Contributions of roots and rootstocks to sustainable, intensified crop production

Sustainable intensification is seen as the main route for meeting the world’s increasing demands for food and fibre. As demands mount for greater efficiency in the use of resources to achieve this goal, so the focus on roots and rootstocks and their role in acquiring water and nutrients, and overcoming pests and pathogens, is increasing. The purpose of this review is to explore some of the ways in which understanding root systems and their interactions with soils could contribute to the development of more sustainable systems of intensive production. Physical interactions with soil particles limit root growth if soils are dense, but root–soil contact is essential for optimal growth and uptake of water and nutrients. X-ray microtomography demonstrated that maize roots elongated more rapidly with increasing root–soil contact, as long as mechanical impedance was not limiting root elongation, while lupin was less sensitive to changes in root–soil contact. In addition to selecting for root architecture and rhizosphere properties, the growth of many plants in cultivated systems is profoundly affected by selection of an appropriate rootstock. Several mechanisms for scion control by rootstocks have been suggested, but the causal signals are still uncertain and may differ between crop species. Linkage map locations for quantitative trait loci for disease resistance and other traits of interest in rootstock breeding are becoming available. Designing root systems and rootstocks for specific environments is becoming a feasible target.

Feeding nine billion: the challenge to sustainable crop production

In the recent past there was a widespread working assumption in many countries that problems of food production had been solved, and that food security was largely a matter of distribution and access to be achieved principally by open markets. The events of 2008 challenged these assumptions, and made public a much wider debate about the costs of current food production practices to the environment and whether these could be sustained. As in the past 50 years, it is anticipated that future increases in crop production will be achieved largely by increasing yields per unit area rather than by increasing the area of cropped land. However, as yields have increased, so the ratio of photosynthetic energy captured to energy expended in crop production has decreased. This poses a considerable challenge: how to increase yield while simultaneously reducing energy consumption (allied to greenhouse gas emissions) and utilizing resources such as water and phosphate more efficiently. Given the timeframe in which the increased production has to be realized, most of the increase will need to come from crop genotypes that are being bred now, together with known agronomic and management practices that are currently under-developed.

Implications of climate change for diseases, crop yields and food security

Accelerated climate change affects components of complex biological interactions differentially, often causing changes that are difficult to predict. Crop yield and quality are affected by climate change directly, and indirectly, through diseases that themselves will change but remain important. These effects are difficult to dissect and model as their mechanistic bases are generally poorly understood. Nevertheless, a combination of integrated modelling from different disciplines and multi-factorial experimentation will advance our understanding and prioritisation of the challenges. Food security brings in additional socio-economic, geographical and political factors. Enhancing resilience to the effects of climate change is important for all these systems and functional diversity is one of the most effective targets for improved sustainability.

The role of agronomic research in climate change and food security policy

Societal concern is growing about the consequences of climate change for food systems and, in a number of regions, for food security. There is also concern that meeting the rising demand for food is leading to environmental degradation thereby exacerbating factors in part responsible for climate change, and further undermining the food systems upon which food security is based. A major emphasis of climate change/food security research over recent years has addressed the agronomic aspects of climate change, and particularly crop yield. This has provided an excellent foundation for assessments of how climate change may affect crop productivity, but the connectivity between these results and the broader issues of food security at large are relatively poorly explored; too often discussions of food security policy appear to be based on a relatively narrow agronomic perspective. To overcome the limitation of current agronomic research outputs there are several scientific challenges where further agronomic effort is necessary, and where agronomic research results can effectively contribute to the broader issues underlying food security. First is the need to better understand how climate change will affect cropping systems including both direct effects on the crops themselves and indirect effects as a result of changed pest and weed dynamics and altered soil and water conditions. Second is the need to assess technical and policy options for either reducing the deleterious impacts or enhancing the benefits of climate change on cropping systems while minimising further environmental degradation. Third is the need to understand how best to address the information needs of policy makers and report and communicate agronomic research results in a manner that will assist the development of food systems adapted to climate change. There are, however, two important considerations regarding these agronomic research contributions to the food security/climate change debate. The first concerns scale. Agronomic research has traditionally been conducted at plot scale over a growing season or perhaps a few years, but many of the issues related to food security operate at larger spatial and temporal scales. Over the last decade, agronomists have begun to establish trials at landscape scale, but there are a number of methodological challenges to be overcome at such scales. The second concerns the position of crop production (which is a primary focus of agronomic research) in the broader context of food security. Production is clearly important, but food distribution and exchange also determine food availability while access to food and food utilisation are other important components of food security. Therefore, while agronomic research alone cannot address all food security/climate change issues (and hence the balance of investment in research and development for crop production vis à vis other aspects of food security needs to be assessed), it will nevertheless continue to have an important role to play: it both improves understanding of the impacts of climate change on crop production and helps to develop adaptation options; and also – and crucially – it improves understanding of the consequences of different adaptation options on further climate forcing. This role can further be strengthened if agronomists work alongside other scientists to develop adaptation options that are not only effective in terms of crop production, but are also environmentally and economically robust, at landscape and regional scales. Furthermore, such integrated approaches to adaptation research are much more likely to address the information need of policy makers. The potential for stronger linkages between the results of agronomic research in the context of climate change and the policy environment will thus be enhanced.

