Genetically modified insect resistance in cotton: some farm level economic impacts in India

The paper explores the impact of insect-resistant Bacillus thuringiensis (Bt) cotton on costs and returns over the first two seasons of its commercial release in three sub-regions of Maharashtra State, India. It is the first such research conducted in India based on farmers' own practices rather than trial plots. Data were collected for a total of 7793 cotton plots in 2002 and 1577 plots in 2003. Results suggest that while the cost of cotton seed was much higher for farmers growing Bt cotton relative to those growing non-Bt cotton, the costs of bollworm spray were much lower. While Bt plots had greater costs (seed plus insecticide) than non-Bt plots, the yields and revenue from Bt plots were much higher than those of non-Bt plots (some 39% and 63% higher in 2002 and 2003, respectively). Overall, the gross margins of Bt plots were some 43% (2002) and 73% (2003) higher than those of non-Bt plots, although there was some variation between the three sub-regions of the state. The results suggest that Bt cotton has provided substantial benefits for farmers in India over the 2 years, but there are questions as to whether these benefits are sustainable. (c) 2004 Elsevier Ltd. All rights reserved.

Inequality and GM crops: a case study of Bt cotton in India

Critics of genetically modified (GM) crops often contend that their introduction enhances the gap between rich and poor farmers, as the former group are in the best position to afford the expensive seed as well as provide other inputs such as fertilizer and irrigation. The research reported in this paper explores this issue with regard to Bt cotton (cotton with the endotoxtin gene from Bacillus thuringiensis conferring resistance to some insect pests) in Jalgaon, Maharashtra State, India, spanning the 2002 and 2003 seasons. Questionnaire–based survey results from 63 non–adopting and 94 adopting households of Bt cotton were analyzed, spanning 137 Bt cotton plots and 95 non–Bt cotton plots of both Bt adopters and non–adopters. For these households, cotton income accounted for 85 to 88% of total household income, and is thus of vital importance. Results suggest that in 2003 Bt adopting households have significantly more income from cotton than do non–adopting households (Rp 66,872 versus Rp 46,351) but inequality in cotton income, measured with the Gini coefficient (G), was greater amongst non–adopters than adopters. While Bt adopters had greater acreage of cotton in 2003 (9.92 acres versus 7.42 for non–adopters), the respective values of G were comparable. The main reason for the lessening of inequality amongst adopters would appear to be the consistency in the performance of Bt cotton along with the preferred non–Bt cultivar of Bt adopters—Bunny. Taking gross margin as the basis for comparison, Bt plots had 2.5 times the gross margin of non–Bt plots of non–adopters, while the advantage of Bt plots over non–Bt plots of adopters was 1.6 times. Measured in terms of the Gini coefficient of gross margin/acre it was apparent that inequality was lessened with the adoption of Bunny (G = 0.47) and Bt (G = 0.3) relative to all other non–Bt plots (G = 0.63). Hence the issue of equality needs to be seen both in terms of differences between adopters and non–adopters as well as within each of the groups.

Influence of socio-economic and cultural factors in rice varietal diversity management on-farm in Nepal

A questionnaire survey of 408 households explored the role of socio-economic and cultural factors in rice (Oryza sativa L.) varietal diversity management on-farm in two contrasting eco-sites in Nepal. Multiple regression outputs suggest that number of parcels of land, livestock number, number of rice ecosystems, agro-ecology (altitude), and use of chemical fertilizer have a significant positive influence on landrace diversity on-farm, while membership in farmers' groups linked to extension services has significant but negative influence on landrace diversity. Factors with significant positive influence on diversity of modern varieties on-farm were number of parcels of land and of rice ecosystems, access to irrigation, membership in farmers' groups, and use of insecticide. Within communities, resource-endowed households maintain significantly higher varietal diversity on-farm than resource-poor households and play a significant role in conserving landraces that are vulnerable to genetic erosion and those with socio-cultural and market-preferred traits. Resource-poor households also contribute to local diversity conservation but at lower richness and area coverage levels than resource-endowed households. Households where a female had assumed the role of head of household due to death or migrant work of her husband had less diversity due to lower labor availability. Landraces with socio-cultural and market-preferred traits are few in number but have potential to be conserved on-farm.

Output risk aspects of genetically modified crop technology in South Africa

Technology involving genetic modification of crops has the potential to make a contribution to rural poverty reduction in many developing countries. Thus far, insecticide-producing 'Bt' varieties of cotton have been the main GM crops under cultivation in developing nations. Several studies have evaluated the farm-level performance of Bt varieties in comparison to conventional ones by estimating production technology, and have mostly found Bt technology to be very successful in raising output and/or reducing insecticide input. However, the production risk properties of this technology have not been studied, although they are likely to be important to risk-averse smallholders. This study investigates the output risk aspects of Bt technology using a three-year farm-level dataset on smallholder cotton production in Makhathini flats, Kwa-Zulu Natal, South Africa. Stochastic dominance and stochastic production function estimation methods are used to examine the risk properties of the two technologies. Results indicate that Bt technology increases output risk by being most effective when crop growth conditions are good, but being less effective when conditions are less favourable. However, in spite of its risk increasing effect, the mean output performance of Bt cotton is good enough to make it preferable to conventional technology even for risk-averse smallholders.

