Farming systems research is a multi-disciplinary holistic approach to solve the problems of small farms. Small and marginal farmers are the core of the Indian rural economy constituting 0·80 of the total farming community but possessing only 0·36 of the total operational land. The declining trend of per capita land availability poses a serious challenge to the sustainability and profitability of farming. Under such conditions, it is appropriate to integrate land-based enterprises such as dairy, fishery, poultry, duckery, apiary, field and horticultural cropping within the farm, with the objective of generating adequate income and employment for these small and marginal farmers under a set of farm constraints and varying levels of resource availability and opportunity. The integration of different farm enterprises can be achieved with the help of a linear programming model. For the current review, integrated farming systems models were developed, by way of illustration, for the marginal, small, medium and large farms of eastern India using linear programming. Risk analyses were carried out for different levels of income and enterprise combinations. The fishery enterprise was shown to be less risk-prone whereas the crop enterprise involved greater risk. In general, the degree of risk increased with the increasing level of income. With increase in farm income and risk level, the resource use efficiency increased. Medium and large farms proved to be more profitable than small and marginal farms with higher level of resource use efficiency and return per Indian rupee (Rs) invested. Among the different enterprises of integrated farming systems, a chain of interaction and resource flow was observed. In order to make farming profitable and improve resource use efficiency at the farm level, the synergy among interacting components of farming systems should be exploited. In the process of technology generation, transfer and other developmental efforts at the farm level (contrary to the discipline and commodity-based approaches which have a tendency to be piecemeal and in isolation), it is desirable to place a whole-farm scenario before the farmers to enhance their farm income, thereby motivating them towards more efficient and sustainable farming.

Many of the most pervasive disease challenges to livestock are transmitted via oral contact with faeces (or by faecal–aerosol) and the current paper focuses on how disease risk may depend on: spatial heterogeneity, animal searching behaviour, different grazing systems and faecal deposition patterns including those representative of livestock and a range of wildlife. A spatially explicit agent-based model was developed to describe the impact of empirically observed foraging and avoidance behaviours on the risk of disease presented by investigative and grazing contact with both livestock and wildlife faeces. To highlight the role of spatial heterogeneity on disease risks an analogous deterministic model, which ignores spatial heterogeneity and searching behaviour, was compared with the spatially explicit agent-based model. The models were applied to assess disease risks in temperate grazing systems. The results suggest that spatial heterogeneity is crucial in defining the disease risks to which individuals are exposed even at relatively small scales. Interestingly, however, although sensitive to other aspects of behaviour such as faecal avoidance, it was observed that disease risk is insensitive to search distance for typical domestic livestock restricted to small field plots. In contrast disease risk is highly sensitive to distributions of faecal contamination, in that contacts with highly clumped distributions of wildlife contamination are rare in comparison to those with more dispersed contamination. Finally it is argued that the model is a suitable framework to study the relative inter- and intra-specific disease risks posed to livestock under different realistic management regimes.

In France, many dairy farms plan the allocation of animal wastes to the fields of the farm at the beginning of every year. This decision is complex, because many factors must be taken into account at the field and farm scales, including increasingly constraining environmental regulations. To evaluate the environmental impact of waste allocation strategies, these strategies have to be translated into consistent decisions. The objective of the current study was to reproduce the decisions made by farmers, in a wide range of contexts. For this purpose, a linear programming model that could help in generating yearly waste allocations was developed. The model, called Fumigene, takes into account the farmer's preferences and environmental, agronomic and feasibility constraints. It was applied on two case farms and the simulated waste allocations were compared to those chosen by the farmers over periods of 3 and 4 years, respectively. The evaluation showed that the waste allocations generated by the model were consistent with the strategies of the farmers. Fumigene was then used in investigating the impact of taking into account the phosphorus (P) fertilization constraints instead of only the nitrogen constraints. In the case studied, balancing P fertilization over 5 years led to small changes in waste allocation. Balancing P fertilization every year caused bigger changes and led to export of a part of the wastes. In a general way, Fumigene can be coupled with environmental evaluation tools to compare the impacts of different waste allocation strategies.

Previous work has shown that the national average quality of the UK wheat crop from 1974 to 1999 was associated with the preceding winter North Atlantic Oscillation (NAO). The association of the winter NAO with the grain quality measure, specific weight, was shown to be mediated by sunshine duration during grain filling and unconditional wet day probability during grain ripening (the probability of a wet day following either a dry or a wet day). The present study tests the hypothesis that the association between specific weight and the winter NAO can be detected in data from 158 years of the Broadbalk Wheat Experiment at Rothamsted in south-east England. Specific weight from the Broadbalk Experiment responded to sunshine duration during grain filling and unconditional wet day probability during grain ripening in a similar way to the national average data. An association with the winter NAO was found in the Broadbalk data from 1956 to 2001, but not in the previous 112 years (1844–1955). This finding is consistent with other work showing significant correlations between the winter NAO and summer climate only in recent decades. It is concluded that the association between wheat quality and the NAO is a recent phenomenon.

