The history of genetic modification and improvement of perennial grasses used for turf and sport can be traced back to the earliest events leading to the evolution of traits such as perenniality, asexual reproduction by rhizomes or stolons, apical dominance and hardening or acclimation responses to environmental stress. Human influences on perennial grasses likely began with the dawn of agriculture and the domestication of livestock about 8–10000 years ago with the movement of grasses from forest margins and meadows to pastures and cropland. As agrarian cultures found more time for leisure and recreation, perennial grasses became multi-functional, taking on a greater role with the invention of ball games, sports and a sod industry. Early human selection of superior turf grasses was largely based on individual clones that were vegetatively propagated for commercial purposes, dating back as far as 12th century Japan. The science of turf breeding began in 1962 with the initiation of extensive efforts to collect superior clones from old turf sods in highly stressful environments, followed by numerous cycles of recurrent selection for turf traits in harsh environments and under realistic mowing regimes. These efforts spawned many public and commercial breeding ventures and thousands of cultivars that have spread throughout the world, improving the quality, persistence and functionality of turf for many uses.

Studies of single soil organisms, while useful in specialized cases, e.g. Rhizobia and mycohrrizae, do not yield information on the functioning of the soil ecosystem. This is because most important soil processes, e.g. carbon and nitrogen mineralization, depend upon interactions between entire suites of organisms, many of which still await identification and most of which remain unculturable.

For many purposes, treating the soil microbial community as a single, undifferentiated unit, the soil microbial biomass (defined as all soil organisms <5000 μm3 volume), has much to commend it. It is analogous to studying the forest rather than an individual tree and uniquely permits an understanding of the soil–plant–microbe system as a whole, rather than studying only a small part. The present paper reviews the development of methods to measure microbial dynamics over the last century, the evolution of biomass methodologies and how they have helped the study of crucial soil processes such as nutrient and carbon cycling. Possible future directions for this research are also discussed and an explanation set forth of why the manipulation of this huge population (easily comprising 10 tonnes per hectare of living microbial cells in UK arable soils) has, so far, proved elusive.

In our Editorial in the first issue of 2005 (Naylor & Wiseman 2005), we celebrated the Journal's achievement of 100 years of publication and introduced the Centenary Reviews. We have been gratified at the interest in the Centenary Reviews and the willingness of authors to consider writing them. This, coupled with the observation that the first volume of the Journal of Agricultural Science was 1905–06, has enabled us to continue the series of Centenary Reviews into the 2006 volume. We thank the various authors for their time and effort in writing these reviews. In 2006 we anticipate Centenary Reviews on international wheat breeding, crop losses, lentils, yield forecasting and grapevine evolution, amongst others.

Despite the successes of the Green Revolution, about a billion people are still undernourished and food security in the developing world faces new challenges in terms of population growth, reduced water resources, climate change and decreased public sector investment. It is also becoming widely recognized that poverty is a cause of environmental degradation, conflict and civil unrest. Internationally coordinated agricultural research can play a significant role in improving food security by deploying promising new technologies as well as adapting those with well-established impact.

In addition to the genetic challenges of crop improvement, agriculturalists must also embrace the problems associated with a highly heterogeneous and unpredictable environment. Not only are new genetic tools becoming more accessible, but a new generation of quantitative tools are available to enable better definition of agro-ecosystems, of cultivar by environment interactions, and of socio-economic issues, while satellite imagery can help predict crop yields on large scales. Identifying areas of low genetic diversity – for example as found in large tracts of South Asia – is an important aspect of reducing vulnerability to disease epidemics. Global strategies for incorporating durable disease resistance genes into a wider genetic background, as well as participatory approaches that deliver a fuller range of options to farmers, are being implemented to increase cultivar diversity.

The unpredictable effects of environment on productivity can be buffered somewhat by crop management practices that maintain healthy soils, while reversing the consequences of rapid agricultural intensification on soil degradation. Conservation agriculture is an alternative strategy that is especially pertinent for resource-poor farmers.

