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The information seeking behaviors of primary care providers was studied in an effort to understand their needs while seeing patients. Based on patterns previously established in the literature, the primary care providers in the VA Stars and Stripes Healthcare System were surveyed to learn their medical knowledge resource habits and preferences while seeing patients. The survey indicated preference for an electronic resource, and with the advent of the electronic medical record, this resource was implemented and usage tracked over a three year period. The research methods, findings, observations, and conclusions are described. [ABSTRACT FROM AUTHOR]

Investigates the effects of the genes Lf, Sn, E, and Hr on time to flowering in pea, which is determined by genetically controlled responses to photoperiod and temperature. Inverse relationship between temperature sensitivity within the thermal plane and dominance of gene; Variation in the critical photoperiod with temperature changes in all photoperiod-sensitive genotypes.

Abstract Background Core podiatry involves treatment of the nails, corns and callus and also giving footwear and foot health advice. Though it is an integral part of current podiatric practice little evidence is available to support its efficacy in terms of research and audit data. This information is important in order to support the current NHS commissioning process where services are expected to provide data on standards including outcomes. This study aimed to increase the evidence base for this area of practice by conducting a multi-centre audit in 8 NHS podiatry departments over a 1-year period. Methods The outcome measure used in this audit was the Podiatry Health Questionnaire which is a self completed short measure of foot health including a pain visual analogue scale and a section for the podiatrist to rate an individual's foot health based on their podiatric problems. The patient questionnaire was completed by individuals prior to receiving podiatry care and then 2 weeks after treatment to assess the effect of core podiatry in terms of pain and foot health. Results 1047 patients completed both questionnaires, with an age range from 26–95 years and a mean age of 72.9 years. The podiatrists clinical rating at baseline showed 75% of patients had either slight or moderate podiatric problems. The differences in questionnaire and visual analogue scores before and after treatment were determined according to three categories – better, same, worse and 75% of patients' scores either remained the same or improved after core podiatry treatment. A student t-test showed a statistical significant difference in pre and post treatment scores where P < 0.001, though the confidence interval indicated that the improvement was relatively small. Conclusion Core podiatry has been shown to sustain or improve foot health and pain in 75% of the patients taking part in the audit. Simple outcome measures including pain scales should be used routinely in podiatric practice to assess the affect of different aspects of treatments and improve the evidence base for podiatry.

The twin pandemics of COVID-19 and structural racism brought into focus health disparities and disproportionate impacts of disease on communities of color. Health equity has subsequently emerged as a priority. Recognizing that the future of health care will be informed by advanced information technologies including artificial intelligence (AI), machine learning, and algorithmic applications, the authors argue that to advance towards states of improved health equity, health information professionals need to engage in and encourage the conduct of research at the intersections of health equity, health disparities, and computational biomedical knowledge (CBK) applications. Recommendations are provided with a means to engage in this mobilization effort., (Copyright © 2024 Nancy J. Allee, Gerald Perry, Gabriel R.Rios, Joshua C. Rubin, Vignesh Subbian, Deborah E. Swain, Terrie R. Wheeler.)

Technology advances and collaborations with information technology and computer science groups have enabled library services to expand into new domains. Listening to user needs, eliminating administrative burden and saving users time remain strong foundations on which to build new library services enabled by technology. Examples of what is now possible is described, including service to user groups, successes, failures and challenges. Although technology advances have enabled library service enhancements to all user groups, special emphasis on new library services in support of the research enterprise is discussed. As Lindberg and Humphreys predicted in 2015, the research enterprise's need for responsible curation of research data has created new opportunities for library services and examples of those services are discussed. As technology continues to advance, new library services are expected to emerge. These may include regulatory and compliance services. By developing these services with user feedback to save users time and expedite their work, and in collaboration with technology experts, libraries can expect to offer sustainable and valued services for years to come., (© 2022 The Authors Health Information and Libraries Journal published by John Wiley & Sons Ltd on behalf of Health Libraries Group.)

