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Humanity's survival depends on crops-the green line standing between us and calamity. To meet ever expanding human needs, crops must become increasingly more productive, mainly through genetic gains that exploit diverse plant genetic resources (PGR), the raw materials for crop breeding. For millennia, PGR have been conserved by individuals, communities, and organizations. These stewards of our agricultural future have been nearly as diverse as the PGR that they have conserved. Their invaluable roles in underpinning the security of global agriculture have largely been underappreciated. Furthermore, the challenges and complexity of successful PGR stewardship have been inadequately recognized. This paper pays tribute to these stewards' characteristic attributes and their contributions to PGR conservation and sustainable use. It describes the pervasive impacts of PGR on crop agriculture and explains how numerous factors have affected PGR stewardship capacities. Plant genetic resource stewardship involves many different components, which are typically conducted over extended timeframes. Sustained, adequate support for PGR maintenance, a key component, has been the exception rather than the rule. Past and present PGR stewardship successes and challenges furnish numerous lessons for meeting future demands. Such lessons include recognizing the importance to PGR stewardship of: dedicated and diverse PGR stewards, continual and persistent financial support for PGR genebanks and their staffs, protecting crop wild relatives, and safeguarding genebank collections from extreme weather and introduced pests and pathogens. In the future, PGR stewardship might be conducted more frequently and more adequately by multiinstitutional networks enabled by advances in information technology and artificial intelligence. [ABSTRACT FROM AUTHOR]

This paper provides an outline of the biobased economy, its perspectives for agriculture and, more particularly, for development purposes. Possibilities of development of biobased products, advanced biofuels, and viable and efficient biorefinery concepts are explored. The paper lists non-fuel bioproducts (e.g., chemicals, pharmaceuticals, biopolymers) and presents basic principles and development options for biorefineries that can be used to generate them alongside biofuels, power, and by-products. One of the main challenges is to capture more value from existing crops without compromising the needs and possibilities of small-scale, less endowed farmers. Biobased products offer the most development perspectives, combining large market volumes with medium to high price levels. Consequently, the most can be expected from products like fine chemicals, lubricants, and solvents. In addition, biosolar cells can help to relax pressures on biomass production systems while decentralized production chains can serve local needs for energy, materials, and nutrients as their requirement for viable economic development are linked to larger markets. Research challenges include development of such production and market chains, and of biosolar cells and selection of model crops that offer perspectives for less favored producers and underdeveloped rural areas. [ABSTRACT FROM AUTHOR]

Eco-efficiency in the simplest of terms is about achieving more with less-more agricultural outputs, in terms of quantity and quality, for less input of land, water, nutrients, energy, labor, or capital. The concept of eco-efficiency encompasses both the ecological and economic dimensions of sustainable agriculture. Social and institutional dimensions of sustainability, while not explicitly captured in eco-efficiency measures, remain critical barriers and opportunities on the pathway toward more eco-efficient agriculture. This paper explores the multidimensionality of the eco-efficiency concept as it applies to agriculture across diverse spatial and temporal scales, from cellular metabolisms through to crops, farms, regions, and eco- systems. These dimensions of eco-efficiency are integrated through the presentation and exploration of a framework that explores an efficiency frontier between agricultural outputs and inputs, investment, or risk. The challenge for agriculture in the coming decades will be to increase productivity of agricultural lands in line with the increasing demands for food and fiber. Achieving such eco-efficiency, while addressing risk and variability, will be a major challenge for future agriculture. Often, risk will be a critical issue influencing adoption; it needs explicit attention in the diagnosis and intervention steps toward enhancing eco-efficiency. To ensure food security, systems analysis and modeling approaches, combined with farmer-focused experimentation and resource assessment, will provide the necessary robust approaches to raise the eco-efficiency of agricultural systems. [ABSTRACT FROM AUTHOR]

