Plant productivity and other ecosystem processes vary widely in their responses to experimental increases in atmospheric carbon dioxide (CO2) concentration. A conceptual framework first suggested by Chapin et al. (1996) was adapted to address the question of why CO2 effects on primary productivity vary so greatly among rangelands and among years for a given ecosystem. The ‘interactive controls’ framework is based on the premise that the influence of elevated CO2 on productivity is governed by a set of internal variables that interact dynamically with ecosystem processes. These interactive controls, which include regional climate, soil resource supply, major functional groups of organisms and disturbance regimes, both regulate CO2 effects on ecosystems and respond to CO2 effects. Changes in interactive controls resulting from CO2 enrichment may feed back to dampen or amplify ecosystem responses to CO2. Most feedbacks from interactive controls will be negative and dampen CO2 effects on ecosystems. Negative feedbacks promote homeostasis in ecosystem processes and reduce the response of plant productivity to CO2. Positive feedbacks on CO2 responses are fewer, but can sustain or even increase benefits of CO2 enrichment for productivity. Positive feedbacks on CO2 responses occur most frequently through changes in plant species and functional group composition. Understanding positive and negative feedbacks on CO2 responses could be one key to predicting consequences of CO2 enrichment for rangeland productivity and other processes.

The association of carbon isotope discrimination of grain (Δ13C) with yield performance under rain-fed and well-watered conditions was analysed using a doubled-haploid (DH) winter wheat population, derived from the cross between cvars Beaver×Soissons, within field experiments at two site-seasons. The aim of this work was to quantify associations between Δ13C and yield responses to drought and to test effects of major genes (the semi-dwarf genes, Rht-B1b, Rht-D1b, an awn suppressor gene, B1 and the 1BL.1RS wheat–rye chromosome translocation) segregating in the population for associations with Δ13C and drought performance. Carbon isotope discrimination, through its negative relationship with transpiration efficiency, may be used as a surrogate for this trait. Grain Δ13C was positively associated with grain yield under both irrigated and unirrigated conditions in each site-season and, overall, explained 0·34 of the phenotypic variation in grain yield amongst DH lines under drought and 0·14 under well-watered conditions. There was a positive association between specific leaf lamina N content (SLN) at anthesis and Δ13C under drought amongst DH lines in one site-season, suggesting higher SLN may confer increased stomatal conductance via higher photosynthetic capacity, hence increased grain Δ13C. Overall the Rht-D1b (semi-dwarf) lines had slightly higher Δ13C of grain (20·0‰) than the Rht-B1a/Rht-D1a (tall) group of lines (19·8‰). There were no significant differences between the Rht-B1b (semi-dwarf) or the Rht-B1b/Rht-D1b (dwarf) lines and the tall lines. Comparing their performance under irrigated and unirrigated conditions, the Rht groups of lines (Rht-B1b semi-dwarf, Rht-D1b semidwarf and dwarf and tall groups) responded no differently to drought for Δ13C. The Rht-D1b semi-dwarf lines had higher grain yield (9·50 t/ha) than the tall lines (8·76 t/ha), while the yield of the Rht-B1b semi-dwarf and dwarf lines did not differ significantly from the tall lines. In each site-season, the presence of the 1BL.1RS chromosome increased grain Δ13C (P<0·001), with an overall increase from 19·7‰ in the 1B lines to 20·0‰ in the 1BL.1RS lines (P<0·001). However, the 1BL.1RS and 1B lines responded similarly to drought. The effect of the presence/absence of awns on grain Δ13C was not statistically significant in either site-season. Overall, the present results show that Rht-D1b confers higher Δ13C and grain yield, and the 1BL.1RS translocation confers higher Δ13C. This implies that modern UK wheat cultivars may have lower water-use efficiency during the grain filling period than their predecessors, and therefore may require more water to fulfil their yield potential.

