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It is important to implement detection and assessment of plant diseases based on remotely sensed data for disease monitoring and control. Hyperspectral data of healthy leaves, leaves in incubation period and leaves in diseased period of wheat stripe rust and wheat leaf rust were collected under in-field conditions using a black-paper-based measuring method developed in this study. After data preprocessing, the models to identify the diseases were built using distinguished partial least squares (DPLS) and support vector machine (SVM), and the disease severity inversion models of stripe rust and the disease severity inversion models of leaf rust were built using quantitative partial least squares (QPLS) and support vector regression (SVR). All the models were validated by using leave-one-out cross validation and external validation. The diseases could be discriminated using both distinguished partial least squares and support vector machine with the accuracies of more than 99%. For each wheat rust, disease severity levels were accurately retrieved using both the optimal QPLS models and the optimal SVR models with the coefficients of determination (R2) of more than 0.90 and the root mean square errors (RMSE) of less than 0.15. The results demonstrated that identification and severity evaluation of stripe rust and leaf rust at the leaf level could be implemented based on the hyperspectral data acquired using the developed method. A scientific basis was provided for implementing disease monitoring by using aerial and space remote sensing technologies. [ABSTRACT FROM AUTHOR]

The use of process-based modelling is increasing in most disciplines of plant science, but criteria for what is acceptable modelling work have rarely been made explicit. Unlike empirical work, modelling does not provide direct information on nature, and the goal is generally to explain natural phenomena, or predict their consequences, rather than reveal new phenomena or test specific hypotheses. Goals, methods and results of modelling and empirical work thus differ and they should be judged by different criteria. This note shows how the four criteria of explanation, testability, novelty and good modelling practice can be applied to modelling papers in the plant sciences. The practical implementation of these criteria is discussed, and a checklist of eight questions is derived with which papers can be evaluated. To illustrate the use of the criteria, they are applied to a classic publication from the crop modelling literature [Simulation of Assimilation, Respiration and Transpiration of Crops. Pudoc, Wageningen]. [Copyright &y& Elsevier]

Unmanned aerial vehicle-based hyperspectral imaging (HSI) and machine learning (ML) techniques are applied for crop field data collection such as yield, nitrogen content, leaf chlorophyll, biomass estimation, leaf area index (LAI), and biotic and abiotic stress. It is very difficult to identify with certainty best practices for specific applications and for targeted crop species because the results are frequently contradictory; models or indices sometimes perform well, but other times they do not. ML and HSI are useful and sophisticated techniques, but treating them as first-option methods may be detrimental in the long term. Favoring HSI in situations where a multispectral sensor performs equally well only delays end-user adoption of technology owing to cost and complexity. The past few years have seen increased interest in unmanned aerial vehicle (UAV)-based hyperspectral imaging (HSI) and machine learning (ML) in agricultural research, concomitant with an increase in published research on these topics. We provide an updated review, written for agriculturalists, highlighting the benefits in the retrieval of biophysical parameters of crops via UAVs relative to less sophisticated options. We reviewed >70 recent papers and found few consistent results between similar studies. Owing to their high complexity and cost, especially when applied to crops of low value, the benefits of most of the research reviewed are difficult to explain. Future effort will be necessary to distill research findings into lower-cost options for end-users. [ABSTRACT FROM AUTHOR]

Crop losses from pests threaten global food security and safety. In the last six decades, pest control using chemical pesticides has resulted in important yield gains per unit area, worldwide. However, the long-term sustainability of chemical pest control has been increasingly thrown into doubt due to the negative impact on human health, biodiversity, and the environment. Consequently, there is an urgent need to improve the science of crop protection in order to tackle the five key challenges of 21st century agriculture holistically: (i) maintaining or improving agricultural productivity, (ii) producing healthy food, (iii) reducing the negative impacts of agriculture on ecosystem and human health, (iv) ensuring the economic viability of farms, and (v) adapting agriculture to climate change. Agroecological Crop Protection (ACP) can be a powerful approach to address these challenges, as we demonstrate in this paper. ACP is the application of the principles of agroecology to crop protection in order to promote virtuous and sustainable changes in agriculture and food systems. ACP combines multiple approaches and disciplines including ecology, agroecology, and Integrated Pest Management. It promotes a crop protection system compatible with healthy agricultural and food systems, agroecological principles and the "one health" approach. We predict that ACP will meet the challenge of pesticide-free agriculture in the future. In this paper, we will first present the scientific, agricultural and social components of ACP. We will then analyze the research approaches, questions, methods and tools needed to adopt ACP. Finally, we suggest key mechanisms to facilitate the transition to ACP, which will ultimately provide sustainable food, feed, and fuel in a context of major global change. [ABSTRACT FROM AUTHOR]