Academic institutions need to maintain publication lists for thousands of faculty and other scholars. Automated tools are essential to minimize the need for direct feedback from the scholars themselves who are practically unable to commit necessary effort to keep the data accurate. In relying exclusively on clustering techniques, author disambiguation applications fail to satisfy key use cases of academic institutions. Algorithms can perfectly group together a set of publications authored by a common individual, but, for them to be useful to an academic institution, they need to programmatically and recurrently map articles to thousands of scholars of interest en masse. Consistent with a savvy librarian's approach for generating a scholar's list of publications, identity-driven authorship prediction is the process of using information about a scholar to quantify the likelihood that person wrote certain articles. ReCiter is an application that attempts to do exactly that. ReCiter uses institutionally-maintained identity data such as name of department and year of terminal degree to predict which articles a given scholar has authored. To compute the overall score for a given candidate article from PubMed (and, optionally, Scopus), ReCiter uses: up to 12 types of commonly available, identity data; whether other members of a cluster have been accepted or rejected by a user; and the average score of a cluster. In addition, ReCiter provides scoring and qualitative evidence supporting why particular articles are suggested. This context and confidence scoring allows curators to more accurately provide feedback on behalf of scholars. To help users to more efficiently curate publication lists, we used a support vector machine analysis to optimize the scoring of the ReCiter algorithm. In our analysis of a diverse test group of 500 scholars at an academic private medical center, ReCiter correctly predicted 98% of their publications in PubMed., Competing Interests: The authors have declared that no competing interests exist.

Academic medical centers need to make sensitive data from electronic health records, payer claims, genomic pipelines, and other sources available for analytical and educational purposes while ensuring privacy and security. Although many studies have described warehouses for collecting biomedical data, few studies have described secure computing environments for analysis of sensitive data. This case report describes the Weill Cornell Medicine Data Core with respect to user access, data controls, hardware, software, audit, and financial considerations. In the 2.5 years since launch, the Data Core has supported more than 200 faculty, staff, and students across nearly 60 research and education projects. Other institutions may benefit from adopting elements of the approach, including tools available on Github, for balancing access with privacy and security.

Establishment of a new bioinformatics service at the Samuel J. Wood Library of Weill Cornell Medicine was successfully achieved through reference to existing programs and utilization of established success factors. Setting the vision, focusing on the essentials, designing for value, and implementing continuous improvement through feedback, helped to create a successful and integrated bioinformatics service for the medical research community.

Objective: The paper provides a review of current practices related to evaluation support services reported by seven biomedical and research libraries., Methods: A group of seven libraries from the United States and Canada described their experiences with establishing evaluation support services at their libraries. A questionnaire was distributed among the libraries to elicit information as to program development, service and staffing models, campus partnerships, training, products such as tools and reports, and resources used for evaluation support services. The libraries also reported interesting projects, lessons learned, and future plans., Results: The seven libraries profiled in this paper report a variety of service models in providing evaluation support services to meet the needs of campus stakeholders. The service models range from research center cores, partnerships with research groups, and library programs with staff dedicated to evaluation support services. A variety of products and services were described such as an automated tool to develop rank-based metrics, consultation on appropriate metrics to use for evaluation, customized publication and citation reports, resource guides, classes and training, and others. Implementing these services has allowed the libraries to expand their roles on campus and to contribute more directly to the research missions of their institutions., Conclusions: Libraries can leverage a variety of evaluation support services as an opportunity to successfully meet an array of challenges confronting the biomedical research community, including robust efforts to report and demonstrate tangible and meaningful outcomes of biomedical research and clinical care. These services represent a transformative direction that can be emulated by other biomedical and research libraries., Competing Interests: CONFLICTS OF INTEREST The authors have no conflict of interest.