The potential synergy between genetic improvement and innovative crop management practices has been referred to as the Doubly Green Revolution. The unique benefits and efficiency of the international collaborative platform are indisputable when considering the duplications that otherwise would have been required to achieve the same impacts through unilateral or even bilateral programmes. Furthermore, while the West takes for granted public support for crucial economic and social issues, this is not the case in a number of less-developed countries where the activities of International Agricultural Research Centres (IARCs) and other development assistance organizations can provide continuity in agricultural research and infrastructure.

The Journal of Agricultural Science, Cambridge has been a fixture in dissemination of crop simulation models and the concepts and data upon which they are built since the inception of computers and computer modelling in the mid-20th century. To quantify the performance of a crop simulation model, model outputs are compared with observed values using statistical measures of bias, i.e. the difference between simulated and observed values. While applying these statistical measures is unambiguous for the experienced user, the same cannot always be said of determining the observed or simulated values. For example, differences in accessing crop development can be due to the subjectivity of an observer or to a definition that is difficult to apply in the field. Methods of determining kernel number, kernel mass, and yield can vary among researchers, which can add errors to comparisons between experimental observations and simulated results. If kernel moisture is not carefully determined and reported it can add error to values of grain yield and kernels per unit area regardless of the protocol used to collect these data. Inaccurate determination of kernel moisture will also influence computation of grain protein or oil content. Problems can also be associated with input data to the simulation models. Under-reporting of precipitation values from tipping bucket rain gauges, commonly found on automated weather stations, can introduce errors in results from crop simulation models. Using weather data collected too far from an experimental site may compound problems with input data. The importance of accurate soil and weather input data increases as the environment becomes more limiting for plant growth and development. Problems can also arise from algorithms that calculate important parameters in a model, such as daylength, which is used to determine a photoperiod response. Errors in the calculation of photoperiod can be related to the definition of sunrise and sunset and the inclusion or exclusion of civil twilight or to the improper calculation of the solar declination. Even the simple calculation of the daily mean air temperature can have an impact on the results from a non-linear algorithm. During a period when crop simulation modelling is moving in the difficult direction of incorporating genomic-based inputs, the critical importance of careful and accurate collection and reporting of field data and the need to develop robust algorithms that accommodate readily available or easily acquired input data should not be forgotten. As scientists we have an obligation to provide the best available knowledge and understanding as possible. Avoiding potential pitfalls will assist us as we develop new knowledge and understanding and incorporate these concepts into new or modified crop simulation models.

Oilseed rape yields on farms have not increased in several countries, including the UK, since the mid 1980s. This may be because the yield potential for the environment in these countries has been reached, or due to a lack of genetic improvement, or due to changes in the environment of the growing crop caused by crop management practices. The present paper investigates which of these factors may be causing the yield of farm crops in the UK to remain at 3 t/ha. The yield potential for the UK that would be possible by combining the best characteristics that have been observed with the best crop management is estimated to be significantly greater than average farm yields at 6·5 t/ha (90 g/kg moisture content). In order to achieve 6·5 t/ha, a crop would have a flower cover of less than 0·4 to facilitate the production of 130000 seeds/m2. Seed filling must last 46 days and have a solar radiation use efficiency of 0·75 g of seed/MJ. A tenth of the yield must come from stem reserves and the seed weight must be 5·0 mg. All of these characteristics have been achieved; therefore the challenge lies in combining these traits within the same crop. The ultimate yield potential for water retentive soils in the UK is estimated at 9·2 t/ha. This would require new characteristics to be bred into the crop and represents a long-term target. In the UK, new oilseed rape varieties are introduced each year and the yield of these varieties under optimum growing conditions is estimated to have increased by 62 kg/ha/year between 1978 and 2005. Lack of genetic improvement is therefore unlikely to explain the halt in farm yields. There have been trends for farm crops to be grown in shorter rotations, established using minimal cultivations rather than ploughing and to receive less nitrogen fertilizer. Sulphur applications have increased, but probably have not kept pace with the reduction in deposition from the atmosphere. Fungicide applications to farm crops are less than applied to the variety testing system and are unlikely to offer complete disease control. It is concluded that a combination of these crop management factors has caused the halt in yield improvement on UK farms.

During the past century wheat breeders have produced a large number of genetically improved wheat lines and varieties. This activity has led to widespread adoption of improved varieties, a steady increase in average wheat yields during the past 4–5 decades and major contributions to food security and poverty reduction. The rate of generation and adoption of improved varieties, and therefore the time lag from varietal release to widespread use, varies across regions. The remarkable success of wheat improvement hinges on the decisions of millions of farmers to adopt, or replace older wheat varieties with superior material. The present paper summarizes studies on the determinants of adoption. Because adoption is a necessary but not sufficient condition for economic impact, the present paper synthesizes key assessments of impact from different farming systems in developing countries.

The results of recent trials for winter wheat (Triticum aestivum L.) have influenced farming practice in the UK by encouraging the use of lower seed rates. Spink et al. (2000) have demonstrated that, particularly if sown early, wheat can compensate for reduced plant populations by increased tiller production.

Results from seed-rate trials are usually analysed separately for each environment or each combination of environment and variety, and not combined into a single model. They therefore address the question of what the best seed rate would have been for each combination, rather than answer the more relevant question of what rate to choose for a future site. The current paper presents a Bayesian method for combining data from seed-rate trials and choosing optimum seed rates: this method can incorporate information on seed and treatment costs, crop value and covariates. More importantly, for use as an advisory tool, it allows incorporation of expert knowledge of the crop and of the target site.

The method is illustrated using two series of trials: the first, carried out at two sites in 1997–99, investigated the effects of sowing date and variety in addition to seed rate. The second was conducted at seven sites in 2001–03 and included latitude and certain management factors. Recommended seed rates based on these series vary substantially with sowing date and latitude.

Two non-linear dose-response functions are fitted to the data, the widely used exponential-plus-linear function and the inverse-quadratic function (Nelder 1966). The inverse-quadratic function is found to provide a better fit to the data than the exponential-plus-linear and the latter function gives estimated optimum rates which are as much as 40% lower. The economic consequences of using one function rather than the other are not great in these circumstances.

The method is found to be robust to changes in the prior distribution and to other changes in the model used for dependence of yield on sowing date, latitude, variety and management factors.

Despite the importance of selection for quality characteristics in plant improvement programmes, literature on experimental design and statistical analysis for these traits is scarce. Most quality traits are obtained from multi-phase experiments in which plant varieties are first grown in a field trial then further processed in the laboratory. In the present paper a general mixed model approach for the analysis of multi-phase data is described, with particular emphasis on quality trait data that are often highly unbalanced and involve substantial sources of non-genetic variation and correlation. Also detailed is a new approach for experimental design that employs partial replication in all phases. The motivation for this was the high cost of obtaining quality trait data, thus the need to limit the total number of samples tested, but still allow use of the mixed model analysis. A simulation study is used to show that the combined use of the new designs and mixed model analysis has substantial benefits in terms of the genetic gain from selection.

Smallholder cropping systems are a vital component in the agricultural sectors of tropical Asia, especially in the developing nations. These systems are important for producing food and providing a livelihood to a major proportion of the populations of Asia. While the rice systems, usually cultivated under puddled conditions are considered stable, the upland or highland units, which provide a range of food, fibre and feed commodities, are generally situated on marginal lands. Low soil fertility, erosion, sub-optimal crop management and subsistence farming conditions characterize these units. Hence, these units require improved but low cost strategies to reverse the trend of lower productivity, loss of sustainability and most importantly, the loss of livelihood for the farming populations. Among the many strategies available, the regeneration of soil fertility through agronomic measures would be a useful and easily adoptable method of enhancing productivity of tropical Asian upland smallholding farming units. The methods available include the revival of age-old traditions such as adding organic matter directly to soils, green manuring and mimicking forest ecosystems through agroforestry. Agronomic measures using plants to enrich the soil and regenerate its supporting capacity are presented in the present paper. Relevant examples are cited to highlight the potential of these methods for regenerating productivity of the upland smallholder farming units and more importantly the agro-based livelihood of a large majority of the populations of tropical Asia.

