Responses of soil carbon sequestration to climate‐smart agriculture practices: A meta‐analysis

Climate‐smart agriculture (CSA) management practices (e.g., conservation tillage, cover crops, and biochar applications) have been widely adopted to enhance soil organic carbon (SOC) sequestration and to reduce greenhouse gas emissions while ensuring crop productivity. However, current measurements regarding the influences of CSA management practices on SOC sequestration diverge widely, making it difficult to derive conclusions about individual and combined CSA management effects and bringing large uncertainties in quantifying the potential of the agricultural sector to mitigate climate change. We conducted a meta‐analysis of 3,049 paired measurements from 417 peer‐reviewed articles to examine the effects of three common CSA management practices on SOC sequestration as well as the environmental controlling factors. We found that, on average, biochar applications represented the most effective approach for increasing SOC content (39%), followed by cover crops (6%) and conservation tillage (5%). Further analysis suggested that the effects of CSA management practices were more pronounced in areas with relatively warmer climates or lower nitrogen fertilizer inputs. Our meta‐analysis demonstrated that, through adopting CSA practices, cropland could be an improved carbon sink. We also highlight the importance of considering local environmental factors (e.g., climate and soil conditions and their combination with other management practices) in identifying appropriate CSA practices for mitigating greenhouse gas emissions while ensuring crop productivity.     

Models meet data: Challenges and opportunities in implementing land management in Earth system models

As the applications of Earth system models (ESMs) move from general climate projections toward questions of mitigation and adaptation, the inclusion of land management practices in these models becomes crucial. We carried out a survey among modeling groups to show an evolution from models able only to deal with land‐cover change to more sophisticated approaches that allow also for the partial integration of land management changes. For the longer term a comprehensive land management representation can be anticipated for all major models. To guide the prioritization of implementation, we evaluate ten land management practices—forestry harvest, tree species selection, grazing and mowing harvest, crop harvest, crop species selection, irrigation, wetland drainage, fertilization, tillage, and fire—for (1) their importance on the Earth system, (2) the possibility of implementing them in state‐of‐the‐art ESMs, and (3) availability of required input data. Matching these criteria, we identify “low‐hanging fruits” for the inclusion in ESMs, such as basic implementations of crop and forestry harvest and fertilization. We also identify research requirements for specific communities to address the remaining land management practices. Data availability severely hampers modeling the most extensive land management practice, grazing and mowing harvest, and is a limiting factor for a comprehensive implementation of most other practices. Inadequate process understanding hampers even a basic assessment of crop species selection and tillage effects. The need for multiple advanced model structures will be the challenge for a comprehensive implementation of most practices but considerable synergy can be gained using the same structures for different practices. A continuous and closer collaboration of the modeling, Earth observation, and land system science communities is thus required to achieve the inclusion of land management in ESMs.     

The overlooked spatial dimension of climate‐smart agriculture

Climate‐smart agriculture (CSA) and sustainable intensification (SI) are widely claimed to be high‐potential solutions to address the interlinked challenges of food security and climate change. Operationalization of these promising concepts is still lacking and potential trade‐offs are often not considered in the current continental‐ to global‐scale assessments. Here we discuss the effect of spatial variability in the context of the implementation of climate‐smart practices on two central indicators, namely yield development and carbon sequestration, considering biophysical limitations of suggested benefits, socioeconomic and institutional barriers to adoption, and feedback mechanisms across scales. We substantiate our arguments by an illustrative analysis using the example of a hypothetical large‐scale adoption of conservation agriculture (CA) in sub‐Saharan Africa. We argue that, up to now, large‐scale assessments widely neglect the spatially variable effects of climate‐smart practices, leading to inflated statements about co‐benefits of agricultural production and climate change mitigation potentials. There is an urgent need to account for spatial variability in assessments of climate‐smart practices and target those locations where synergies in land functions can be maximized in order to meet the global targets. Therefore, we call for more attention toward spatial planning and landscape optimization approaches in the operationalization of CSA and SI to navigate potential trade‐offs.     