Agricultural systems science generates knowledge that allows researchers to consider complex problems or take informed agricultural decisions. The rich history of this science exemplifies the diversity of systems and scales over which they operate and have been studied. Modeling, an essential tool in agricultural systems science, has been accomplished by scientists from a wide range of disciplines, who have contributed concepts and tools over more than six decades. As agricultural scientists now consider the "next generation" models, data, and knowledge products needed to meet the increasingly complex systems problems faced by society, it is important to take stock of this history and its lessons to ensure that we avoid re-invention and strive to consider all dimensions of associated challenges. To this end, we summarize here the history of agricultural systems modeling and identify lessons learned that can help guide the design and development of next generation of agricultural system tools and methods. A number of past events combined with overall technological progress in other fields have strongly contributed to the evolution of agricultural system modeling, including development of process-based bio-physical models of crops and livestock, statistical models based on historical observations, and economic optimization and simulation models at household and regional to global scales. Characteristics of agricultural systems models have varied widely depending on the systems involved, their scales, and the wide range of purposes that motivated their development and use by researchers in different disciplines. Recent trends in broader collaboration across institutions, across disciplines, and between the public and private sectors suggest that the stage is set for the major advances in agricultural systems science that are needed for the next generation of models, databases, knowledge products and decision support systems. The lessons from history should be considered to help avoid roadblocks and pitfalls as the community develops this next generation of agricultural systems models.

Background: Two new directors were each charged by their institutions to catalyze transformational change in their libraries and to develop dynamic and evolving information ecosystems ready for the information challenges of the future. The directors approached this transformational change using a strategic, forward-looking approach., Results: This paper presents examples of actions that served as catalysts for change at the two libraries using Kotter's Eight Steps of Change as a framework. Small and large changes are critical for successfully transforming library services, resources, and personnel., Conclusions: Libraries are faced with incredible pressure to adapt to meet emerging and intensifying information needs on today's academic medical campuses. These pressures offer an opportunity for libraries to accelerate their evolution at the micro and macro levels. This commentary reports the expansion of new services and areas of support, enhancement of professional visibility of the libraries on their campuses, and overall, a more positive and productive environment at the respective institutions.

This paper presents ideas for a new generation of agricultural system models that could meet the needs of a growing community of end-users exemplified by a set of Use Cases. We envision new data, models and knowledge products that could accelerate the innovation process that is needed to achieve the goal of achieving sustainable local, regional and global food security. We identify desirable features for models, and describe some of the potential advances that we envisage for model components and their integration. We propose an implementation strategy that would link a "pre-competitive" space for model development to a "competitive space" for knowledge product development and through private-public partnerships for new data infrastructure. Specific model improvements would be based on further testing and evaluation of existing models, the development and testing of modular model components and integration, and linkages of model integration platforms to new data management and visualization tools.

We review the current state of agricultural systems science, focusing in particular on the capabilities and limitations of agricultural systems models. We discuss the state of models relative to five different Use Cases spanning field, farm, landscape, regional, and global spatial scales and engaging questions in past, current, and future time periods. Contributions from multiple disciplines have made major advances relevant to a wide range of agricultural system model applications at various spatial and temporal scales. Although current agricultural systems models have features that are needed for the Use Cases, we found that all of them have limitations and need to be improved. We identified common limitations across all Use Cases, namely 1) a scarcity of data for developing, evaluating, and applying agricultural system models and 2) inadequate knowledge systems that effectively communicate model results to society. We argue that these limitations are greater obstacles to progress than gaps in conceptual theory or available methods for using system models. New initiatives on open data show promise for addressing the data problem, but there also needs to be a cultural change among agricultural researchers to ensure that data for addressing the range of Use Cases are available for future model improvements and applications. We conclude that multiple platforms and multiple models are needed for model applications for different purposes. The Use Cases provide a useful framework for considering capabilities and limitations of existing models and data.