Evidence for a climate signal in trends of global crop yield variability over the past 50 years

Low variability of crop production from year to year is desirable for many reasons, including reduced income risk and stability of supplies. Therefore, it is important to understand the nature of yield variability, whether it is changing through time, and how it varies between crops and regions. Previous studies have shown that national crop yield variability has changed in the past, with the direction and magnitude dependent on crop type and location. Whilst such studies acknowledge the importance of climate variability in determining yield variability, it has been assumed that its magnitude and its effect on crop production have not changed through time and, hence, that changes to yield variability have been due to non-climatic factors. We address this assumption by jointly examining yield and climate variability for three major crops (rice, wheat and maize) over the past 50 years. National yield time series and growing season temperature and precipitation were de-trended and related using multiple linear regression. Yield variability changed significantly in half of the crop–country combinations examined. For several crop–country combinations, changes in yield variability were related to changes in climate variability.

Evaluation of diagnostic molecular markers for DUS phenotypic assessment in the cereal crop, barley (Hordeum vulgare ssp. vulgare L.)

The deployment of genetic markers is of interest in crop assessment and breeding programmes, due to the potential savings in cost and time afforded. As part of the internationally recognised framework for the awarding of Plant Breeders’ Rights (PBR), new barley variety submissions are evaluated using a suite of morphological traits to ensure they are distinct, uniform and stable (DUS) in comparison to all previous submissions. Increasing knowledge of the genetic control of many of these traits provides the opportunity to assess the potential of deploying diagnostic/perfect genetic markers in place of phenotypic assessment. Here, we identify a suite of 25 genetic markers assaying for 14 DUS traits, and implement them using a single genotyping platform (KASPar). Using a panel of 169 UK barley varieties, we show that phenotypic state at three of these traits can be perfectly predicted by genotype. Predictive values for an additional nine traits ranged from 81 to 99 %. Finally, by comparison of varietal discrimination based on phenotype and genotype resulted in correlation of 0.72, indicating that deployment of molecular markers for varietal discrimination could be feasible in the near future. Due to the flexibility of the genotyping platform used, the genetic markers described here can be used in any number or combination, in-house or by outsourcing, allowing flexible deployment by users. These markers are likely to find application where tracking of specific alleles is required in breeding programmes, or for potential use within national assessment programmes for the awarding of PBRs.

Empirical test of an agricultural landscape model: the importance of farmer preference for risk aversion and crop complexity

Developing models to predict the effects of social and economic change on agricultural landscapes is an important challenge. Model development often involves making decisions about which aspects of the system require detailed description and which are reasonably insensitive to the assumptions. However, important components of the system are often left out because parameter estimates are unavailable. In particular, measurements of the relative influence of different objectives, such as risk, environmental management, on farmer decision making, have proven difficult to quantify. We describe a model that can make predictions of land use on the basis of profit alone or with the inclusion of explicit additional objectives. Importantly, our model is specifically designed to use parameter estimates for additional objectives obtained via farmer interviews. By statistically comparing the outputs of this model with a large farm-level land-use data set, we show that cropping patterns in the United Kingdom contain a significant contribution from farmer’s preference for objectives other than profit. In particular, we found that risk aversion had an effect on the accuracy of model predictions, whereas preference for a particular number of crops grown was less important. While nonprofit objectives have frequently been identified as factors in farmers’ decision making, our results take this analysis further by demonstrating the relationship between these preferences and actual cropping patterns.

An improved methodology for the recovery of Zea mays and other large crop pollen, with implications for environmental archaeology in the Neotropics

We present a simple sieving methodology to aid the recovery of large cultigen pollen grains, such as maize (Zea mays L.), manioc (Manihot esculenta Crantz), and sweet potato (Ipomoea batatas L.), among others, for the detection of food production using fossil pollen analysis of lake sediments in the tropical Americas. The new methodology was tested on three large study lakes located next to known and/or excavated pre-Columbian archaeological sites in South and Central America. Five paired samples, one treated by sieving, the other prepared using standard methodology, were compared for each of the three sites. Using the new methodology, chemically digested sediment samples were passed through a 53 µm sieve, and the residue was retained, mounted in silicone oil, and counted for large cultigen pollen grains. The filtrate was mounted and analysed for pollen according to standard palynological procedures. Zea mays (L.) was recovered from the sediments of all three study lakes using the sieving technique, where no cultigen pollen had been previously recorded using the standard methodology. Confidence intervals demonstrate there is no significant difference in pollen assemblages between the sieved versus unsieved samples. Equal numbers of exotic Lycopodium spores added to both the filtrate and residue of the sieved samples allow for direct comparison of cultigen pollen abundance with the standard terrestrial pollen count. Our technique enables the isolation and rapid scanning for maize and other cultigen pollen in lake sediments, which, in conjunction with charcoal and pollen records, is key to determining land-use patterns and the environmental impact of pre-Columbian societies.

High Resolution Melt (HRM) analysis is an efficient tool to genotype EMS mutants in complex crop genomes

Background: Targeted Induced Loci Lesions IN Genomes (TILLING) is increasingly being used to generate and identify mutations in target genes of crop genomes. TILLING populations of several thousand lines have been generated in a number of crop species including Brassica rapa. Genetic analysis of mutants identified by TILLING requires an efficient, high-throughput and cost effective genotyping method to track the mutations through numerous generations. High resolution melt (HRM) analysis has been used in a number of systems to identify single nucleotide polymorphisms (SNPs) and insertion/deletions (IN/DELs) enabling the genotyping of different types of samples. HRM is ideally suited to high-throughput genotyping of multiple TILLING mutants in complex crop genomes. To date it has been used to identify mutants and genotype single mutations. The aim of this study was to determine if HRM can facilitate downstream analysis of multiple mutant lines identified by TILLING in order to characterise allelic series of EMS induced mutations in target genes across a number of generations in complex crop genomes. Results: We demonstrate that HRM can be used to genotype allelic series of mutations in two genes, BraA.CAX1a and BraA.MET1.a in Brassica rapa. We analysed 12 mutations in BraA.CAX1.a and five in BraA.MET1.a over two generations including a back-cross to the wild-type. Using a commercially available HRM kit and the Lightscanner™ system we were able to detect mutations in heterozygous and homozygous states for both genes. Conclusions: Using HRM genotyping on TILLING derived mutants, it is possible to generate an allelic series of mutations within multiple target genes rapidly. Lines suitable for phenotypic analysis can be isolated approximately 8-9 months (3 generations) from receiving M3 seed of Brassica rapa from the RevGenUK TILLING service.

An easily implemented agro-hydrological procedure with dynamic root simulation for water transfer in the crop-soil system: validation and application

Models for water transfer in the crop-soil system are key components of agro-hydrological models for irrigation, fertilizer and pesticide practices. Many of the hydrological models for water transfer in the crop-soil system are either too approximate due to oversimplified algorithms or employ complex numerical schemes. In this paper we developed a simple and sufficiently accurate algorithm which can be easily adopted in agro-hydrological models for the simulation of water dynamics. We used a dual crop coefficient approach proposed by the FAO for estimating potential evaporation and transpiration, and a dynamic model for calculating relative root length distribution on a daily basis. In a small time step of 0.001 d, we implemented algorithms separately for actual evaporation, root water uptake and soil water content redistribution by decoupling these processes. The Richards equation describing soil water movement was solved using an integration strategy over the soil layers instead of complex numerical schemes. This drastically simplified the procedures of modeling soil water and led to much shorter computer codes. The validity of the proposed model was tested against data from field experiments on two contrasting soils cropped with wheat. Good agreement was achieved between measurement and simulation of soil water content in various depths collected at intervals during crop growth. This indicates that the model is satisfactory in simulating water transfer in the crop-soil system, and therefore can reliably be adopted in agro-hydrological models. Finally we demonstrated how the developed model could be used to study the effect of changes in the environment such as lowering the groundwater table caused by the construction of a motorway on crop transpiration. (c) 2009 Elsevier B.V. All rights reserved.