Plant genetics, sustainable agriculture and global food security

The United States and the world face serious societal challenges in the areas of food, environment, energy, and health. Historically, advances in plant genetics have provided new knowledge and technologies needed to address these challenges. Plant genetics remains a key component of global food security, peace, and prosperity for the foreseeable future. Millions of lives depend upon the extent to which crop genetic improvement can keep pace with the growing global population, changing climate, and shrinking environmental resources. While there is still much to be learned about the biology of plant-environment interactions, the fundamental technologies of plant genetic improvement, including crop genetic engineering, are in place, and are expected to play crucial roles in meeting the chronic demands of global food security. However, genetically improved seed is only part of the solution. Such seed must be integrated into ecologically based farming systems and evaluated in light of their environmental, economic, and social impacts-the three pillars of sustainable agriculture. In this review, I describe some lessons learned, over the last decade, of how genetically engineered crops have been integrated into agricultural practices around the world and discuss their current and future contribution to sustainable agricultural systems.     

Gene-based modelling for rice: an opportunity to enhance the simulation of rice growth and development?

Process-based crop simulation models require employment of new knowledge for continuous improvement. To simulate growth and development of different genotypes of a given crop, most models use empirical relationships or parameters defined as genetic coefficients to represent the various cultivar characteristics. Such a loose introduction of different cultivar characteristics can result in bias within a simulation, which could potentially integrate to a high simulation error at the end of the growing season when final yield at maturity is predicted. Recent advances in genetics and biomolecular analysis provide important opportunities for incorporating genetic information into process-based models to improve the accuracy of the simulation of growth and development and ultimately the final yield. This improvement is especially important for complex applications of models. For instance, the effect of the climate change on the crop growth processes in the context of natural climatic and soil variability and a large range of crop management options (e.g., N management) make it difficult to predict the potential impact of the climate change on the crop production. Quantification of the interaction of the environmental variables with the management factors requires fine tuning of the crop models to consider differences among different genotypes. In this paper we present this concept by reviewing the available knowledge of major genes and quantitative trait loci (QTLs) for important traits of rice for improvement of rice growth modelling and further requirements. It is our aim to review the assumption of the adequacy of the available knowledge of rice genes and QTL information to be introduced into the models. Although the rice genome sequence has been completed, the development of gene-based rice models still requires additional information than is currently unavailable. We conclude that a multidiscipline research project would be able to introduce this concept for practical applications.     

Production of transmitochondrial mice

With the advancement of various gene transfer technologies, the establishment of mitochondria transfer as a viable technique to genetically engineer mouse models paradoxically lagged behind other genetic technologies. The lack of demonstrable recombination in mtDNA necessitates different approaches to conventional transgenesis-based techniques. Initially, heteroplasmic mice were created to explore disease pathogenesis and mitochondrial dynamics in an in vivo system. Ultimately, transmitochondrial mouse models will be used to explore the role of the mitochondrial genome in human disease processes and in the development of novel human gene therapies. Here, we describe methodology to produce transmitochondrial mice (both homoplasmic and heteroplasmic models) harboring foreign mitochondrial genomes, using both embryo microinjection and embryonic stem (ES) cell-based approaches. Specific modeling and the procedures for mitochondrial transfer will be of considerable importance toward our understanding of discrete mitochondrial mutations, as well as lead to the development of novel strategies and therapies for human diseases influenced by mitochondrial DNA mutations.     

Modeling and simulation: tools for metabolic engineering.

Mathematical modeling is one of the key methodologies of metabolic engineering. Based on a given metabolic model different computational tools for the simulation, data evaluation, systems analysis, prediction, design and optimization of metabolic systems have been developed. The currently used metabolic modeling approaches can be subdivided into structural models, stoichiometric models, carbon flux models, stationary and nonstationary mechanistic models and models with gene regulation. However, the power of a model strongly depends on its basic modeling assumptions, the simplifications made and the data sources used. Model validation turns out to be particularly difficult for metabolic systems. The different modeling approaches are critically reviewed with respect to their potential and benefits for the metabolic engineering cycle. Several tools that have emerged from the different modeling approaches including structural pathway synthesis, stoichiometric pathway analysis, metabolic flux analysis, metabolic control analysis, optimization of regulatory architectures and the evaluation of rapid sampling experiments are discussed.     

