Dynamic QTL-based ecophysiological models to predict phenotype from genotype and environment data.

BACKGROUND: Predicting the phenotype from the genotype is one of the major contemporary challenges in biology. This challenge is greater in plants because their development occurs mostly post-embryonically under diurnal and seasonal environmental fluctuations. Most current crop simulation models are physiology-based models capable of capturing environmental fluctuations but cannot adequately capture genotypic effects because they were not constructed within a genetics framework. RESULTS: We describe the construction of a mixed-effects dynamic model to predict time-to-flowering in the common bean (Phaseolus vulgaris L.). This prediction model applies the developmental approach used by traditional crop simulation models, uses direct observational data, and captures the Genotype, Environment, and Genotype-by-Environment effects to predict progress towards time-to-flowering in real time. Comparisons to a traditional crop simulation model and to a previously developed static model shows the advantages of the new dynamic model. CONCLUSIONS: The dynamic model can be applied to other species and to different plant processes. These types of models can, in modular form, gradually replace plant processes in existing crop models as has been implemented in BeanGro, a crop simulation model within the DSSAT Cropping Systems Model. Gene-based dynamic models can accelerate precision breeding of diverse crop species, particularly with the prospects of climate change. Finally, a gene-based simulation model can assist policy decision makers in matters pertaining to prediction of food supplies.

Development of a QTL-environment-based predictive model for node addition rate in common bean.

KEY MESSAGE: This work reports the effects of the genetic makeup, the environment and the genotype by environment interactions for node addition rate in an RIL population of common bean. This information was used to build a predictive model for node addition rate. To select a plant genotype that will thrive in targeted environments it is critical to understand the genotype by environment interaction (GEI). In this study, multi-environment QTL analysis was used to characterize node addition rate (NAR, node day- 1) on the main stem of the common bean (Phaseolus vulgaris L). This analysis was carried out with field data of 171 recombinant inbred lines that were grown at five sites (Florida, Puerto Rico, 2 sites in Colombia, and North Dakota). Four QTLs (Nar1, Nar2, Nar3 and Nar4) were identified, one of which had significant QTL by environment interactions (QEI), that is, Nar2 with temperature. Temperature was identified as the main environmental factor affecting NAR while day length and solar radiation played a minor role. Integration of sites as covariates into a QTL mixed site-effect model, and further replacing the site component with explanatory environmental covariates (i.e., temperature, day length and solar radiation) yielded a model that explained 73% of the phenotypic variation for NAR with root mean square error of 16.25% of the mean. The QTL consistency and stability was examined through a tenfold cross validation with different sets of genotypes and these four QTLs were always detected with 50-90% probability. The final model was evaluated using leave-one-site-out method to assess the influence of site on node addition rate. These analyses provided a quantitative measure of the effects on NAR of common beans exerted by the genetic makeup, the environment and their interactions.

Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison.

Here we present the results from an intercomparison of multiple global gridded crop models (GGCMs) within the framework of the Agricultural Model Intercomparison and Improvement Project and the Inter-Sectoral Impacts Model Intercomparison Project. Results indicate strong negative effects of climate change, especially at higher levels of warming and at low latitudes; models that include explicit nitrogen stress project more severe impacts. Across seven GGCMs, five global climate models, and four representative concentration pathways, model agreement on direction of yield changes is found in many major agricultural regions at both low and high latitudes; however, reducing uncertainty in sign of response in mid-latitude regions remains a challenge. Uncertainties related to the representation of carbon dioxide, nitrogen, and high temperature effects demonstrated here show that further research is urgently needed to better understand effects of climate change on agricultural production and to devise targeted adaptation strategies.

Next generation agricultural system models and knowledge products: Synthesis and strategy.

The purpose of this Special Issue of Agricultural Systems is to lay the foundation for the next generation of agricultural systems data, models and knowledge products. In the Introduction to this Special Issue, we described a vision for accelerating the rate of agricultural innovation and meeting the growing global need for food and fiber. In this concluding article of the NextGen Special Issue we synthesize insights and formulate a strategy to advance data, models, and knowledge products that are consistent with this vision. This strategy is designed to facilitate a transition from the current, primarily supply-driven approach toward a more demand-driven approach that would address key Use Cases where better data, models and knowledge products are seen by end-users as essential to meet their needs.

Next generation agricultural system data, models and knowledge products: Introduction.

Agricultural system models have become important tools to provide predictive and assessment capability to a growing array of decision-makers in the private and public sectors. Despite ongoing research and model improvements, many of the agricultural models today are direct descendants of research investments initially made 30-40 years ago, and many of the major advances in data, information and communication technology (ICT) of the past decade have not been fully exploited. The purpose of this Special Issue of Agricultural Systems is to lay the foundation for the next generation of agricultural systems data, models and knowledge products. The Special Issue is based on a "NextGen" study led by the Agricultural Model Intercomparison and Improvement Project (AgMIP) with support from the Bill and Melinda Gates Foundation.