The predicted 2–4°C increment in temperature by the end of the 21st Century poses a threat to rice production. The impact of high temperatures at night is more devastating than day-time or mean daily temperatures. Booting and flowering are the stages most sensitive to high temperature, which may sometimes lead to complete sterility. Humidity also plays a vital role in increasing the spikelet sterility at increased temperature. Significant variation exists among rice germplasms in response to temperature stress. Flowering at cooler times of day, more pollen viability, larger anthers, longer basal dehiscence and presence of long basal pores are some of the phenotypic markers for high-temperature tolerance. Protection of structural proteins, enzymes and membranes and expression of heat shock proteins (HSPs) are some of the biochemical processes that can impart thermo-tolerance. All these traits should be actively exploited in future breeding programmes for developing heat-resistant cultivars. Replacement of heat-sensitive cultivars with heat-tolerant ones, adjustment of sowing time, choice of varieties with a growth duration allowing avoidance of peak stress periods, and exogenous application of plant hormones are some of the adaptive measures that will help in the mitigation of forecast yield reduction due to global warming.

Cropping systems contain a diverse multi-species weed flora including several species that cross-breed with and/or descend from crops, including weed beet (Beta vulgaris ssp. vulgaris). The effects of cropping systems on this weed flora are complex because of their large range of variation and their numerous interactions with climate and soil conditions. In order to study and quantify the long-term effects of cropping system components (crop succession and cultural techniques) on weed population dynamics, a biophysical process-based model called GENESYS-Beet has previously been developed for weed beet. In the present paper, the model was modified to remove the crop–weed connection and employed to identify and rank the weed life-traits as a function of their effect on weed emergence timing and density as well as on weed densities at plant, adult and seed bank stages, using a global sensitivity analysis to model parameters. A similar method has already been used with the complete GENESYS-Beet model (i.e. including the crop–weed connection) based on Monte Carlo simulations with simultaneous randomization of all life-trait parameters and run in three cropping systems differing in their risk of infestation by weed beet. Simulated weed emergence timing and density, as well as surviving plant, adult and seed bank densities, were then analysed with regression models as a function of model parameters to rank life-cycle processes and related life-traits and quantify their effects. The comparison of the present, crop-independent results to those of the previous, crop-dependent study showed that the crop-relative weed beet can be considered as a typical crop-independent spring weed as long as no traits conferring a selective advantage are inherited and in rotations where crops favouring weed emergence and reproduction are frequent. In such rotations, advice for controlling the crop-relative and the crop-independent weed is more or less identical. The rarer these favourable crops, the more important pre-emergence processes become for the crop-independent weed; management advice should thus focus more on seed bank survival and seedling emergence. For the crop-relative, post-emergence processes become dominant because of the increasing necessity for a new population founding event; management advice should mostly concern the avoidance of crop bolters. In both studies, the key parameters were more or less the same, i.e. those determining the timing and success of growth, development, seed maturation and the physiological end of seed production. Timing parameters were usually more important than success parameters, showing for instance that optimal timing of weed management operations is often more important than its exact efficacy. Comparison with previous sensitivity analyses carried out for autumn-emerging weed species showed that some of the present conclusions are probably specific to spring-emerging weed species only. For autumn-emerging species, pre-emergence traits would be more important. In the rotations with frequent favourable crops and insufficient weed control, interactions between traits were small, indicating that diverse populations and species with contrasting traits could prosper, potentially leading to a diverse multi-species weed flora. Conversely, when favourable crops were rare and weed control optimal, traits had little impact individually, indicating that a small number of optimal combinations of traits would be successful, thus limiting both intra- and inter-specific variability.

To meet the increasing global demand for food that is predicted over the coming decades it will be necessary to increase productivity and to do this in a way that is sustainable and efficient in its use of resources. Productivity is currently determined by the intrinsic genetic potential of the domestic plants and animals on which mankind is dependent as well as by components of the biophysical environment (temperature, water availability and quality, soil fertility, parasites, pathogens, weeds) from which terrestrial or aquatic food production is derived. Within certain limits, it is possible to manipulate plant and animal genotypes, the production environment, and the inevitable interaction between these factors, to relax constraints on productivity and potential output. Looking to the future, increased scientific understanding will undoubtedly permit this manipulation to be achieved more effectively, thus enabling the scale of production to be elevated predictably while reducing reliance on non-renewable inputs and limiting the use of more forest, grassland, wetland or coastal margin. The present paper introduces a collection of reviews that were commissioned as part of the UK's Government Office of Science Foresight Project on Global Food and Farming Futures which reports early in 2011. The reviews explore opportunities for advances in science and technology to impact in coming decades on the sustainable productivity of terrestrial and aquatic food production systems. Collectively, they describe many of the approaches currently being considered to define, remove or relax the different genetic or environmental constraints limiting sustainable food production. These include: potential impacts of climate change on aquatic systems, the application of biotechnology, genetics and the development of systems to improve livestock, fish and crop production; approaches to the management of parasites and pathogens; weed control in crops; management of soil fertility; approaches to countering problems of water shortage; reducing post-harvest wastage; the role of advanced engineering and the potential for increasing food production in urban environments.