Changes in the distribution of multispecies pest assemblages affect levels of crop damage in warming tropical Andes

Climate induced species range shifts might create novel interactions among species that may outweigh direct climatic effects. In an agricultural context, climate change might alter the intensity of competition or facilitation interactions among pests with, potentially, negative consequences on the levels of damage to crop. This could threaten the productivity of agricultural systems and have negative impacts on food security, but has yet been poorly considered in studies. In this contribution, we constructed and evaluated process‐based species distribution models for three invasive potato pests in the Tropical Andean Region. These three species have been found to co‐occur and interact within the same potato tuber, causing different levels of damage to crop. Our models allowed us to predict the current and future distribution of the species and therefore, to assess how damage to crop might change in the future due to novel interactions. In general, our study revealed the main challenges related to distribution modeling of invasive pests in highly heterogeneous regions. It yielded different results for the three species, both in terms of accuracy and distribution, with one species surviving best at lower altitudes and the other two performing better at higher altitudes. As to future distributions our results suggested that the three species will show different responses to climate change, with one of them expanding to higher altitudes, another contracting its range and the other shifting its distribution to higher altitudes. These changes will result in novel areas of co‐occurrence and hence, interactions of the pests, which will cause different levels of damage to crop. Combining population dynamics and species distribution models that incorporate interspecific trade‐off relationships in different environments revealed a powerful approach to provide predictions about the response of an assemblage of interacting species to future environmental changes and their impact on process rates.     

A Taxonomic Review of the Use of IoT and Blockchain in Healthcare Applications

ObjectivesWith the rapid evolution and technology advancement, the healthcare sector is evolving day by day. It is taking advantage of different technologies such as Internet of things and Blockchain. Several applications related to daily healthcare activities are adopting the use of these technologies. In this paper, we present a review in which we group different healthcare applications that integrate the Internet of things and Blockchain in their systems.Material and methodsA review study about the integration of IoT and Blockchain in healthcare systems was conducted. We searched the databases ScienceDirect, IEEE Xplore, Google Scholar and ACM Digital Library.ResultsThis review focuses on categorizing the use cases of IoT and Blockchain in the healthcare sector. The study listed 6 applications in medical services, namely, remote patient monitoring, electronic medical records management, disease prediction, patient tracking, drug traceability and fighting infectious disease especially COVID-19. The paper also investigates the challenges associated with the adoption of the Blockchain technology in healthcare IoT-based systems and some of the existing solutions. It also introduces some future research directions.ConclusionThe survey of the use cases of IoT and Blockchain in the healthcare sector will serve as a state of the art for future researches. In addition, the paper gives some directions to new possible researches that could help to revolutionize the healthcare sector by using other technologies such as artificial intelligence, big data, fog and cloud computing.     

Insect pest management in the age of synthetic biology

Arthropod crop pests are responsible for 20% of global annual crop losses, a figure predicted to increase in a changing climate where the ranges of numerous species are projected to expand. At the same time, many insect species are beneficial, acting as pollinators and predators of pest species. For thousands of years, humans have used increasingly sophisticated chemical formulations to control insect pests but, as the scale of agriculture expanded to meet the needs of the global population, concerns about the negative impacts of agricultural practices on biodiversity have grown. While biological solutions, such as biological control agents and pheromones, have previously had relatively minor roles in pest management, biotechnology has opened the door to numerous new approaches for controlling insect pests. In this review, we look at how advances in synthetic biology and biotechnology are providing new options for pest control. We discuss emerging technologies for engineering resistant crops and insect populations and examine advances in biomanufacturing that are enabling the production of new products for pest control.     

Environmental variability and fisheries: what can models do?

This review is based on 58 climate-fisheries models published over the last 28 years that describe the impacts of fishery pressure and environmental variability on populations and ecosystems and include basic principles of population dynamics. It points out that the incorporation of environmental factors in fishery models has already been done and is of great importance for future models used in the assessment of marine resources. The work is guided by the questions to what extent have these models a) enhanced our understanding of the interrelationships between the environment, the fishery and the state of the exploited resources and b) helped to improve the prediction of population dynamics and the assessment of marine resources. For each of the six most commonly used model categories a case study is critically analyzed. The problems of “breaking relationships” between environmental factors and the biological response used in models, the trade-off between model complexity (realism) and simplicity (data availability) and the potential of multivariate climate indices for forecasting ecosystem states and for use as proxies for combined models are discussed, as are novel non-linear and spatially explicit modeling approaches. Approaches differ in terms of model complexity, use of linear or non-linear equations, number of parameters, forecast time horizon and type of resource modelled. A majority of the models were constructed for fish and invertebrate stocks of the northeast Pacific and the epicontinental seas of the Atlantic, reflecting the advancement of fisheries science in these regions. New, in parts highly complex models and sophisticated approaches were identified. The reviewed studies demonstrate that the performance of fished stocks can better be described if environmental or climatic variability is incorporated into the fisheries models. We conclude that due to the already available knowledge, the greatly enhanced computer power, new methods and recent findings of large-scale climatic/oceanographic cycles, fisheries modeling should progress greatly in the coming years.     