Myofibroblast differentiation is characterized by an increased level of expression of cytoskeletal smooth muscle α-actin. In human and murine fibroblasts, the gene encoding smooth muscle α-actin (Acta2) is tightly regulated by a network of transcription factors that either activate or repress the 5' promoter-enhancer in response to environmental cues signaling tissue repair and remodeling. Purine-rich element-binding protein B (Purβ) suppresses the expression of Acta2 by cooperatively interacting with the sense strand of a 5' polypurine sequence containing an inverted MCAT cis element required for gene activation. In this study, we evaluated the chemical basis of nucleoprotein complex formation between the Purβ repressor and the purine-rich strand of the MCAT element in the mouse Acta2 promoter. Quantitative single-stranded DNA (ssDNA) binding assays conducted in the presence of increasing concentrations of monovalent salt or anionic detergent suggested that the assembly of a high-affinity nucleoprotein complex is driven by a combination of electrostatic and hydrophobic interactions. Consistent with the results of pH titration analysis, site-directed mutagenesis revealed several basic amino acid residues in the intermolecular (R267) and intramolecular (K82 and R159) subdomains that are essential for Purβ transcriptional repressor function in Acta2 promoter-reporter assays. In keeping with their diminished Acta2 repressor activity in fibroblasts, purified Purβ variants containing an R267A mutation exhibited reduced binding affinity for purine-rich ssDNA. Moreover, certain double and triple-point mutants were also defective in binding to the Acta2 corepressor protein, Y-box-binding protein 1. Collectively, these findings establish the repertoire of noncovalent interactions that account for the unique structural and functional properties of Purβ.

Hybrid vigour may help overcome the negative effects of climate change in rice. A popular rice hybrid (IR75217H), a heat-tolerant check (N22), and a mega-variety (IR64) were tested for tolerance of seed-set and grain quality to high-temperature stress at anthesis at ambient and elevated [CO(2)]. Under an ambient air temperature of 29 °C (tissue temperature 28.3 °C), elevated [CO(2)] increased vegetative and reproductive growth, including seed yield in all three genotypes. Seed-set was reduced by high temperature in all three genotypes, with the hybrid and IR64 equally affected and twice as sensitive as the tolerant cultivar N22. No interaction occurred between temperature and [CO(2)] for seed-set. The hybrid had significantly more anthesed spikelets at all temperatures than IR64 and at 29 °C this resulted in a large yield advantage. At 35 °C (tissue temperature 32.9 °C) the hybrid had a higher seed yield than IR64 due to the higher spikelet number, but at 38 °C (tissue temperature 34-35 °C) there was no yield advantage. Grain gel consistency in the hybrid and IR64 was reduced by high temperatures only at elevated [CO(2)], while the percentage of broken grains increased from 10% at 29 °C to 35% at 38 °C in the hybrid. It is concluded that seed-set of hybrids is susceptible to short episodes of high temperature during anthesis, but that at intermediate tissue temperatures of 32.9 °C higher spikelet number (yield potential) of the hybrid can compensate to some extent. If the heat tolerance from N22 or other tolerant donors could be transferred into hybrids, yield could be maintained under the higher temperatures predicted with climate change.

Episodes of high temperature at anthesis, which in rice is the most sensitive stage to temperature, are expected to occur more frequently in future climates. The morphology of the reproductive organs and pollen number, and changes in anther protein expression, were studied in response to high temperature at anthesis in three rice (Oryza sativa L.) genotypes. Plants were exposed to 6 h of high (38 degrees C) and control (29 degrees C) temperature at anthesis and spikelets collected for morphological and proteomic analysis. Moroberekan was the most heat-sensitive genotype (18% spikelet fertility at 38 degrees C), while IR64 (48%) and N22 (71%) were moderately and highly heat tolerant, respectively. There were significant differences among the genotypes in anther length and width, apical and basal pore lengths, apical pore area, and stigma and pistil length. Temperature also affected some of these traits, increasing anther pore size and reducing stigma length. Nonetheless, variation in the number of pollen on the stigma could not be related to measured morphological traits. Variation in spikelet fertility was highly correlated (r=0.97, n=6) with the proportion of spikelets with > or = 20 germinated pollen grains on the stigma. A 2D-gel electrophoresis showed 46 protein spots changing in abundance, of which 13 differentially expressed protein spots were analysed by MS/MALDI-TOF. A cold and a heat shock protein were found significantly up-regulated in N22, and this may have contributed to the greater heat tolerance of N22. The role of differentially expressed proteins and morphology during anther dehiscence and pollination in shaping heat tolerance and susceptibility is discussed.