An evolving green agenda as the UK seeks to achieve 'net zero' in greenhouse gas emissions by 2050, coupled with our new trading relationship with the European Union, is resulting in new government policies, which will be disruptive to Britain's traditional food and farming practices. These policies encourage sustainable farming and land‐sparing to restore natural habitats and will provide an opportunity to address issues such as high emissions of GHGs and dwindling biodiversity resulting from many intensive agricultural practices. To address these and other food challenges such as global conflicts and health issues, Britain will need a revolution in its food system. The aim of this paper is to make the case for such a food revolution where additional healthy food for the UK population is produced in‐country in specialised production units for fruits and vegetables developed on sites previously considered unsuitable for crop production. High crop productivity can be achieved in low‐cost controlled environments, making extensive use of novel crop science and modern controlled‐environment technology. Such systems must be operated with very limited environmental impact. In recent years, growth in the application of plasticulture in UK horticulture has driven some increases in crop yield, quality and value. However, the environmental cost of plastic production and plastic pollution is regarded as a generational challenge that faces the earth system complex. The distribution of plastic waste is ubiquitous, with a significant pollution load arising from a range of agricultural practices. The primary receptor of agriplastic pollution is agricultural soil. Impacts of microplastics on crop productivity and quality and also on human health are only now being investigated. This paper explores the possibility that we can mitigate the adverse environmental effects of agriplastics and thereby exploit the potential of plasticulture to enhance the productivity and positive health impact of UK horticulture. [ABSTRACT FROM AUTHOR]

Research into an innovative weed management approach should focus on a long-term ecological approach, taking into account the interaction between weed communities, crops, management actions, and environmental and socio-economic aspects for each specific agroecosystem [[7], [12]]. From 2018 to 2023, I Agronomy i published 323 papers in the areas of weed science and weed management. Other topics, like VRM (3%), BHM (6%), and INM (7%), confirm the current interest within weed science research towards alternative methods within an integrated and sustainable management approach. [Extracted from the article]

The editorial board of Crop Science has announced the recipients of the 2023 Editor's Citation for Excellence. These awards recognize the dedication and professional commitment of volunteer reviewers and editors who have contributed to the high standard and quality of papers published in the journal. The recipients were chosen based on their thorough, competent, and timely reviews or editing of manuscripts. Each recipient will receive a certificate of appreciation, an ASA‐CSSA‐SSSA gift certificate, and recognition in CSA News. The recipients include Dr. Gabriela Abeledo, Dr. Brenda Laura Gambin, Dr. Lori Hinze, Dr. Vince Pantalone, Dr. Cristiane Pilon, and Dr. Wei Wu as associate editors, and Dr. Georgia Eizenga, Dr. Jales Mendes Oliveira Fonseca, Dr. Laura Lindsey, Dr. Ntombokulunga Mbuma, Dr. Desalegn Serba, and Prof. Dr. Meiliang Zhou as reviewers. [Extracted from the article]

In the current research landscape, there are increasing demands for research to be innovative and cutting-edge. At the same time, concerns are voiced that as a consequence of neoliberal regimes of research governance, innovative research becomes impeded. In this paper, I suggest that to gain a better understanding of these dynamics, it is indispensable to scrutinise current demands for innovativeness as a distinct way of ascribing worth to research. Drawing on interviews and focus groups produced in a close collaboration with three research groups from the crop and soil sciences, I develop the notion of a project-innovation regime of valuation that can be traced in the sphere of research. In this evaluative framework, it is considered valuable to constantly re-invent oneself and take 'first steps' instead of 'just' following up on previous findings. Subsequently, I describe how these demands for innovativeness relate to and often clash with other regimes of valuation that matter for researchers' practices. I show that valuations of innovativeness are in many ways bound to those of productivity and competitiveness, but that these two regimes are nevertheless sometimes in tension with each other, creating a complicated double bind for researchers. Moreover, I highlight that also the project-innovation regime as such is not always in line with what researchers considered as a valuable progress of knowledge, especially because it entails a de-valuation of certain kinds of long-term epistemic agendas. I show that prevailing pushes for innovativeness seem to be based on a rather short-sighted temporal imaginary of scientific progress that is hardly grounded in the complex realities of research practices, and that they can reshape epistemic practices in potentially problematic ways. [ABSTRACT FROM AUTHOR]

This article is part of a series of brief commentaries to highlight papers that have resulted in important and distinctly new perspectives in crop science. A criterion for selection of papers is that they must have been published at least 20 yr ago to allow for a long‐range perspective in assessment of the papers. The current article briefly reviews the paper by M. Wayne Adams published in 1967 that provided original insights about compensation in the components of seed number and seed yield in determining crop yield. Adams reviewed experimental results in a large number of crop species and discovered a consistent negative correlation between seed number and mean seed mass. He labeled this negative correlation as "component compensation" in the formation of yield. He hypothesized that component compensation resulted from limiting nutrient‐metabolite availability to support developing reproductive structures. Ultimately, the retained seeds would be filled to the extent allowed by the supply of nutrient‐metabolites so that there was compensation between seed number and individual seed mass. [ABSTRACT FROM AUTHOR]