For over 40 years a collaborative network of publicly funded international wheat scientists has made a significant contribution to food security in the developing world. Thousands of modern wheat varieties (MVs) have been released for use in both favourable and marginal environments on well over 50 million hectares. The yield increases associated with genetic improvement in yield potential and adaptation to biotic and abiotic stresses are well documented. Millions of small-scale farmers in the developing world have benefited. While this so-called ‘Green Revolution’ displaced landraces in favour of more productive MVs, these and other genetic resources, held in trust by international organizations, have been utilized to improve the inherent genetic diversity of modern varieties. Furthermore, the result of increased yields reduced the need to bring natural ecosystems under cultivation, by as much as a billion hectares.

Although international wheat breeding has its origins in the 1940s, recognition of a common scientific basis of agricultural problems worldwide was highlighted by the creation of International Agricultural Research Centres (IARCs) which included the International Maize and Wheat Improvement Centre (CIMMYT) established in 1965. This grew into a larger network called the Consultative Group for International Agricultural Research (CGIAR) now comprising 15 IARCs, including the International Centre for Agricultural Research in the Dry Areas (ICARDA) established in Syria in 1977, another key player in the international wheat and barley breeding network. Two of the major coordination responsibilities of CIMMYT are maintaining the world collection of wheat genetic resources – a public good protected by international treaty – and the facilitation of the International Wheat Nurseries.

After the initial impact of the Green Revolution in high production zones through exploitation of Rht-B1 and Rht-D1 dwarfing genes in conjunction with disease resistance, international breeding encompassed more challenging environments through, for example, international shuttle breeding between Brazil and Mexico to overcome problems associated with acid soils that restricted adoption of MVs. Another example is drought, which affects at least 30 million ha of wheat in the developing world. The approach focused initially on exploiting the inherent yield potential and disease resistance of MVs and later combined this with new stress-adaptive traits from wild wheat ancestors through wide crossing techniques. Adoption of modern varieties has increased substantially in drier areas between 1990 and 1997. In all environments, possibly the greatest threat to productivity is disease, especially those caused by fungal pathogens. International wheat breeding has placed great emphasis on genetic control of disease since resource-poor farmers generally lack the means to control diseases chemically.

Turkey is one of the most important durum wheat (T. turgidum L. var. durum Desf.) producers in West Asia and North Africa (WANA). There appears to have been a lack of progress in wheat yields in WANA over recent decades. Most of the modern cultivars grown in WANA are related to crosses produced by the International Maize and Wheat Improvement Center (CIMMYT). During 1999 and 2000, a chronological set of 11 cultivars related to CIMMYT crosses was evaluated using two irrigation regimes near Şanlıurfa, Turkey.

Average yields ranged from 386 g/m2 (local cultivar, Karakılçık-33) to 614 g/m2 (Ege-88). When wheat cultivars were grown with irrigation until physiological maturity, cessation of irrigation near anthesis reduced average grain yields of all cultivars by 6·2–25·7%. Since the introduction of the first generation of CIMMYT cultivars in 1975, CIMMYT grain yields have increased by about 0·60% per year compared with that of Karakılçık-33. This rate increased up to 1·08% per year until 1988. No further progress in yield was measured for varieties released in the 1990s. The average rate was 0·76% per year. After the introduction of the CIMMYT cultivars, yield changes fitted better in a quadratic function. Compared with Karakılçık-33, the yield increases of CIMMYT cultivars have resulted from an increase in harvest index associated with reduced height and the development of more and heavier grains. Grain quality traits decreased with the introduction of the first CIMMYT cultivar but recovered slightly thereafter with no clear trend. The results are discussed with consideration of breeding priorities and specific WANA conditions.

The difference between the bread wheat and feed wheat prices in the UK (the premium) is an important influence on behaviour throughout the entire grain chain. The aim of the present study was to quantify the influence of grain quality and other factors on interannual variation in the premium calculated as a proportion of the feed price. A hypothetical model of the UK wheat economy was devised, appropriate annual national data from 1982 to 2000 were collected for each component and multiple regression was used to develop a statistical model for the premium.

The statistical model included livestock numbers (calculated as pig equivalents), Hagberg falling number and wheat stocks, which together explained 0·80 of the interannual variation in the premium. A high premium was associated with high livestock numbers, low Hagberg falling number and low wheat stocks. These variables were included in the hypothetical model because: livestock numbers represent demand for feed wheat; Hagberg falling number is a quality criterion for purchase of bread wheat with a low value indicating poor quality and thus a smaller supply of bread wheat; wheat stocks are one of the sources of supply of wheat. It was concluded that of the 16 supply, demand or price variables in the hypothetical model the main variables associated with the premium from 1982 to 2000 were demand for feed wheat, quality of the wheat harvest and carry-over of wheat from the previous harvest.