Crop production is inherently sensitive to variability in climate. Temperature is a major determinant of the rate of plant development and, under climate change, warmer temperatures that shorten development stages of determinate crops will most probably reduce the yield of a given variety. Earlier crop flowering and maturity have been observed and documented in recent decades, and these are often associated with warmer (spring) temperatures. However, farm management practices have also changed and the attribution of observed changes in phenology to climate change per se is difficult. Increases in atmospheric [CO(2)] often advance the time of flowering by a few days, but measurements in FACE (free air CO(2) enrichment) field-based experiments suggest that elevated [CO(2)] has little or no effect on the rate of development other than small advances in development associated with a warmer canopy temperature. The rate of development (inverse of the duration from sowing to flowering) is largely determined by responses to temperature and photoperiod, and the effects of temperature and of photoperiod at optimum and suboptimum temperatures can be quantified and predicted. However, responses to temperature, and more particularly photoperiod, at supraoptimal temperature are not well understood. Analysis of a comprehensive data set of time to tassel initiation in maize (Zea mays) with a wide range of photoperiods above and below the optimum suggests that photoperiod modulates the negative effects of temperature above the optimum. A simulation analysis of the effects of prescribed increases in temperature (0-6 degrees C in +1 degree C steps) and temperature variability (0% and +50%) on days to tassel initiation showed that tassel initiation occurs later, and variability was increased, as the temperature exceeds the optimum in models both with and without photoperiod sensitivity. However, the inclusion of photoperiod sensitivity above the optimum temperature resulted in a higher apparent optimum temperature and less variability in the time of tassel initiation. Given the importance of changes in plant development for crop yield under climate change, the effects of photoperiod and temperature on development rates above the optimum temperature clearly merit further research, and some of the knowledge gaps are identified herein.

One of the major factors contributing to the failure of new wheat varieties is seasonal variability in end-use quality. Consequently, it is important to produce varieties which are robust and stable over a range of environmental conditions. Recently developed sample preparation methods have allowed the application of FT-IR spectroscopic imaging methods to the analysis of wheat endosperm cell wall composition, allowing the spatial distribution of structural components to be determined without the limitations of conventional chemical analysis. The advantages of the methods, described in this paper, are that they determine the composition of endosperm cell walls in situ and with minimal modification during preparation. Two bread-making wheat cultivars, Spark and Rialto, were selected to determine the impact of environmental conditions on the cell-wall composition of the starchy endosperm of the developing and mature grain, focusing on the period of grain filling (starting at about 14 days after anthesis). Studies carried out over two successive seasons show that the structure of the arabinoxylans in the endosperm cell walls changes from a highly branched form to a less branched form. Furthermore, during development the rate of restructuring was faster when the plants were grown at higher temperature with restricted water availability from 14 days after anthesis with differences in the rate of restructuring occurring between the two cultivars.

The impacts of climate change on crop productivity are often assessed using simulations from a numerical climate model as an input to a crop simulation model. The precision of these predictions reflects the uncertainty in both models. We examined how uncertainty in a climate (HadAM3) and crop General Large-Area Model (GLAM) for annual crops model affects the mean and standard deviation of crop yield simulations in present and doubled carbon dioxide (CO2) climates by perturbation of parameters in each model. The climate sensitivity parameter (gamma, the equilibrium response of global mean surface temperature to doubled CO2) was used to define the control climate. Observed 1966-1989 mean yields of groundnut (Arachis hypogaea L.) in India were simulated well by the crop model using the control climate and climates with values of gamma near the control value. The simulations were used to measure the contribution to uncertainty of key crop and climate model parameters. The standard deviation of yield was more affected by perturbation of climate parameters than crop model parameters in both the present-day and doubled CO2 climates. Climate uncertainty was higher in the doubled CO2 climate than in the present-day climate. Crop transpiration efficiency was key to crop model uncertainty in both present-day and doubled CO2 climates. The response of crop development to mean temperature contributed little uncertainty in the present-day simulations but was among the largest contributors under doubled CO2. The ensemble methods used here to quantify physical and biological uncertainty offer a method to improve model estimates of the impacts of climate change.