The objective of the present paper was to study the impact of climate change on grain yield, water balance, crop water productivity (CWP) and water requirements for the summer-sown maize in Faisalabad, Pakistan. Climate-change scenarios (Special Report on Emission Scenarios (SRES) A1B, A2 and B1) were derived from the general circulation model ECHAM 5 and the crop model CERES-Maize was used to simulate impacts of the applied climate scenarios. Calibration and validation of the crop models were carried out for the summer-sown maize in 2007 and for the spring-sown maize in 2008. Three predefined reduced irrigation scenarios were compared to traditional irrigation practices for the summer-sown maize. Under the current conditions, scenario S1 (one irrigation event skipped at the vegetative stage) showed a higher simulated yield than scenario S2 (one irrigation event skipped at the grain-filling stage) due to higher water drainage and nitrogen (N) leaching rates in scenario S2. Scenario S3 (irrigation events skipped at both crop establishment and the grain-filling stage) showed significantly higher grain yield because it had the lowest drainage and N leaching rates. In this irrigation scenario, 60 mm of water were saved compared to the other two scenarios, and much more water was saved compared to the traditional local regime.

In the predicted climatic scenarios and with reduced irrigation, the simulated maize yields and crop water productivities were affected differently. For the period from 2036 to 2065, a more significant yield decrease was shown in all emission and irrigation scenarios. A yield decrease was simulated by both, including and not including the direct effect of elevated atmospheric CO2 concentrations on photosynthesis. However, the simulated direct effect of elevated CO2 was to produce higher yield and CWP in all scenarios. The highest grain yields and crop water productivities were achieved in the reduced irrigation scenario S3 for all emission scenarios and climatic periods for the same reason as under the current conditions (N leaching). However, the yield differences between the climate scenarios were mainly due to the shortening of the simulated growing period. This was caused by increased temperatures compared to current conditions. A shortened growing cycle reduced the potential time for biomass accumulation and in the present case it was not balanced by the CO2 fertilizing effect (without a potential change in maize cultivars).

By simulating optimum yields (where automatic irrigation is determined by the model to receive optimum yield), under the current conditions it was found that 285 mm of irrigation would ensure the highest grain yield and CWP (30 mm more than under irrigation scenario S3). In this case, actual evapotranspiration reached 373 mm and less deep drainage and N leaching occurred. In the future climate scenarios, optimum yields and irrigation demands diminished depending on the emission scenario, but CWP increased slightly.

The present simulation study shows a clear decreasing yield trend for autumn maize under a warm climate for each type of (unchanged) irrigation management due to the shortening of the growing period. However, in the current climate, as well as in the future climate scenarios, maize yield levels could be improved by optimized (and reduced) irrigation compared to traditional irrigation due to reduced N leaching. Even in the scenario with the highest warming trend (A1B emission scenario for the period 2036–65), the current yield levels could be kept or even improved.

Dry bean (Phaseolus vulgaris L.) is a traditional crop of north-western Macedonia, Greece, where two landraces (plaki Prespas and Chrisoupoli) in particular are grown. The aim of this study was to test whether the grain carbon isotope discrimination (Δ) and ash content (ASH) are related to grain yield (GY), protein content (PC) and mean grain weight (MGW) in dry bean. As a part of a honeycomb selection programme, 21 genotypes (19 lines derived via intra-landrace honeycomb selection for single plant yield at low density plus the two original populations) were grown at two densities, 1·2 and 4·8 plants/m2 under non-limiting water conditions in a glasshouse and in the field. Genotypes differed significantly for Δ, ASH and PC under the low density. In the dense stand, genotypes differed significantly only for ASH and PC. The environment (glasshouse or field conditions) affected all the traits significantly. Neither Δ nor ASH showed strong or consistent relationships with GY and thus, they cannot serve as reliable, indirect selection criteria for GY. Strong, negative relationships between Δ and PC were found especially in the dense stand, confirming analogous results in C3 cereals. Inconsistent genotypic ranking for grain physiological traits under the different densities and environments was indicative of large genotype×environment interaction. Genotypes performed consistently for GY and MGW under both densities, showing the strong stability of these traits.