The impact of organic, compared with conventional, farming practices on N leaching loss was studied for Danish mixed dairy and arable farms using an N balance approach based on representative data. On mixed dairy farms, a simple N balance method was used to estimate N surplus and N leaching loss. On arable farms, the simple N balance method was unreliable due to changes in the soil N pool. Consequently, the Farm ASSEssment Tool (FASSET) simulation model was used to estimate N surplus, N leaching loss and the changes in the soil N pool.

The study found a lower N leaching loss from organic than conventional mixed dairy farms, primarily due to lower N inputs. On organic arable farms, the soil N pool increased over time but the N leaching loss was comparable with conventional arable farms. The soil N pool was increased primarily by organic farming practices and incorporation of straw. The highest increase in the soil N pool was seen on soils with a low initial level of organic matter. The N leaching loss was dependent on soil type, the use of catch crops and the level of soil organic matter, whereas incorporation of straw had a minor effect. N leaching was highest on sandy soils with a high level of soil organic matter and no catch crops. The present results stress the importance of using representative data from organic and conventional farming practices in comparative studies of N leaching loss. Lack of representative data has been a major weakness of previous comparisons on N leaching losses on organic and conventional farms.

Varietal identification is an important aspect of crop research and utilization. Identification using computer-based image analysis could be an alternative to visual identification. However, the effectiveness of image analysis systems needs to be established under various real conditions. Three wheat varieties were sown on three different dates. Variation in the grain size and shape of these varieties, brought about by changes in the environmental conditions, was measured using Comprehensive Image Processing Software (CIPS). Some parameters showed considerable grain-to-grain variation, which was either inherent or due to environmental changes during grain filling. Euclidean distances were calculated using either means of all the parameters (ED1), or using only those parameters that did not show a high coefficient of variation (ED2). For samples of the same variety sown at different times, Euclidean distances were smaller compared with samples of different varieties, indicating that grains of the same variety resembled one another. By using the criterion of minimum Euclidean distance it was possible to distinguish between varieties, in spite of variation in grain shape and size due to environmental conditions. It was possible to identify correctly an unknown sample, taken as a test case.

Lentil (Lens culinaris Medikus subsp. culinaris) was among the first crops domesticated and has become an important food legume crop in the farming and food systems of many countries globally. Its seed is a rich source of protein, minerals, and vitamins for human nutrition, and the straw is a valued animal feed. Its ability in nitrogen and carbon sequestration improves soil nutrient status, which in turn provides sustainability in production systems. In the current paper, research progress achieved in lentil improvement at national and international levels is reviewed.

Since the late 1970s there have been significant national and international lentil improvement programmes, with the main objectives being to develop phenologically adapted, stress resistant and high-yielding cultivars with improved production packages.

Systematic research on lentil started recently, compared to other early-domesticated crops. During the last two and a half decades, research progress has been made in various aspects of the crop. Large numbers of germplasm have been collected, evaluated and preserved at national and international levels, with the International Center for Agricultural Research in the Dry Areas (ICARDA) holding the largest collection of cultivated and wild germplasm accessions. A major effort has been made to study the genetic variation in the world germplasm collection, in order to understand local adaptation and to develop specific research programmes. Genotypes with resistance to various biotic and abiotic stresses, particularly resistance to vascular wilt, rust and Ascochyta blight have been identified, and directly exploited or used in breeding programmes. New genotypes have been bred with good standing ability, suitable for mechanical harvest for West Asia and North Africa. Through introduction and hybridization, the genetic base of lentil has been broadened, most particularly in South Asia, by breaking an ancient genetic bottleneck.