Changes in both the mean and the variability of climate, whether naturally forced, or due to human activities, pose a threat to crop production globally. This paper summarizes discussions of this issue at a meeting of the Royal Society in April 2005. Recent advances in understanding the sensitivity of crops to weather, climate and the levels of particular gases in the atmosphere indicate that the impact of these factors on crop yields and quality may be more severe than previously thought. There is increasing information on the importance to crop yields of extremes of temperature and rainfall at key stages of crop development. Agriculture will itself impact on the climate system and a greater understanding of these feedbacks is needed. Complex models are required to perform simulations of climate variability and change, together with predictions of how crops will respond to different climate variables. Variability of climate, such as that associated with El Niño events, has large impacts on crop production. If skilful predictions of the probability of such events occurring can be made a season or more in advance, then agricultural and other societal responses can be made. The development of strategies to adapt to variations in the current climate may also build resilience to changes in future climate. Africa will be the part of the world that is most vulnerable to climate variability and change, but knowledge of how to use climate information and the regional impacts of climate variability and change in Africa is rudimentary. In order to develop appropriate adaptation strategies globally, predictions about changes in the quantity and quality of food crops need to be considered in the context of the entire food chain from production to distribution, access and utilization. Recommendations for future research priorities are given.

Rhizobium leguminosarum synthesizes polyhydroxybutyrate and glycogen as its main carbon storage compounds. To examine the role of these compounds in bacteroid development and in symbiotic efficiency, single and double mutants of R. leguminosarum bv. viciae were made which lack polyhydroxybutyrate synthase (phaC), glycogen synthase (glgA), or both. For comparison, a single phaC mutant also was isolated in a bean-nodulating strain of R. leguminosarum bv. phaseoli. In one large glasshouse trial, the growth of pea plants inoculated with the R. leguminosarum bv. viciae phaC mutant were significantly reduced compared with wild-type-inoculated plants. However, in subsequent glasshouse and growth-room studies, the growth of pea plants inoculated with the mutant were similar to wildtype-inoculated plants. Bean plants were unaffected by the loss of polyhydroxybutyrate biosynthesis in bacteroids. Pea plants nodulated by a glycogen synthase mutant, or the glgA/phaC double mutant, grew as well as the wild type in growth-room experiments. Light and electron micrographs revealed that pea nodules infected with the glgA mutant accumulated large amounts of starch in the II/III interzone. This suggests that glycogen may be the dominant carbon storage compound in pea bacteroids. Polyhydroxybutyrate was present in bacteria in the infection thread of pea plants but was broken down during bacteroid formation. In nodules infected with a phaC mutant of R. leguminosarum bv. viciae, there was a drop in the amount of starch in the II/III interzone, where bacteroids form. Therefore, we propose a carbon burst hypothesis for bacteroid formation, where polyhydroxybutyrate accumulated by bacteria is degraded to fuel bacteroid differentiation.