Hard endosperm maize (Zea mays L.) is useful for industry and for human consumption. The objective of the present work was to study the inheritance of quality traits in hard endosperm maize. Three flint and three dent inbreds, F1 of their diallel crosses, F2s and backcrosses to each parent were evaluated for grain yield and quality traits (flotation test, flour-milling test, grain damage (GD) index and grain density). Genotypes and genotype×environment interactions were significant for most traits. A genetic model including additive, dominance and epistatic effects explained most of the genetic variation for the traits. Additive effect mean squares were larger than those due to dominance effects, except for grain yield and GD. Partition of the dominance variance into average, general, and specific dominance components revealed that the average dominance related to heterosis was the most important. Additive×additive epistatic variation was smaller than additive and dominance variation for quality traits. Some inbreds displayed sufficient potential to be used in hard endosperm maize breeding programmes. The average dominance effect was favourable for most of the quality and agronomic traits. Breeding programmes for improving quality in hard endosperm maize would be most efficient if both additive and dominant effects are capitalized on.

Genetic manipulation of leaf architecture may be a useful breeding objective in cotton (Gossypium spp.). The present study reports quantitative genetic analysis of leaf traits from two intraspecific crosses of inbred lines in upland cotton (Gossypium hirsutum L.) viz. Kang3×Chaoji463 and Han109×Ji98. Six leaf morphological traits (leaf area (LA), leaf perimeter (LP), main lobe length (LL) and width (LW), petiole length (PL), and main LL/LW ratio) were recorded from multiple generations (P1, F1, P2, BC1, BC2, and F2) in the two crosses. Generation mean analyses were conducted to explain the inheritance of each leaf morphological trait. The six-parameter model showed a better fit to an additive-dominance model for LA, main LW, PL, and main LL/LW ratio in the two crosses, suggesting the relative importance of epistatic effects controlling leaf morphology. A simple additive-dominance model accounted for the genetic variation of the main LL in the Kang3×Chaoji463 cross. Different models were selected as appropriate to explain LP in the two crosses. The differences between broad- and narrow-sense heritability values for the same trait were not constant in the two crosses. The estimated minimum number of genes controlling each leaf morphological trait ranged from 0 to 2 for both the crosses. Moreover, the sums of the minimum number of genes controlling leaf morphology were 6 and 2 in the Kang3×Chaoji463 and Han109×Ji98 populations, respectively. Most data suggested that there existed a substantial opportunity to breed cottons that transgress the present range of leaf phenotypes found.

Genotype by environment (G×E) interaction effects are of special interest for breeding programmes to identify adaptation targets and test locations. Their assessment by additive main effect and multiplicative interaction (AMMI) model analysis is currently defined for this situation. A combined analysis of two former parametric measures and seven AMMI stability statistics was undertaken to assess G×E interactions and stability analysis to identify stable genotypes of 11 lentil genotypes across 20 environments. G×E interaction introduces inconsistency in the relative rating of genotypes across environments and plays a key role in formulating strategies for crop improvement. The combined analysis of variance for environments (E), genotypes (G) and G×E interaction was highly significant (P<0·01), suggesting differential responses of the genotypes and the need for stability analysis. The parametric stability measures of environmental variance showed that genotype ILL 6037 was the most stable genotype, whereas the priority index measure indicated genotype FLIP 82-1L to be the most stable genotype. The first seven principal component (PC) axes (PC1–PC7) were significant (P<0·01), but the first two PC axes cumulatively accounted for 71% of the total G×E interaction. In contrast, the AMMI stability statistics suggested different genotypes to be the most stable. Most of the AMMI stability statistics showed biological stability, but the SIPCF statistics of AMMI model had agronomical concept stability. The AMMI stability value (ASV) identified genotype FLIP 92-12L as a more stable genotype, which also had high mean performance. Such an outcome could be regularly employed in the future to delineate predictive, more rigorous recommendation strategies as well as to help define stability concepts for recommendations for lentil and other crops in the Middle East and other areas of the world.

The control effect of Cucurbita ficifolia (pumpkin) leaf acetone extract on caterpillars of the small cabbage butterfly Pieris rapae Linnaeus (Lepidoptera: Pieridae) was observed in laboratory and field experiments from 1 March 2006 to 30 May 2007. The mechanism of the action by which pumpkin leaf extract (PLE) controls small cabbage caterpillars was examined for feeding restraint, and the values for 0·50 feeding restraint concentration (FC50) and 0·95 feeding restraint concentration (FC95) after 12 and 24 h were estimated. The results showed that the absolute anti-feeding activity for fourth instar caterpillars after 12 h was 0·65 and after 24 h was 0·56, while relative anti-feeding activity was 0·57 after 12 h and 0·59 after 24 h. Field experimental results indicated that the leaf protection effects increased up to day 7, while the feeding control effects remained constant. Comparison of the profits from pest management using indigenous pesticides, biological pesticides and chemical pesticides and without pest management suggested that there are currently economic benefits associated with the use of indigenous pesticides, such as PLE.

The working group, which is concerned with operational research methods and applications to agricultural science in its broad meaning (i.e. including Forest Management and Fisheries), was formed in 2003 within the European Association of Operational Research Societies (EURO). The first meeting of the group was held at the former Silsoe Research Institute in 2004. The group intends to have regular meetings in Europe at approximately yearly intervals, usually within the EURO Conferences. However, the next meeting will be held in 2008 within the British Operational Research Society's OR50 Conference in York, followed by the EURO XXIII Conference in Bonn in 2009 and the EURO XXIV Conference in Lisbon in 2010. The third meeting of the working group, chaired by Dr L. M. Plà of the University of Lleida, with the assistance of D. L. Sandars of Cranfield University and organized as a stream within the XXII EURO Conference, was held at the University of Economics in Prague from 8 to 11 July 2007 where the following papers were read in a set of 10 sessions.