Hydrothermal time (HTT) is a valuable environmental synthesis to predict weed emergence. However, weed scientists face practical problems in determining the best soil depth at which to calculate it. Two different types of measures are proposed for this: moment-based indices and probability density-based indices. Due to the monitoring process, it is not possible to observe the exact emergence time of every seedling; therefore, emergence times are not observed individually, seedling by seedling, but in an aggregated way. To address these facts, some new methods to estimate the proposed indices are derived, using grouped data estimators and kernel density estimators. The proposed methods have been exemplified with an emergence data set of Bromus diandrus. The results indicate that hydrothermal timing at 50 mm is more useful than that at 10 mm.

The performances of two remote sensing drought indices were evaluated at selected agricultural sites in different agro-climatic zones in Iran to detect the severity of drought phenomena related to temporal variation and different climatic conditions. The indices used were the perpendicular drought index (PDI) and the modified perpendicular drought index (MPDI), which are derived from moderate resolution imaging spectroradiometer (MODIS) satellite images (MOD13A3 V005). The correlations between these perpendicular indices and two other remote sensing indices in ten different agro-climatic zones of Iran from February 2000 to December 2005 were analysed. The additional indices evaluated were the enhanced vegetation index (EVI) and the vegetation condition index (VCI) along with five water balance parameters, including climatic water balance (CL), crop water balance (CR), monthly reference crop evapotranspiration (ET0), crop evapotranspiration (ETc) and required irrigation water (I). Winter wheat was selected as the reference crop because it is grown in the majority of climatic conditions in Iran.

The results show that in several climatic regions, there is a statistically significant correlation between PDI and MPDI and the water balance parameters, indicating an acceptable performance in detecting crop drought stress conditions. In all zones except at the sites located in northwest and northeast of Iran, VCI and EVI are less correlated with the applied water balance indicators compared to PDI and MPDI. In a temporal analysis, PDI and MPDI showed a greater ability to detect CR conditions than VCI and EVI in the most drought-sensitive winter wheat-growing stages. Since Iran is characterized by arid or semi-arid climatic conditions and winter wheat is a major agricultural crop, a combination of both PDI and MPDI could be used as simple remote sensing-based tool to map drought conditions for crops in Iran and in other developing countries with similar climatic conditions.

An inventory of topsoil soil organic carbon (SOC) content in household farms was performed in a village from a red earth region in Jiangxi Province, China in 2003. In this region, the farmland managed by each household is fragmented, consisting of several plots of land that are not necessarily adjacent to each other. A statistical analysis of SOC variation with land use and household management type, and with crop management practices was conducted. Plot size ranged from 0·007 to 0·630 ha with a mean of 0·1 ha, and SOC content ranged from 1·72 to 25·2 g/kg, varying widely with a variety of land management and agricultural practices, arising from individual household behaviours. The mean SOC content in plot size <0·1 ha was 20% lower than in plot size ⩾0·1 ha. SOC of dry crop plots was 70% lower than that in rice paddies, and SOC of plots contracted from the village was almost double that of plots leased from other householders. Moreover, a 30% increase in SOC was observed with green manure cultivation, and a 55% increase under triple cropping. The difference in SOC levels between the least and most favourable cases of household land management and agricultural practice was up to 150%. The results suggest that policies targeted at crop management alone may not deliver the expected SOC benefits if household land management is also not improved.

Agriculture can benefit substantially from long-range weather forecasts, for the month or the season, which can help to optimize farming operations and deal more effectively with the adverse impacts of climate variability, including extreme weather events. In the context of climate change, long-range weather forecasts also represent key elements for the development of adaptation strategies. In spite of an undeniable potential, long-range forecasts issued for instance by the European Centre for Medium-Range Weather Forecasts (ECMWF) have yet to find widespread application in European agriculture. To address partially the question of why this is the case, the performance of the ECMWF monthly ensemble forecasting system was examined. It was noted that predictability is currently limited to about 3 weeks for temperature and 2 weeks for precipitation and solar radiation. This may appear deceptive at first sight, but it was noticed that precipitation forecasts over a month are, overall, at least as valuable as information obtained from observed climatology. Encouraged by this finding, the possibility of using monthly forecasts to predict soil water availability was tested. In an operational context, this could serve as a basis for scheduling irrigation. Positive skills were found for lead times of up to 1 month. It was concluded that more systematic investigations of the possibilities offered by long-range forecasts should be undertaken in the future. However, this will require additional efforts to increase the quality of the forecasts, design appropriate application tools and promote the dissemination of the outcome within the agriculture community.