Understanding the growth and development of individual plants is of central importance in modern agriculture, crop breeding, and crop science. To this end, using 3D data for plant analysis has gained attention over the last years. High-resolution point clouds offer the potential to derive a variety of plant traits, such as plant height, biomass, as well as the number and size of relevant plant organs. Periodically scanning the plants even allows for performing spatio-temporal growth analysis. However, highly accurate 3D point clouds from plants recorded at different growth stages are rare, and acquiring this kind of data is costly. Besides, advanced plant analysis methods from machine learning require annotated training data and thus generate intense manual labor before being able to perform an analysis. To address these issues, we present with this dataset paper a multi-temporal dataset featuring high-resolution registered point clouds of maize and tomato plants, which we manually labeled for computer vision tasks, such as for instance segmentation and 3D reconstruction, providing approximately 260 million labeled 3D points. To highlight the usability of the data and to provide baselines for other researchers, we show a variety of applications ranging from point cloud segmentation to non-rigid registration and surface reconstruction. We believe that our dataset will help to develop new algorithms to advance the research for plant phenotyping, 3D reconstruction, non-rigid registration, and deep learning on raw point clouds. The dataset is freely accessible at https://www.ipb.uni-bonn.de/data/pheno4d/. [ABSTRACT FROM AUTHOR]

Human agriculture is a universal subject of study across all disciplines of the natural, humanities and social sciences. Since the Renaissance, however, “agricultural science” has mainly focused on European agriculture, and it is only relatively recently that indigenous African agriculture has been fairly treated as an object of modern science. In this paper, the brief history of studies on African agriculture in Europe and Japan and outline the main issues and trends in the field in recent years. Since the 2000s, studies on African agriculture in Japan has been vigorously pursued with a generally impartial and objective attitude in the fields of agricultural origins and history, anthropology of farming and pastoralism, crop science and breeding, soil and environment, crop protection, animal husbandry and veterinary science, agricultural economics and rural sociology. Modern agriculture faces fundamental problems how it produces more food and how it produces food sustainably while conserving biodiversity. Overcoming these conflicting problems is the ultimate challenge in African agricultural studies, and further development of research by various methods in various fields is expected. [ABSTRACT FROM AUTHOR]

This article is part of a series of brief commentaries to highlight papers that have resulted in important and distinctly new perspectives in crop science. A criterion for selection of papers is that they must have been published at least 20 yr ago to allow for a long‐range perspective in assessment of the papers. The current article briefly reviews the paper by M.Y. Siddiqi, A.D.M. Glass, T.J. Ruth, and T.W. Rufty, Jr. published in 1990 that investigated the kinetics of nitrate influx by barley (Hordeum vulgare L.) seedlings. Using 13NO3−, they documented the existence of two influx systems. One was inducible and nitrate influx saturated under low nitrate concentrations. The second was noninducible and expressed a linear increase in nitrate influx over high nitrate concentrations. Key transformative results from this study were the demonstration that both systems were under negative feedback control based on root nitrate concentration. [ABSTRACT FROM AUTHOR]

This article is part of a series of brief commentaries to highlight papers that have resulted in important and distinctly new perspectives in crop science. A criterion for selection of papers is that they must have been published at least 20 yr ago to allow for a long‐range perspective in assessment of the papers. The current article briefly reviews the paper by Harold L. Penman published in 1948 that offered an original analysis of approaches to estimate evaporation from natural surfaces. He developed two approaches: one based on a sink strength model, and the second on an energy balance model. He compared the predictions of these approaches to his experimental observations of evaporation from open water, bare soil, and grass. He found each of the models did well (r ≈ 0.8) in predicting open water evaporation. The evaporation from bare soil and grass was less than that from the open water, and the predicted evaporation amounts were variable even when normalized by open water evaporation. Even though Penman warned that aspects of the approaches were empirical, the energy balance model remains a mainstay in predicting crop water loss. [ABSTRACT FROM AUTHOR]