Managing the environmental problem of seawater intrusion in coastal aquifers through simulation–optimization modeling

The seawater intrusion is a widespread environmental problem of coastal aquifers where more than two third of the world’s population lives. The indiscriminate and unplanned groundwater withdrawal for fulfilling the growing freshwater needs of coastal regions causes this problem. Computer-based models are useful tools for achieving the optimal solution of seawater intrusion management problems. Various simulation and optimization modeling approaches have been used to solve the problems. Optimization approaches have been shown to be of great importance when combined with simulation models. A review on the combined applications of simulation and optimization modeling for the seawater intrusion management of the coastal aquifers are done and is presented in this paper. The reviews revealed that the simulation–optimization modeling approach is very suitable for achieving an optimal solution of seawater intrusion management problems even with a large number of variables. It is recommended that the future research should be directed toward improving the long-term hydraulic assessment by collecting and analyzing widespread spatial data, which can be done by increasing the observation and monitoring networks. The coupling of socioeconomic aspects in the seawater intrusion modeling would be another aspect which could be included in the future studies.     

Cancer theranostics: the rise of targeted magnetic nanoparticles

Interest in utilizing magnetic nanoparticles (MNP) for biomedical applications has increased considerably over the past two decades. This excitement has been driven in large part by the success of MNPs as contrast agents in magnetic resonance imaging. The recent investigative trend with respect to cancer has continued down a diagnostic path, but has also turned toward concurrent therapy, giving rise to the distinction of MNPs as potential "theranostics". Here we review both the key technical principles of MNPs and ongoing advancement toward a cancer theranostic MNP. Recent progress in diagnostics, hyperthermia treatments, and drug delivery are all considered. We conclude by identifying current barriers to clinical translation of MNPs and offer considerations for their future development.     

Climate Change and Crop Exposure to Adverse Weather: Changes to Frost Risk and Grapevine Flowering Conditions

The cultivation of grapevines in the UK and many other cool climate regions is expected to benefit from the higher growing season temperatures predicted under future climate scenarios. Yet the effects of climate change on the risk of adverse weather conditions or events at key stages of crop development are not always captured by aggregated measures of seasonal or yearly climates, or by downscaling techniques that assume climate variability will remain unchanged under future scenarios. Using fine resolution projections of future climate scenarios for south-west England and grapevine phenology models we explore how risks to cool-climate vineyard harvests vary under future climate conditions. Results indicate that the risk of adverse conditions during flowering declines under all future climate scenarios. In contrast, the risk of late spring frosts increases under many future climate projections due to advancement in the timing of budbreak. Estimates of frost risk, however, were highly sensitive to the choice of phenology model, and future frost exposure declined when budbreak was calculated using models that included a winter chill requirement for dormancy break. The lack of robust phenological models is a major source of uncertainty concerning the impacts of future climate change on the development of cool-climate viticulture in historically marginal climatic regions.     

Cancer modeling in the modern era: progress and challenges

Genetically engineered mouse models have contributed extensively to the field of cancer research. The ability to manipulate the mouse germline affords numerous approaches toward understanding the complexities of this disease, possibly providing accurate preclinical models for therapeutic and diagnostic advances. This review highlights some of the current strategies for modeling cancer in the mouse, recent accomplishments, and key remaining challenges.     

气温、CO2浓度和降水交互作用对作物生长和产量的影响

气温、大气CO₂浓度和降水等气候因子是影响作物生长发育的关键因子,而不同的气候因子对作物的影响并非独立的,多气候因子交互作用对作物的影响目前已成为研究的焦点问题.研究不同气候因子交互作用的影响,其结果更接近作物生长的实际情况,有助于了解作物甚至作物生态系统对气候变化的真实响应.国内外关于不同气候因子对作物影响的报道较多,要全面总结不同气候因子交互作用对作物的影响是非常困难的.因此,本文只对近年来有关气温升高、大气CO₂浓度增加和降水变化交互作用对作物生长发育、光合生理及产量影响的研究进展做一简要评述,并提出目前研究的不足和需要解决的关键问题,以期为气候变化对作物生长发育及产量影响的研究提供参考.     