Towards a new generation of agricultural system data, models and knowledge products: Information and communication technology.

Agricultural modeling has long suffered from fragmentation in model implementation. Many models are developed, there is much redundancy, models are often poorly coupled, model component re-use is rare, and it is frequently difficult to apply models to generate real solutions for the agricultural sector. To improve this situation, we argue that an open, self-sustained, and committed community is required to co-develop agricultural models and associated data and tools as a common resource. Such a community can benefit from recent developments in information and communications technology (ICT). We examine how such developments can be leveraged to design and implement the next generation of data, models, and decision support tools for agricultural production systems. Our objective is to assess relevant technologies for their maturity, expected development, and potential to benefit the agricultural modeling community. The technologies considered encompass methods for collaborative development and for involving stakeholders and users in development in a transdisciplinary manner. Our qualitative evaluation suggests that as an overall research challenge, the interoperability of data sources, modular granular open models, reference data sets for applications and specific user requirements analysis methodologies need to be addressed to allow agricultural modeling to enter in the big data era. This will enable much higher analytical capacities and the integrated use of new data sources. Overall agricultural systems modeling needs to rapidly adopt and absorb state-of-the-art data and ICT technologies with a focus on the needs of beneficiaries and on facilitating those who develop applications of their models. This adoption requires the widespread uptake of a set of best practices as standard operating procedures.

Brief history of agricultural systems modeling.

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.

Towards a new generation of agricultural system data, models and knowledge products: Design and improvement.

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.

Toward a new generation of agricultural system data, models, and knowledge products: State of agricultural systems science.

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.

The ethics of insurance limiting institutional medical care: It's all about the money.

Dr F. Inest practices surgery at a renowned medical center but is concerned because increasing numbers of medical insurers are excluding his institution from coverage. Many of his former referring physicians are beginning to send their patients elsewhere for this reason. The marketing people have been busy increasing their advertising buys and exploring new business models. There is even talk about reducing expensive clinical trials. However, regardless of his affiliation, he has little control over these and other organizational decisions that directly impact his practice clinically and fiscally. What should he do?

The ethics of dysfunctional professional relationships.

Dr N, the chief surgeon at a large private hospital who has been practicing there for decades, has noted recent changes in the administration that are troubling. Multiple advertisements proclaim awards that have not been achieved and various ads employed actors pretending to be patients experiencing miracle cures. Pressures on medical staff to practice more efficiently have become overbearing. Changes in bundling Medicare postoperative care have raised questions about future patient selection. There is a lack of transparency with minimal physician input. The much respected chief-of-staff has moved into the administrative side and no longer advocates for the professionalism of the staff. When Dr N meets with the chief-of-staff and objects to these changes, the chief of staff calls Dr N a complainer and tells him to forget about it. Nothing is done.

Fiduciary disparity clarity: Ethics of divided allegiances.

An experienced senior vascular surgeon, Dr H. O. Nest, at a university medical center is asked to evaluate a patient with a rare complex vascular problem. The patient is a high-ranking university official, Mr N. Otable, well known to all in the university setting. Dr Nest has had very limited experience with the condition. He has viewed presentations about it but is aware of a world expert at another institution. He discusses transfer with the patient, who agrees on that approach. Later that day, when Dr Nest receives a visit from the Chief-of-Staff and the hospital CEO asking about Mr Otable, they are very concerned that transfer will reflect badly on the medical center's reputation. Dr Nest is strongly requested to reconsider his recommendation--almost at gunpoint. What should he do? A. If he believes that the outcome will be satisfactory, he should schedule the operation. B. He should explain the situation to the patient and let him choose where he wishes to have his surgery. C. He should continue with the plan to refer the patient to another center. D. He must understand his limits and base his decision accordingly. E. He should arrange a conference with the surgeons in the vascular division and the administrators.

To treat or not to treat: On what should surgical therapy be based?

Dr C. Autious has just returned from the most prestigious vascular surgery meeting in America. At the meeting, one of the most prominent complex aneurysm surgeons arose to discuss a paper concerning a procedure he had developed and popularized over the last decade. Dr L. Uminous stunned the audience with his declaration that he no longer recommends that his namesake procedure be performed. Instead, he proclaimed that a new, radically different procedure be adopted immediately. He showed slides detailing the novel proposal but did not give data concerning results obtained. The recommended procedure is technically possible but seems to require a different skill set. Dr Autious has a patient scheduled for elective surgery that he had planned to use the Uminous procedure to treat. What should he do? A. Do the recommended procedure as best you can. B. Refer the patient to Dr Uminous. C. Offer the recommended procedure with full disclosure. D. Give full disclosure and let the patient decide which procedure to use. E. Put the procedure on hold until more information becomes available.

Where does innovation adaptation end and experimentation begin?