The challenge for the next 50 years is to increase the productivity of major livestock species to address the food needs of the world, while at the same time minimizing the environmental impact. The present review presents an optimistic view of this challenge. The completion of genome sequences, and high-density analytical tools to map genetic markers, allows for whole-genome selection programmes based on linkage disequilibrium for a wide spectrum of traits, simultaneously. In turn, it will be possible to redefine genetic prediction based on allele sharing, rather than pedigree relationships and to make breeding value predictions early in the life of the peak sire. Selection will be applied to a much wider range of traits, including those that are directed towards environmental or adaptive outcomes. In parallel, reproductive technologies will continue to advance to allow acceleration of genetic selection, probably including recombination in vitro. Transgenesis and/or mutagenesis will be applied to introduce new genetic variation or desired phenotypes. Traditional livestock systems will continue to evolve towards more intensive integrated farming modes that control inputs and outputs to minimize the impact and improve efficiency. The challenges of the next 50 years can certainly be met, but only if governments reverse the long-term disinvestment in agricultural research.

Maize is one of the most important agricultural crops in Croatia, and was selected for research of the effect of climate warming on yields. The Decision Support System for the Agrotechnology Transfer model (DSSAT) is one of the most utilized crop–weather models in the world, and was used in this paper for the investigation of maize growth and production in the present and future climate. The impact of present climate on maize yield was studied using DSSAT 4.0 with meteorological data from the Zagreb–Maksimir station covering the period 1949–2004. Pedological, physiological and genetic data from a 1999 field maize experiment at the same location were added. The location is representative of the continental climate in central Croatia. The linear trends of model outputs and the non-parametric Mann–Kendall test indicate that the beginning of silking has advanced significantly by 1·4 days/decade since the mid-1990s, and maturity by 4·5 days/decade. It also shows a decrease in biomass by 122 kg/ha and in maize yield by 216 kg/ha in 10 years.

Estimates of the sensitivity of maize growth and yield in future climates were made by changing the initial weather and CO2 conditions of the DSSAT 4.0 model according to the different climatic scenarios for Croatia at the end of the 21st century. Changed climate suggests increases in global solar radiation, minimal temperature and maximal temperature (×1·07, 2 and 4°C, respectively), but a decrease in the amount of precipitation (×0·92), compared with weather data from the period 1949–2004. The reduction of maize yield was caused by the increase in minimal and maximal temperature and the decrease in precipitation amount, related to the present climate, is 6, 12 and 3%, respectively. A doubling of CO2 concentration stimulates leaf assimilation, but maize yield is only 1% higher, while global solar radiation growth by 7% increases evapotranspiration by 3%. Simultaneous application of all these climate changes suggested that the maize growth period would shorten by c. 1 month and maize yield would decrease by 9%, with the main reason for maize yield reduction in Croatia being due to extremely warm conditions in the future climate.

This paper is a brief review summarizing some of the important areas of activity in crop biotechnology likely to be exploited over the medium term (10–20 years), with an emphasis on agronomic traits. It provides details on various approaches to improving the tolerance of crops to abiotic and to biotic stresses. Additionally, it describes recent advances in understanding the factors that affect the intrinsic performance of plants, for example, in terms of their photosynthetic efficiency and their genetic composition. The review also provides a short selection of recently granted patents and patent applications, as this information often identifies those subjects that might be commercially exploited over this period. Finally, it provides a summary of the various predictions of the commercial development pipeline based upon a range of transgenes in major crop species.