A universal agro-hydrological model for water and nitrogen cycles in the soil-crop system SMCR_N: critical update and further validation

Agro-hydrological models have widely been used for optimizing resources use and minimizing environmental consequences in agriculture. SMCRN is a recently developed sophisticated model which simulates crop response to nitrogen fertilizer for a wide range of crops, and the associated leaching of nitrate from arable soils. In this paper, we describe the improvements of this model by replacing the existing approximate hydrological cascade algorithm with a new simple and explicit algorithm for the basic soil water flow equation, which not only enhanced the model performance in hydrological simulation, but also was essential to extend the model application to the situations where the capillary flow is important. As a result, the updated SMCRN model could be used for more accurate study of water dynamics in the soil-crop system. The success of the model update was demonstrated by the simulated results that the updated model consistently out-performed the original model in drainage simulations and in predicting time course soil water content in different layers in the soil-wheat system. Tests of the updated SMCRN model against data from 4 field crop experiments showed that crop nitrogen offtakes and soil mineral nitrogen in the top 90 cm were in a good agreement with the measured values, indicating that the model could make more reliable predictions of nitrogen fate in the crop-soil system, and thus provides a useful platform to assess the impacts of nitrogen fertilizer on crop yield and nitrogen leaching from different production systems. (C) 2010 Elsevier B.V. All rights reserved.

Assessing the benefits of crop albedo bio-geoengineering

It has been proposed that growing crop varieties with higher canopy albedo would lower summer-time temperatures over North America and Eurasia and provide a partial mitigation of global warming ('bio-geoengineering') (Ridgwell et al 2009 Curr. Biol. 19 1–5). Here, we use a coupled ocean–atmosphere–vegetation model (HadCM3) with prescribed agricultural regions, to investigate to what extent the regional effectiveness of crop albedo bio-geoengineering might be influenced by a progressively warming climate as well as assessing the impacts on regional hydrological cycling and primary productivity. Consistent with previous analysis, we find that the averted warming due to increasing crop canopy albedo by 0.04 is regionally and seasonally specific, with the largest cooling of ~1 °C for Europe in summer whereas in the low latitude monsoonal SE Asian regions of high density cropland, the greatest cooling is experienced in winter. In this study we identify potentially important positive impacts of increasing crop canopy albedo on soil moisture and primary productivity in European cropland regions, due to seasonal increases in precipitation. We also find that the background climate state has an important influence on the predicted regional effectiveness of bio-geoengineering on societally-relevant timescales (ca 100 years). The degree of natural climate variability and its dependence on greenhouse forcing that are evident in our simulations highlights the difficulties faced in the detection and verification of climate mitigation in geoengineering schemes. However, despite the small global impact, regionally focused schemes such as crop albedo bio-geoengineering have detection advantages.

Creation of the WATCH Forcing Data and Its Use to Assess Global and Regional Reference Crop Evaporation over Land during the Twentieth Century

The Water and Global Change (WATCH) project evaluation of the terrestrial water cycle involves using land surface models and general hydrological models to assess hydrologically important variables including evaporation, soil moisture, and runoff. Such models require meteorological forcing data, and this paper describes the creation of the WATCH Forcing Data for 1958–2001 based on the 40-yr ECMWF Re-Analysis (ERA-40) and for 1901–57 based on reordered reanalysis data. It also discusses and analyses modelindependent estimates of reference crop evaporation. Global average annual cumulative reference crop evaporation was selected as a widely adopted measure of potential evapotranspiration. It exhibits no significant trend from 1979 to 2001 although there are significant long-term increases in global average vapor pressure deficit and concurrent significant decreases in global average net radiation and wind speed. The near-constant global average of annual reference crop evaporation in the late twentieth century masks significant decreases in some regions (e.g., the Murray–Darling basin) with significant increases in others.

Ice internal friction: Standard theoretical perspectives on friction codified, adapted for the unusual rheology of ice, and unified

Sea ice contains flaws including frictional contacts. We aim to describe quantitatively the mechanics of those contacts, providing local physics for geophysical models. With a focus on the internal friction of ice, we review standard micro-mechanical models of friction. The solid's deformation under normal load may be ductile or elastic. The shear failure of the contact may be by ductile flow, brittle fracture, or melting and hydrodynamic lubrication. Combinations of these give a total of six rheological models. When the material under study is ice, several of the rheological parameters in the standard models are not constant, but depend on the temperature of the bulk, on the normal stress under which samples are pressed together, or on the sliding velocity and acceleration. This has the effect of making the shear stress required for sliding dependent on sliding velocity, acceleration, and temperature. In some cases, it also perturbs the exponent in the normal-stress dependence of that shear stress away from the value that applies to most materials. We unify the models by a principle of maximum displacement for normal deformation, and of minimum stress for shear failure, reducing the controversy over the mechanism of internal friction in ice to the choice of values of four parameters in a single model. The four parameters represent, for a typical asperity contact, the sliding distance required to expel melt-water, the sliding distance required to break contact, the normal strain in the asperity, and the thickness of any ductile shear zone.