This paper reviews recent progress in wheat (Triticum aestivum L.), rice (Oryza sativa L.), and maize (Zea mays L.) yields resulting from substantial breeding efforts in mostly favorable environments and examines its physiological basis. Breeding and improved agronomy lift potential yield (PY), namely yield with the best variety and management in the absence of manageable abiotic and biotic stresses, and PY increase is a key component of progress in farm yield (FY), the other component being closure of the PY to FY gap. Changes in PY and FY are reviewed for several key production regions, namely the United Kingdom and the Yaqui Valley of Mexico for wheat, Japan and Central Luzon in the Philippines for rice, and Iowa and briefly sub Saharan Africa for maize The PY growth rates have fallen and are currently generally no more than 1% per annum and usually much less. The trajectory of FY with time often closely parallels PY, but, especially in developing countries, there remain large yield gaps. In at least one instance (maize in Iowa) the gap between PY and FY appears to be closing rapidly. Current genetic progress is linked to increased bio- mass accumulation, and this will remain the way for- ward in the future given the limits to increased harvest index (HI). There is evidence that recent progress is related to increased photosynthesis (e.g., greater radiation use efficiency (RUE) at the canopy level and/or maximum photosynthetic rate Pmax at saturating irradiance at the leaf level) before and around anthesis. There is no theoretical reason why this trend cannot continue, especially given the vast genetic resources already found within each crop species. However, it will not be easily or cheaply accomplished, so prospects for higher rates of potential yield growth appear to be limited, notwithstanding new molecular tools and claims to the contrary. Closing the yield gap, therefore, becomes more important. Many factors are involved, but breeding can also help farmers achieve this through, for example, improved host plant resistance. [ABSTRACT FROM AUTHOR]

Information about several papers discussed at a forum sponsored by the Consultative Group on International Agricultural Research (CGIAR) on the relevance of science research for agricultural development is presented. Topics include identifying scientific advances to improve agriculture and natural resources in developed countries. It mentions issues on the effectiveness of biofuels as a means of agricultural development as well as its limitations and resource problems.

Knowledge, information, and data-and the social and physical infrastructures that carry them-are widely recognized as key building blocks for more sustainable agriculture, effective agricultural science, and productive partnerships among the global research community. Through investments in e-Science infrastructure and collaboration on one hand, and rapid developments in digital devices and connectivity in rural areas, the ways that scientists, academics and development workers create share and apply agricultural knowledge is being transformed through the use of information and communication technologies (ICTs). This paper examines some trends and opportunities associated with the use of these lCTs in agricultural science for development [ABSTRACT FROM AUTHOR]

This paper discusses how research on natural resources management systems can address the complexity of such systems. Three different types of complexity are identified: ontological, societal, and analytical. Significant ideas for "dealing with complexity" are extracted from U.S., Swiss, and U.K. literature on inter- and transdisciplinary research. Based on this, the "boundary work" framework is presented to systematically think through complexity challenges. The framework suggests that inter- and transdisciplinary research on natural research management requires three types of work: (i) the development of suitable boundary concepts that allow thinking of the multidimensionality of NRM issues; (ii) the configuration of adequate boundary objects as devices and methods that allow acting in situations of incomplete knowledge nonlinearity and divergent interests and (iii) the shaping of conducive boundary settings in which these concepts, devices, and methods can be fruitfully developed and effectively put to work. The ideas presented are illustrated with an example of a research program on sustain- able land and water management in Uzbekistan. The concluding section highlights three issues important for increasing the effectiveness of inter- and transdisciplinary research on natural resources management. [ABSTRACT FROM AUTHOR]

Plant evolution in climatic areas with marked seasonal changes has led to species adaptation to periods of high and low temperatures and drought and to significant changes in their morphological structure and annual developmental cycles. One characteristic of these adaptations is the state of dormancy, in which the plants do not exhibit any visible external growth. This paper reviews dormancy and florogenesis as main components of the survival strategies of perennial herbaceous plants. Summer dormancy protects plants from negative effects of water deficit and high temperatures on vegetative and reproductive organs, and forces plant species to schedule their active development in more favorable seasons. Mechanisms of summer survival vary among species and provide different modes of adaptation to harsh environments. The interrelationship between florogenesis and dormancy is most probably controlled in meristems, where the survival strategy of the plant, including vegetative growth, flowering, drought tolerance, and formation of storage organs, is determined. Mechanisms by which summer dormancy confers summer drought survival warrant further investigation for improving agronomic and environmental traits of perennial plants. [ABSTRACT FROM AUTHOR]

Rising research costs, broadening goals, intellectual property rights, and other concerns increase the need for robust management of crop improvement data. The data model of the International Crop Information System (ICIS) allows breeding processes to be recorded unambiguously in a relational database. This paper describes this model, which underlies the Genealogical Management System (GMS) of ICIS. The model recognizes three classes of methods by which genetic material is advanced. Generative methods such as crossing or mutagenesis increase variation. Derivative methods usually involve selection, and maintenance methods conserve the genetic makeup of germplasm, such as in seed multiplications. Unlike systems that only track pedigrees, the model describes steps of selection. Applications are illustrated for self-pollinating, outcrossing, and clonally propagated crops. The ICIS GMS is in use for species including rice (Oryza sativa L.), wheat (Triticum aestivum L.), maize (Zea mays L.), potato (Solanum tuberosum L.), common bean (Phaseolus vulgaris L.), lesquerella [Lesquerella fend/en (Gray) S. Wats.], and witloof chicory (Cichorium intybus L.). The International Rice Information System, based on ICIS, holds more than 2.6 million unique identifiers for germplasm accessions, crosses, populations, and lines, requiring about 900 megabytes of storage space, which can easily be managed on a personal computer. The GMS model appears suited for widespread use in managing data on crop improvement. [ABSTRACT FROM AUTHOR]

Cassava (Manihot esculenta Crantz) is a vitally important food source for many people in developing tropical countries. There are significant opportunities for improving the compositional qualities and pest resistance of cassava, and modern biotechnology is expected to play an important role in these improvements. The testing and development of genetically modified cassava will of course be subject to regulatory review, and experimental field trials must be performed in a fashion that prevents gene flow from the regulated plants. Methods to ensure reproductive isolation will be derived from a fundamental understanding of the biology of the crop. A current and comprehensive document on cassava reproductive biology is not yet available but is essential to guide regulators and scientists in planning and evaluating measures for reproductive isolation of confined field trials. This paper compiles a current view of the reproductive biology of cassava for use in experimental design and regulation of confined field trials. With the current state of knowledge on gene flow and seed dormancy in cassava, three methods for reproductive isolation of regulated experimental plots may currently be recommended: (i) removal of flower buds before flowering, (ii) destruction of plants before flowering, and (iii) floral bagging to contain pollen and seed. Areas for further research in cassava biology and biosafety are suggested. [ABSTRACT FROM AUTHOR]

This paper reviews some traditional and more recent methods for analyzing unreplicated experiments. Such experiments have presented a challenge to statisticians throughout their involvement in agricultural research. At Rothamsted this began in 1919, when R.A. Fisher was appointed to analyze the accumulated data from the classical field experiments. Fisher's experiences with the classicals, which had virtually no replication, must have contributed to his inclusion of replication as one of the key features of a well-designed experiment. Nevertheless, Fisher made good use of Rothamsted's data, for example in his study of the influence of rainfall on yields from the Broadbalk. He also devised the randomization test, which can be used to analyze unreplicated data. More recently, Broadbalk has also been used to study climate change and sustainability. Newer developments have been concerned to find alternatives to use, instead of blocking, to take account of the spatial variation within an experiment. The resulting methods for modeling spatial correlations have allowed experimenters to obtain more precise estimates of treatment effects—or to decrease numbers of replicates—and they can also provide reliable analyses of unreplicated treatments. [ABSTRACT FROM AUTHOR]

The Additive Main effects and Multiplicative Interaction (AMMI) model, Genotype main effects and Genotype × Environment interaction (GGE) model, and Principal Components Analysis (PCA) are singular value decomposition (SVD) based statistical analyses often applied to yield-trial data. This paper presents a systematic comparison, using both statistical theory and empirical investigations, while considering both current practices and best practices. Agricultural researchers using these analyses face two inevitable choices. First is the choice of a model for visualizing data. AMMI is decidedly superior, not for statistical reasons, but rather for agricultural reasons. AMMI partitions the overall variation into genotype main effects, environment main effects, and genotype x environment interactions. These three sources of variation present agricultural researchers with different challenges and opportunities, so it is best to handle them separately, while still considering all three in an integrated manner. Second is the choice of a member of a given model family for gaining predictive accuracy. AMMI, GGE, and other SVD-based model families are essentially equivalent, but best practices require model diagnosis for each individual dataset to determine which member is most predictively accurate. Making these two choices well allows researchers to extract more usable information from their data, thereby increasing efficiency and accelerating progress. [ABSTRACT FROM AUTHOR]

Field trials with perennial grasses may often be conducted at several locations with different starting years. A key issue in the analysis of such trials is the distinction between effects of calendar years, which are associated with external environmental variation, and harvest years, which represent internal yield formation processes of the perennial crop. Furthermore, analysis of field trials with perennial grasses needs to account for serial correlation of observations on the same plot from consecutive harvest years. Such analyses are conveniently implemented using mixed models. Here, we consider series of trials when the target region is subdivided into several zones. We show how cultivar yield means per zone can be estimated borrowing strength across zones. The proposed mixed models are illustrated using simulated data generated by employing variance component estimates from real experiments. It is shown in simulations that best linear unbiased prediction (BLUP) can provide more precise zone-specific mean estimates than alternative methods. [ABSTRACT FROM AUTHOR]

Increasingly, funding agencies are investing in integrated and transdisciplinary research to tackle "grand challenge" priority areas, critical for sustaining agriculture and protecting the environment. Coordinating multidisciplinary research teams capable of addressing these priority areas, however, presents its own unique set of challenges, ranging from bridging across multiple disciplinary perspectives to achieve common questions and methods to facilitating engagement in holistic and integrative thinking that promotes linkages from scholarship to societal needs. We propose that structural equation modeling (SEM) can provide a powerful framework for synergizing multidisciplinary research teams around grand challenge issues. Structural equation modeling can integrate both visual and statistical expression of complex hypotheses at all stages of the research process, from planning to analysis. Three elements of the SEM framework are particularly beneficial to multidisciplinary research teams; these include (i) a common graphical language that transcends disciplinary boundaries, (ii) iterative, critical evaluation of complex hypotheses involving manifest and latent variables and direct and indirect interactions, and (iii) enhanced opportunities to discover unanticipated interactions or causal pathways as empirical data are tested statistically against the model. Using our ongoing multidisciplinary, multisite field investigation of climate change adaptation and mitigation in annual row crop agroecosystems as a case study, we demonstrate the value of the SEM framework for project design, coordination, and implementation and provide recommendations for its broader application as a means to more effectively engage and address issues of critical societal concern. [ABSTRACT FROM AUTHOR]

The high molecular weight gluteniri subunits (IrIMW-GS) are essential in determining breadmaking quality, and knowing their composition can help in making appropriate decisions to improve wheat (Triticum aestivum L.) quality. The HMW-GS compositions of 189 Chinese wheat landraces (CWLs), 61 introduced lines (ILs), and 840 Chinese improved varieties (ClVs) were irivestigated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) in this study. The aim was to identify novel HMWGS alleles and to compare the genetic diversity ~mong the three groups. A total of 31 HMW-GS alleles and 86 allele combinations were found in all accessions. For CWL and CIV, the predominant pattern was (null, 7+8, 2+12), with a frequency of 71.6 and 26.0%, respectively. The predominant pattern in the IL was (null, 7+9,2+12) with a frequency of 13.6%. The IL had the largest variation and the average index of genetic variation (H). The H was 0.6117, whereas CWL and CIV had H values of 0.2275 and 0.51 61, respectively. In addition, the present study showed that an increase of 7+9 and 5+10 in the CIV came from the use of foreign parents. The results revealed that the IL was an important reservoir for improving Chinese wheat-quality characteristics such as grain protein content, hardness, and sodium dodecyl sulfate (SOS) sedimentation. Although the genetic variation in the CWL was low, it contained novel alleles (lBx7.1* and 1By8.1*), which indicated that this group was also a potential resource for wheat-quality improvement. [ABSTRACT FROM AUTHOR]

Exploitation of the available genetic resources around the world requires information about the relationships and genetic diversity present among genebank collections. These relations ôan be established by defining for each crop a small but informative set of accessions, together with a small set of reliable molecular markers, that can be used as reference material. In this study, various strategies to arrive at small but informative reference sets are discussed. For selection of accessions, we proposed genetic distance optimization (GDOpt) method, which selects a subset of accessions that optimally represent the accessions not included in the core collection. The performance of GDOpt was ôompared with Core Hunter, an advanced stochastic local search algorithm for selecting core subsets. For the selection of molecular markërs, we evaluated (i) the backward elimination (BE) method and (ii) methods based on principal component analysis (PCA). We examined the performance of the proposed methodologies using five real datasets. Relative to average distance between an accession and the nearest selected accession (representativeness), GDOpt out performed Core Hunter. However, Core Hunter outperformed GDOpt with respect to allelic richness. The BE performed much better than other methods in selecting subsets of markers. Methods based on PCA showed that, for practical purposes, the inclusion of the first few (two or three) principal components (PCs) was often sufficient. To obtain robust and highquality reference sets of accessions and markers we advise a combination of GDOpt (for accessions) and BE or methods based on PCA using a few PCs (for subsets of markers). [ABSTRACT FROM AUTHOR]

Molecular markers have emerged as useful tools to assess the genetic diversity across crops. In lentil, molecular markers are limited. The objective of the study was to explore crossgenera transferability of sequence tagged microsatellite site (STMS) markers from related legumes and assess their utility in lentils. Thirty lentil (Lens culinaris Medik. subsp. culinaris) accessions were evaluated for genetic similarity analysis using cross-genera STMS markers. Thirty-nine STMS markers amplified 68 alleles with an average of 1.74 alleles per locus. Twenty lentil-specific STMS markers produced a total of 36 amplicons, of which 90% (18) markers were polymorphic. A maximum of four alleles were obtained with primers SSR13 and SSR19. Of 47 STMS markers from other legume genera, only 19 markers produced 32 scorable amplicons, and only 58% (11) of the amplified markers exhibited polymorphism. The polymorphism information content values observed with lentil specific markers ranged from 0.02 to 0.99, while for transferrable markers it ranged from 0.06 to 0.84. Maximum genetic similarity was observed between 'NDL1' and 'LH84-8' (0.942) and minimum between PL234 and Precoz' (0.709). The dendrogram based on Jaccard's similarity coefficients showed limited genetic variability among the cultivars included in the present study. A combination of lentil-specific and transferrable STMS markers was successfully used for identification of genetic similarity in lentil germplasm. [ABSTRACT FROM AUTHOR]

We compared yield, genetic gain, and morphology for two sets of maize (Zea mays L.) hybrids using yield test plots grown in China at different pianting densities. One set comprised 29 Chinise maize hybrids that were individually widely grown in China during 1964 through 2001. A second set comprised U.S. hybrids that were used either during the 1960s or during the 2000s. The US. hybrids had higher yields for both 1960s and 2000s comparisons. United States hybrids showed highest genetic gain (81 kg ha-1) at the highest planting density (67,550 plants ha1) whereas the highest rate of gain for Chinese hybrids was 62 kg ha1 at the medium planting density (52,500 plants ha1). Unlike the Chinese hybrids, U.S. hybrids showed significant interaption with planting density. Chronologically, all hybrids showed morphological changes for many characteristics, often at different rates, and occasionally in different directions. Pedig~ree and molecular marker data showed U.S. and Chinese hybrids to be very different germplasm with decades-old U.S. germplasm contributing even to recently developed and widely used Chinese hybrids. Chinese maize agricultural production can rapidly and significantly benefit from adopting breeding and agronomic strategies that allow for improved yield under higher planting densities. [ABSTRACT FROM AUTHOR]