Agronomic practices, including seeding time, seed rate, tillage requirements, soil type, and weed control, are optimized locally and improved production packages have been developed to realize higher yield. To date, a total of 91 improved cultivars have been released globally, emanating from genetic material supplied by ICARDA. Due to adoption of improved varieties combined with production technologies, the average global productivity has increased from 611 kg/ha to 966 kg/ha, and total production from 1·3 million tonnes to 3·8 million tonnes in the last three decades. Research at the molecular level, including construction of a lentil genetic linkage map, identification of molecular markers, and genetic transformation, has progressed considerably.

In temperate regions, grassland provides most of the feed requirements for ruminants. Its management has implications for landscape and environmental quality as well as agricultural production. The present paper reviews the key developments in grassland management, production and utilization during the 20th century, focusing primarily on the UK but drawing on research and practice from other areas. Increased production from grassland has arisen from improved understanding of soil and plant nutrition, plant physiology and cultivar improvement, while improved understanding of feed evaluation, ruminant nutrition, grazing management and silage technology have contributed to increased utilization of grassland under grazing and cutting. Permanent and long-term swards occupied most of the total grassland area at both the beginning and end of the century, but inputs of nitrogen resulted in greatly increased herbage production, particularly from the 1960s; this, combined with reseeding and early cutting for silage, led to reduced botanical diversity with ryegrass dominance in lowland areas. Forage legumes were highly regarded at the beginning of the century, then decreased in many areas, but are again recognized as having a key role in low- and medium-input systems. Recognition of the environmental implications of grassland management has increased since the 1980s. This includes the need to reduce nutrient emissions in grassland agriculture, and also the role of grassland in biodiversity protection, carbon sequestration and landscape quality. Research is increasingly focused on addressing these issues and on integrating agricultural management with environmental protection. Improved nutrient management, legume-based systems and agri-environmental schemes, as well as interest in the food quality attributes of particular systems and grassland communities, are important in the medium term. In the longer term the effects of population increase, competition for other land uses and the impacts of climate change could impact on global food supplies and affect future grassland management in the temperate zones.

The current study, performed in Castilla-La Mancha (Spain) in 2003–04, reports the growth, nutrition, tolerance to transplanting stress, and resistance to Verticillium dahliae of olive plantlets (Olea europaea L.) inoculated with different arbuscular mycorrhizal (AM) fungi (Glomus mosseae, G. intraradices and G. claroideum). Inoculated plants tolerated the stress of transplanting better than non-inoculated plants. Compared with controls, plantlets inoculated with any of these three Glomus species grew taller, had more and longer shoots, and showed higher plant N, P and K concentrations. However, colonization seemed to have no influence on resistance to V. dahliae.

Productivity of crops grown for human consumption is at risk due to the incidence of pests, especially weeds, pathogens and animal pests. Crop losses due to these harmful organisms can be substantial and may be prevented, or reduced, by crop protection measures. An overview is given on different types of crop losses as well as on various methods of pest control developed during the last century.

Estimates on potential and actual losses despite the current crop protection practices are given for wheat, rice, maize, potatoes, soybeans, and cotton for the period 2001–03 on a regional basis (19 regions) as well as for the global total. Among crops, the total global potential loss due to pests varied from about 50% in wheat to more than 80% in cotton production. The responses are estimated as losses of 26–29% for soybean, wheat and cotton, and 31, 37 and 40% for maize, rice and potatoes, respectively. Overall, weeds produced the highest potential loss (34%), with animal pests and pathogens being less important (losses of 18 and 16%). The efficacy of crop protection was higher in cash crops than in food crops. Weed control can be managed mechanically or chemically, therefore worldwide efficacy was considerably higher than for the control of animal pests or diseases, which rely heavily on synthetic chemicals. Regional differences in efficacy are outlined. Despite a clear increase in pesticide use, crop losses have not significantly decreased during the last 40 years. However, pesticide use has enabled farmers to modify production systems and to increase crop productivity without sustaining the higher losses likely to occur from an increased susceptibility to the damaging effect of pests.

The concept of integrated pest/crop management includes a threshold concept for the application of pest control measures and reduction in the amount/frequency of pesticides applied to an economically and ecologically acceptable level. Often minor crop losses are economically acceptable; however, an increase in crop productivity without adequate crop protection does not make sense, because an increase in attainable yields is often associated with an increased vulnerability to damage inflicted by pests.