Dr U. Nique is internationally known for contributions in vascular surgery. An elderly man, a top governmental leader in his country, is in Dr Nique's clinic for evaluation of a recurrent complex thoracoabdominal aneurysm. It was treated inadequately by a vascular surgeon in another country and was redone without success. It still poses a threat to the man's life. Because of the unusual reconstructions, a one-of-a-kind repair is needed. Dr Nique has never done such a repair and, if someone else has, they have not published their results. What considerations should apply to this case?

What is meant by high-risk informed consent?

Dr S.C. Alpel is a renowned complex aneurysm surgeon, accepting difficult cases from around the world. He has an English-speaking patient from the Middle East who has a very large life-threatening aneurysm. The patient is in the mid-70s, is frail with multiple comorbidities, and needs extensive open surgery. How does the standard Informed consent process need to be altered? A. An interpreter should be present B. The surrogate should be present and participate C. All possible serious complications, including prolonged life support, should be detailed D. The patient must be questioned about his end-of-life wishes E. All of the above should be included

Is medical advertising always unethical, or does it just seem to be?

Dr C. Lever is the undisputed expert in a new endovascular procedure he developed and brought to fruition over the years. Other professionals publishing their results call it by his name, although he has strictly avoided that nomenclature. Lever is at a medical center with several participating hospitals, which boast aggressive ultracompetitive marketing departments. His hospital wants to concentrate on him as proof that the best care is available at their facility. A successful campaign certainly would add to Lever's and perhaps to his group's referrals. He looks at the first advertisement and a Greek god would have been less vaunted but nothing said is untrue. What should he do? A. Ask that all advertising identifying him be discontinued immediately. B.Tell them to hype it up. C. Ask that marketing stick to the facts completely sans hype. D. Check with the Ethics Committee of the hospital. E. Check with the Ethics Committee of the American Medical Association (AMA) or American College of Surgeons or the appropriate surgical subspecialty professional association.

Obligations and frustrations with high-risk patients: ethics of physicians' evaluations.

A surgeon, Dr A. Droit, has been following a 97-year-old male with a type IV thoracoabdominal aneurysm, which became symptomatic this morning and is leaking. The patient is frail but active with no important comorbidities. The anatomy demands an open procedure. The patient is a former renowned physician who has been a longtime family friend of Dr Droit-like a grandfather. He presented incoherent with sagging blood pressure. A complicating factor is that Dr D. Rag, the chief anesthesiologist, decided that neither he nor any of his staff would provide anesthesia. Dr Droit knows an anesthesiologist who handles high-risk patients at another hospital in the medical center. The patient has worsened over the last hour, is becoming more unstable, and is unable to respond but his wife wishes to consent for surgery. What should Dr Droit do?

Multimodel ensembles of wheat growth: many models are better than one.

Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun. We report on the largest ensemble study to date, of 27 wheat models tested in four contrasting locations for their accuracy in simulating multiple crop growth and yield variables. The relative error averaged over models was 24-38% for the different end-of-season variables including grain yield (GY) and grain protein concentration (GPC). There was little relation between error of a model for GY or GPC and error for in-season variables. Thus, most models did not arrive at accurate simulations of GY and GPC by accurately simulating preceding growth dynamics. Ensemble simulations, taking either the mean (e-mean) or median (e-median) of simulated values, gave better estimates than any individual model when all variables were considered. Compared to individual models, e-median ranked first in simulating measured GY and third in GPC. The error of e-mean and e-median declined with an increasing number of ensemble members, with little decrease beyond 10 models. We conclude that multimodel ensembles can be used to create new estimators with improved accuracy and consistency in simulating growth dynamics. We argue that these results are applicable to other crop species, and hypothesize that they apply more generally to ecological system models.

Is "your only hope" medical treatment choice really a choice?

An elderly gentleman, from Scandinavia, Mr. K. R. Plunk, with a soon-to-be lethal disease, has come to see you because you are the world's expert in complex aneurysm surgery and his is a case for the books. He has multiple comorbidities; the most concerning is his cardiopulmonary functioning. You have only operated on a few patients who are at this level of risk. He has been told repeatedly you are his only hope, which is literally true. A cure would pair one of the "biggest operations" with one of the frailest patients. You have been on an invincible roll and have decided to give it a shot, if he agrees. What is the most ethical informed consent in this case?

Defining, aligning, or declining do not resuscitate during surgery.

A Professor A. Droit, 93 years of age, formerly your college ethics teacher, developed a painful ischemic foot from distal aortic blockage. A daughter, who is a nurse, brought him to the hospital. He has multiple comorbidities, including leukemia for which he is getting chemotherapy. He agrees to surgery but hands you a completed do not resuscitate (DNR) form and insists it be honored throughout his care. As the operative wound is being closed, he has a slow ventricular tachycardia, which does not respond to intravenous therapy. You should: