. ETR, indicators. ETR indicators, when user-friendly, show a comparative advantage over non-ETR in best combining the need for a relatively simple tool to be used in contexts of limited data availability and resources, and for a reliable estimation of environmental risk. Non-ETR indicators remain useful and accessible tools to discriminate between different pesticides prior to application. Concerning the human health risk, simple algorithms seem more appropriate for assessing human health risk in LDCs. However, further research on health risk indicators and their validation under LDC conditions is needed.

Considering the normative, systemic and procedural dimensions in indicator-based sustainability assessments in agriculture

This paper develops a framework for evaluating sustainability assessment methods by separately analyzing their normative, systemic and procedural dimensions as suggested by Wiek and Binder [Wiek, A, Binder, C. Solution spaces for decision-making – a sustainability assessment tool for city-regions. Environ Impact Asses Rev 2005, 25: 589-608.]. The framework is then used to characterize indicator-based sustainability assessment methods in agriculture. For a long time, sustainability assessment in agriculture has focused mostly on environmental and technical issues, thus neglecting the economic and, above all, the social aspects of sustainability, the multifunctionality of agriculture and the applicability of the results. In response to these shortcomings, several integrative sustainability assessment methods have been developed for the agricultural sector. This paper reviews seven of these that represent the diversity of tools developed in this area. The reviewed assessment methods can be categorized into three types: (i) top-down farm assessment methods; (ii) top-down regional assessment methods with some stakeholder participation; (iii) bottom-up, integrated participatory or transdisciplinary methods with stakeholder participation throughout the process. The results readily show the trade-offs encountered when selecting an assessment method. A clear, standardized, top-down procedure allows for potentially benchmarking and comparing results across regions and sites. However, this comes at the cost of system specificity. As the top-down methods often have low stakeholder involvement, the application and implementation of the results might be difficult. Our analysis suggests that to include the aspects mentioned above in agricultural sustainability assessment, the bottomup, integrated participatory or transdisciplinary methods are the most suitable ones.

Prediction of processed cheese instrumental texture and meltability by mid-infrared spectroscopy coupled with chemometric tools

The objective of this study was to determine the potential of mid-infrared spectroscopy coupled with multidimensional statistical analysis for the prediction of processed cheese instrumental texture and meltability attributes. Processed cheeses (n = 32) of varying composition were manufactured in a pilot plant. Following two and four weeks storage at 4 degrees C samples were analysed using texture profile analysis, two meltability tests (computer vision, Olson and Price) and mid-infrared spectroscopy (4000-640 cm(-1)). Partial least squares regression was used to develop predictive models for all measured attributes. Five attributes were successfully modelled with varying degrees of accuracy. The computer vision meltability model allowed for discrimination between high and low melt values (R-2 = 0.64). The hardness and springiness models gave approximate quantitative results (R-2 = 0.77) and the cohesiveness (R-2 = 0.81) and Olson and Price meltability (R-2 = 0.88) models gave good prediction results. (c) 2006 Elsevier Ltd. All rights reserved..

Farmers' management of rice varietal diversity in the mid-hills of Nepal: implications for on-farm conservation and crop improvement

Season-long monitoring of on-farm rice (Oryza sativa, L.) plots in Nepal explored farmers' decision-making process on the deployment of varieties to agroecosystems, application of production inputs to varieties, agronomic practices and relationship between economic return and area planted per variety. Farmers deploy varieties [landraces (LRs) and modern varieties (MVs)] to agroecosystems based on their understanding of characteristics of varieties and agroecosystems, and the interaction between them. In marginal growing conditions, LRs can compete with MVs. Within an agroecosystem, economic return and area planted to varieties have positive relationship, but this is not so between agroecosystems. LRs are very diverse on agronomic and economic traits; therefore, they cannot be rejected a priori as inferior materials without proper evaluation. LRs have to be evaluated for useful traits and utilized in breeding programmes to generate farmer-preferred materials for marginal environments and for their conservation on-farm.

On-farm management of rice genetic diversity: understanding farmers' knowledge on rice ecosystems and varietal development

The paper highlights the methodological development of identifying and characterizing rice (Oryza sativa L.) ecosystems and the varietal deployment process through participatory approaches. Farmers have intricate knowledge of their rice ecosystems. Evidence from Begnas (mid-hill) and Kachorwa (plain) sites in Nepal suggests that farmers distinguish ecosystems for rice primarily on the basis of moisture and fertility of soils. Farmers also differentiate the number, relative size and specific characteristics of each ecosystem within a given geographic area. They allocate individual varieties to each ecosystem, based on the principle of ‘best fit’ between ecosystem characteristics and varietal traits, indicating that competition between varieties mainly occurs within the ecosystems. Land use and ecosystems determine rice genetic diversity, with marginal land having fewer options for varieties than more productive areas. Modern varieties are mostly confined to productive land, whereas landraces are adapted to marginal ecosystems. Researchers need to understand the ecosystems and varietal distribution within ecosystems better in order to plan and execute programmes on agrobiodiversity conservation on-farm, diversity deployment, repatriation of landraces and monitoring varietal diversity. Simple and practical ways to elicit information on rice ecosystems and associated varieties through farmers’ group discussion at village level are suggested.