Agriculture must provide sustainable food security and economic development to meet future challenges; new cultivars and the use of quality seed will be key components of this. The use of farm-saved seed may increase due to imbalances between income and expenditure associated with farming. The present study characterized the quality of commonly used, and thereby easily available, farm-saved seed in Finland. Farmers provided 657 seed lot samples of spring barley (Hordeum vulgare L.) and spring wheat (Triticum aestivum L.) that they intended to use for sowing. Germination, seed weight, seedling elongation and within-seed-lot variability were analysed. Information was available on region, number of seed generations and cultivar. The specific aims were to identify how many generations of farm-saved seed are generally used by farmers, whether there is any safe generation threshold and the variability of quality of the seed lots. It was found that 0·80–0·84 of barley seed lots exceeded the 0·85 minimum germination requirement for certified seed, but only 0·60 of wheat. The risk of poor establishment was higher in wheat if the seed was not tested: 0·13 of wheat seed lots had germination of ⩽0·65 and 0·06 of ⩽0·50, while for barley the proportions with inadequate germination were 0·03–0·05. At most, >0·30 abnormal seedlings were recorded for barley and >0·50 for wheat. Variation in seed size and seedling length within seed lots was important, and increase in the latter was associated with reduced germination. In combination with up to 0·14 lethal fungus-infected seed, this emphasizes the need for seed upgrading measures. No safe threshold for farm-saved seed generations was determined.

The present study employed the Heckman sample selection model to analyse the two- step process of adaptation to climate change, which initially requires farmers' perception that climate is changing prior to responding to changes through adaptation. Farmers' perception of climate change was significantly related to the age of the head of the household, wealth, knowledge of climate change, social capital and agro-ecological settings. Factors significantly affecting adaptation to climate change were: education of the head of the household, household size, whether the head of the household was male, whether livestock were owned, the use of extension services on crop and livestock production, the availability of credit and the environmental temperature.

The effect of high temperatures (above 25°C) on starch concentration and the morphology of starch granules in the grains of wheat (Triticum aestivum L.) were studied. Wheat plants of cultivars Yangmai 9 (weak-gluten) and Yangmai 12 (medium-gluten) were treated with high temperatures for 3 days at different times after anthesis. The results showed that the starch concentration of grains given a heat-shock treatment above 30°C were lower than those developing at normal temperature in both cultivars. High temperature lowered starch concentration due to the decrease of amylopectin. Under the same temperature, the effect of heat shock from 6 to 8 days after anthesis (DAA) was the greatest, whereas from 36 to 38 DAA the effect was the least. The effects of high temperatures after anthesis on starch-pasting properties were similar to those on starch concentration, especially after 35–40°C treatments. The size, shape and structure of starch granules in wheat grains (determined by electron microscopy) after heat shock were visibly different from the control. When given heat shock during development, the starch granules in mature wheat grains were ellipsoid in shape and bound loosely with a protein sheath in Yangmai 9, while they were damaged and compressed with fissures in Yangmai 12, indicating the differences in resistance to high temperature between cultivars. Ratios of large (type-A) and small (type-B) starch granules significantly decreased under heat shock, which limited the potential sink size for dry matter deposition in the grain.

Information on the performance of the Rothamsted organic carbon turnover model (RothC model) in predicting changes in soil organic carbon (SOC) in short-term experiments is scarce. In Mexico, it was found that these experiments covered not more than 20 years. The purpose of the present study was to evaluate short-term SOC prediction performance of the RothC model in the following systems: (1) farming with residues added (A+R), (2) farming with no added residues (A−R), (3) pure forest stands (F), (4) grasslands (GR) and (5) rangeland (RL). Work was done in five experimental sites: Atécuaro, Michoacán; Santiago Tlalpan, Tlaxcala; El Batán, State of Mexico; Sierra Norte, Oaxaca; and Linares, Nuevo León. Carbon (C) inputs to the soil were plant residues and organic fertilizers, which need to be known to operate the RothC model. The adjustment coefficients for site modelling had R2 values of 0·77–0·95 and model efficiency (EF) was −0·60 to 0·93. When RothC performance was evaluated by a system, R2 values were 0·06–0·92 and EF was −0·24 to 0·90. The low R2 and EF values in rangelands were attributed to the fact that these systems are complex because of heterogeneous vegetation, soil and climate. In general, the evaluation of the RothC model indicates that it can be useful in simulating SOC changes in temperate and warm climate sites and in farming, forest and grassland systems in Mexico.