Production risk, pesticide use and GM crop technology in South Africa

Technology involving genetic modification of crops has the potential to make a contribution to rural poverty reduction in many developing countries. Thus far, pesticide-producing Bacillus thuringensis (Bt) varieties of cotton have been the main GM crops under cultivation in developing nations. Several studies have evaluated the farm-level performance of Bt varieties in comparison to conventional ones by estimating production technology, and have mostly found Bt technology to be very successful in raising output and/or reducing pesticide input. However, the production risk properties of this technology have not been studied, although they are likely to be important to risk-averse smallholders. This study investigates the output risk aspects of Bt technology by estimating two 'flexible risk' production function models allowing technology to independently affect the mean and higher moments of output. The first is the popular Just-Pope model and the second is a more general 'damage control' flexible risk model. The models are applied to cross-sectional data on South African smallholders, some of whom used Bt varieties. The results show no evidence that a 'risk-reduction' claim can be made for Bt technology. Indeed, there is some evidence to support the notion that the technology increases output risk, implying that simple (expected) profit computations used in past evaluations may overstate true benefits.

Logit models for identifying the factors that influence the uptake of new 'no-tillage' technologies by farmers in the rice-wheat and the cotton-wheat farming systems of Pakistan's Punjab

In the 'rice-wheat' and the 'cotton-wheat' farming systems of Pakistan's Punjab, late planting of wheat is a perennial problem due to often delayed harvesting of the previously planted and late maturing rice and cotton crops. This leaves very limited time for land preparation for 'on-time' planting of wheat. 'No-tillage' technologies that reduce the turn-round time for wheat cultivation after rice and cotton have been developed, but their uptake has not been as expected.-This paper attempts to determine the farm and farmer characteristics and other socio-economic factors that influence the adoption of 'no-tillage' technologies'. Logit models were developed for the analysis undertaken. In the 'cotton-wheat' system personal characteristics like education, tenancy status, attitude towards risk implied in the use of new technologies and contact with extension agents are the main factors that affect adoption. As regards the 'rice-wheat' system, resource endowments such as farm size, access to a 'no-tillage' drill, clayey soils and the area sown to the rice-wheat sequence along with tenancy and contact with extension agents were dominant in explaining adoption. (C) 2002 Elsevier Science Ltd. All rights reserved.

Decoupling EU farm support: Does the new single payment scheme fit within the green box?

Recent reform of the EU’s Common Agricultural Policy (CAP) has led to a further decoupling of farm support. The EU believes that the new Single Payment Scheme, which replaces the former system of area and headage payments to farmers, tied to production, will qualify for green-box status in the WTO. We examine this contention, particularly in light of the recent WTO panel report on upland cotton.

Farm-level risk factors for fluoroquinolone resistance in E-coli and thermophilic Campylobacter spp. on finisher pig farms

Logistic regression, supported by other statistical analyses was used to explore the possible association of risk factors with the fluoroquinolone (FQ)-resistance status of 108 pig finisher farms in Great Britain. The farms were classified as 'affected' or 'not affected' by FQ-resistant E. coli or Campylobacter spp. on the basis of isolation of organisms from faecal samples on media containing 1 mg/l FQ. The use of FQ was the most important factor associated with finding resistant E. coli and/or Campylobacter, which were found on 79% (FQ-resistant E. coli) and 86% (FQ-resistant Campylobacter) of farms with a history of FQ use. However, resistant bacteria were also found on 19% (FQ-resistant E. coli) and 54% (FQ-resistant Campylobacter) of farms with no history of FQ use. For FQ-resistant E. coli, biosecurity measures may be protective and there was strong seasonal variation, with more farms found affected when sampled in the summer. For FQ-resistant Campylobacter, the buying-in of grower stock may increase risk and good on-farm hygiene may be protective. The findings suggest that resistant organisms, particularly Campylobacter, may spread between pig farms.

Predation of Bradysia sp (Diptera: Sciaridae), Liriomyza trifolii (Diptera: Agromyzidae) and Bemisia tabaci (Hemiptera: Aleyrodidae) by Coenosia attenuata (Diptera: Muscidae) in greenhouse crops

We studied the predation behaviour of the "hunter fly" (Coenosia attenuata Stein) in the laboratory and greenhouse. In the laboratory, which was conducted at 25 degrees C at 60-80% RH, with a 16L : 8D photoperiod, we examined the functional response of this species to three different pests, namely the sciarid fly (Bradysia sp.), the tobacco whitefly (Bemisia tabaci) and the leaf miner Liriomyza trifolii. In the greenhouse, we studied the population dynamics of the predator and its prey on pepper and water melon crops grown in southern Spain. Adult hunter flies were found to exhibit a type I functional response to adult sciarid flies and whiteflies, but a type II response to adult leaf miners. The type II response was a result of the greater difficulty in capturing and handling leaf miners compared to the other two species. The dynamics of the predator-prey interaction in the greenhouse revealed that the predator specializes mainly on adult sciarids and that the presence of the other prey can be supplemental, but is never essential for survival of the predator; this, however, is crop-dependent. The results oil the dynamics of the predator-prey systems were obtained through a known population dynamics model with modifications.

Bayesian clustering of farm types using the mixtures model

A Bayesian method of classifying observations that are assumed to come from a number of distinct subpopulations is outlined. The method is illustrated with simulated data and applied to the classification of farms according to their level and variability of income. The resultant classification shows a greater diversity of technical charactersitics within farm types than is conventionally the case. The range of mean farm income between groups in the new classification is wider than that of the conventional method and the variability of income within groups is narrower. Results show that the highest income group in 2000 included large specialist dairy farmers and pig and poultry producers, whilst in 2001 it included large and small specialist dairy farms and large mixed dairy and arable farms. In both years the lowest income group is dominated by non-milk producing livestock farms.