气温、CO2浓度和降水交互作用对作物生长和产量的影响

气温、大气CO₂浓度和降水等气候因子是影响作物生长发育的关键因子,而不同的气候因子对作物的影响并非独立的,多气候因子交互作用对作物的影响目前已成为研究的焦点问题.研究不同气候因子交互作用的影响,其结果更接近作物生长的实际情况,有助于了解作物甚至作物生态系统对气候变化的真实响应.国内外关于不同气候因子对作物影响的报道较多,要全面总结不同气候因子交互作用对作物的影响是非常困难的.因此,本文只对近年来有关气温升高、大气CO₂浓度增加和降水变化交互作用对作物生长发育、光合生理及产量影响的研究进展做一简要评述,并提出目前研究的不足和需要解决的关键问题,以期为气候变化对作物生长发育及产量影响的研究提供参考.     

Preclinical research studies for treating severe muscular injuries: focus on tissue-engineered strategies

Severe skeletal muscle injuries are a lifelong trauma with limited medical solutions. Significant progress has been made in developing in vitro surrogates for treating such trauma. However, more attention is needed when translating these approaches to the clinic. In this review, we survey the potential of tissue-engineered surrogates in promoting muscle healing, by critically analyzing data from recent preclinical models. The therapeutic advantages provided by a combination of different biomaterials, cell types, and biochemical mediators are discussed. Current therapies on muscle healing are also summarized, emphasizing their main advantages and drawbacks. We also discuss previous and ongoing clinical trials as well as highlighting future directions for the field.     

Applications of Decision Support System: A Case Study of Solanaceous Vegetables

Crop simulation models constitute the major proportion in decision support systems. A large number of crop models have been developed for potato and few for tomato and peppers. In the literature, thirty three crop models have been reported to simulate potato, nine for tomato and six for peppers. Some of these models dealt with the climate change scenario and others with the crop management practices such as sowing time, irrigation, nitrogen, and insect-pests management. The most evaluated and applied models for potato include; SUBSTOR, and LINTUL-Potato, whereas CROPGRO-tomato model is the most tested and applied for tomato. The AQUACROP is the most widely used model to simulate the water dynamics. The CROPGRO model has been tested for elevated temperatures and CO₂ under greenhouse conditions for tomato. In tomato and peppers, almost similar models have been applied for field conditions as well as under greenhouse environments with some modifications. Nitrogen dynamics has been widely tested by employing the EU-Rotate-N model for tomato and peppers. Simulation studies dealing with changing climate conditions are rare in potato and are not found for tomato and peppers. To modify potato, tomato and peppers models for climate impact studies, it is required that they are (a) calibrated and evaluated with new cultivars under various agro-environmental conditions and (b) assessed under varying field conditions under changing climates and crop management practices, including temperature increases, water and nutrient management and their interactions. These comprehensive model studies and modifications need a collaborative international effort and a multi-year, large scale field research studies on potato, tomato and peppers.     

Assisted ultrasound applications for the production of safe foods

Ultrasound requires high power and longer treatment times to inactivate micro‐organisms when compared to ultrasound combined with other technologies. Previous reports have shown that the effectiveness of ultrasound as a decontamination technology can be increased by combining it with another treatment such as pressure, heat and antimicrobial solutions. Assisted ultrasound, the combination of ultrasound with another technology, is more energy efficient, and it has less impact on the food properties. In this review paper, the power ultrasound antimicrobial mechanisms of action, the antimicrobial effects of ultrasound in combination with other physical processes and antimicrobial solutions are comprehensively discussed. Furthermore, the present interest on using these technologies as alternative processing and decontamination methods is presented. Research outputs on the application of ultrasound combined with physical processes are showcased including applications of thermosonication, manosonication, manothermosonication and osmosonication. Antimicrobial efficacy, energy requirements and optimal operation conditions of the different assisted ultrasound technologies are critically discussed, and their impact on the food industry for future applications is presented. Overall, this review paper highlights the importance and recent developments of assisted ultrasound for enhancing food safety.