High-titer rabbit polyclonal antibodies to aflatoxin M(1) (AFM1) were produced by utilizing AFM1-bovine serum albumin (BSA) conjugate as an immunogen. An indirect competitive enzyme-linked immunosorbent assay was standardized for estimating AFM1 in milk and milk products. To avoid the influence of interfering substances present in the milk samples, it was necessary to prepare AFM1 standards in methanol extracts of certified reference material (CRM) not containing detectable AFM1 (< 0.05 ng/g). The reliability of the procedure was assessed by using CRM with AFM1 concentrations of < 0.5 and 0.76 ng/g. Also, assays of milk samples mixed with AFM1 ranging in concentration between 0.5 and 50 ng/L gave recoveries of > 93%. The relative cross-reactivity with aflatoxins (AF) and ochratoxin A, assessed as the amount of AFM1 necessary to cause 50% inhibition of binding, was 5% for AFB1 and much less for AFB2, AFG1, and AFG2; there was no reaction with ochratoxin A. AFM1 contamination was measured in retail milk and milk products collected from rural and periurban areas in Andhra Pradesh, India. Of 280 milk samples tested, 146 were found to contain < 0.5 ng/mL of AFM1; in 80 samples it varied from 0.6 to 15 ng/mL, in 42 samples from 16 to 30 ng/mL, and in 12 samples from 31 to 48 ng/mL. Most of the milk samples that contained high AFM1 concentrations were obtained from periurban locations. The results revealed a significant exposure of humans to AFM1 levels in India and thus highlight the need for awareness of risk among milk producers and consumers.

Groundnuts (Arachis hypogaea L.) are an important crop of the semi-arid tropics where they are often exposed to maximum temperatures of > 40 degrees C for short periods during the growing season. The objectives of this study were to determine: (i) the effects of short periods of exposure to high temperature on flower production (FN), the proportion of flowers forming fruits (fruit-set) and the number of pegs and pods per plant (RNt); (ii) whether fruit-set is affected by high temperature during different periods of daylight in each diurnal cycle; and (iii) whether responses to temperature were qualitative or quantitative. Plants of cv. ICGV 86015 were grown in controlled environments at a day/night temperature of 28/22 degrees C from sowing until 9 d after flowering (DAF). Then, cohorts of plants were: (a) exposed to day temperature of 28, 34, 42 or 48 degrees C for 2, 4 or 6 d; or were (b) exposed to 34, 42 or 48 degrees C for 6 d either throughout a 12 h day (08.00 to 20.00 h, WD), or only during the first 6 h (AM) or second 6 h (PM) of the day. Values of RNt were significantly reduced by high temperature, by duration of exposure, and by timing of exposure. Variation in FN was quantitatively related to floral bud temperatures during the day over the range 28-43 degrees C. In contrast, only floral bud temperatures > 36 degrees C during AM and WD significantly reduced fruit-set and hence RNt, whereas high PM temperature had no effect on fruit-set. These findings indicate that the response of RNt to day temperature is quantitative and can be modelled by combining the responses of FN and fruit-set to temperature.

N2-fixation by Rhizobium-legume symbionts is of major ecological and agricultural importance, responsible for producing a substantial fraction of the biosphere's nitrogen. On the basis of 15N-labelling studies, it had been generally accepted that ammonium is the sole secretion product of N2-fixation by the bacteroid and that the plant is responsible for assimilating it into amino acids. However, this paradigm has been challenged in a recent 15N-labelling study showing that soybean bacteroids only secrete alanine. Hitherto, nitrogen secretion has only been assessed from in vitro 15N-labelling studies of isolated bacteroids. We show that both ammonium and alanine are secreted by pea bacteroids. The in vitro partitioning between them will depend on whether the system is open or closed, as well as the ammonium concentration and bacteroid density. To overcome these limitations we identified and mutated the gene for alanine dehydrogenase (aldA) and demonstrate that AldA is the primary route for alanine synthesis in isolated bacteroids. Bacteroids of the aldA mutant fix nitrogen but only secrete ammonium at a significant rate, resulting in lower total nitrogen secretion. Peas inoculated with the aldA mutant are green and healthy, demonstrating that ammonium secretion by bacteroids can provide sufficient nitrogen for plant growth. However, plants inoculated with the mutant are reduced in biomass compared with those inoculated with the wild type. The labelling and plant growth studies suggest that alanine synthesis and secretion contributes to the efficiency of N2-fixation and therefore biomass accumulation.