High-fat diet is associated with hypercholesterolemia and seminal alterations in White New Zealand rabbits. We have previously reported disorders in the development of the manchette-acrosome complex during spermiogenesis and decreased testicular efficiency in hypercholesterolemic rabbits. On the other hand, olive oil incorporated into the diet improves cholesterolemia and semen parameters affected in hypercholesterolemic rabbits. In this paper, we report the recovery—with the addition of olive oil to diet—from the sub-cellular mechanisms involved in the shaping of the sperm cell and testicular efficiency altered in hypercholesterolemic rabbits. Using morphological (structural, ultra-structural and immuno-fluorescence techniques) and cell biology techniques, a reorganization of the manchette and related structures was observed when olive oil was added to the high-fat diet. Specifically, actin filaments, microtubules and lipid rafts—abnormally distributed in hypercholesterolemic rabbits—were recovered with dietary olive oil supplementation. The causes of the decline in sperm count were studied in the previous report and here in more detail. These were attributed to the decrease in the efficiency index and also to the increase in the apoptotic percentage in testis from animals under the high-fat diet. Surprisingly, the addition of olive oil to the diet avoided the sub-cellular, efficiency and apoptosis changes observed in hypercholesterolemic rabbits. This paper reports the positive effects of the olive oil addition to the diet in the recovery of testicular efficiency and normal sperm shaping, mechanisms altered by hypercholesterolemia. [ABSTRACT FROM AUTHOR]

It is widely recognized that increasing agricultural production to the levels needed to feed an expanding world population requires sharply increased public investment in research and development and widespread adoption of new technologies, but funding for national and international agricultural research has rather declined in recent years. In this situation, priority setting has become increasingly important for allocating scarce research resources among competing needs to achieve greater impacts. Using partial equilibrium economic surplus models and poverty impact simulations, this paper assesses cassava research priorities in Africa, Latin America and Caribbean, and Asia based on the potential economic and poverty reduction impacts of alternative research and technology options. The results showed that efficient planting material production and distribution systems and sustainable crop and soil fertility management practices have the greatest expected economic and poverty reduction impacts in the three regions. Lack of clean planting materials is a major constraint to adoption and it is envisaged that efficient production and distribution systems for planting material can accelerate technology adoption by farmers. Similarly, sustainable crop and soil fertility management practices play a key role in closing the observed yield gaps, especially in Africa. The paper discusses the results of the priority assessment for key cassava research options and concludes with the implications for cassava research priorities. [ABSTRACT FROM AUTHOR]

Understanding processes in sources and sinks that contribute to crop yields has taken years of painstaking research. For crop yield improvement, processes need to be understood as standalone mechanisms in addition to how these mechanisms perform at the crop level; currently there is often a chasm between the two. Fundamental mechanisms need to be considered in the context of crop ideotypes and the agricultural environment which is often more water limited than carbon limited. Different approaches for improvement should be considered, namely is there genetic variation? Or if not, could genetic modification, genome editing, or alternative approaches be utilized? Currently, there are few examples where genetic modification has improved intrinsic yield in the field for commercial application in a major crop. Genome editing, particularly of negative yield regulators as a first step, is providing new opportunities. Here we highlight key mechanisms in source and sink, arguing that for large yield increases integration of key processes is likely to produce the biggest successes within the framework of crop ideotypes with optimized phenology. We highlight a plethora of recent papers that show breakthroughs in fundamental science and the promise of the trehalose 6-phosphate signalling pathway, which regulates carbohydrate allocation which is key for many crop traits. [ABSTRACT FROM AUTHOR]

This paper brings advances in weather data collection and modeling, and developments in socioeconomic climate microsimulations to bear on the analysis of the implications of climate change (CC) in the design of public policies to combat food insecurity. It uses new downscaled predictions of future climate in 2050, derived from three Earth System Models calibrated with a new historical weather station dataset for Peru. This climate data is used in a three-stage socioeconomic microsimulation model that includes climate risk, and deals with the endogeneity of incomes and simultaneity of expected food consumption and its variability. We estimate the impact of CC on agricultural yields, and find results consistent and fully bounded within what the global simulations literature has found, with yields falling up to 13% in some regions. However, we show that these drops (and increases) in yields translate to much smaller changes in food consumption, and also surprisingly, to very minor impacts on vulnerability to food insecurity. The document explores what explains this surprising result, showing that in addition to characteristics that are specific to Peru, there are household and market mediating mechanisms that are available in all countries, which explain how changes in yields, and corresponding farm incomes have a reduced impact in vulnerability to food insecurity. Finally, in light of these findings, we explore which policies might have greater impact in reducing food insecurity in contexts of hunger prevalence. [ABSTRACT FROM AUTHOR]

Recently, high-resolution magnetometry surveys have led to the discovery of a special category of buildings–so-called ‘mega-structures’–situated in highly visible positions in the public space of Tripolye giant-settlements of the late 5th and first half of the 4th millennium BCE. In this paper we explore what these buildings actually are and how they can contribute to the understanding of the development of social space in Tripolye giant-settlements. For this investigation, we linked newly obtained excavation data from the giant-settlement Maidanetske, Ukraine, with a much larger sample of such buildings from magnetic plans obtained in the region between the Carpathian foothills and the Dnieper River. Accordingly, Tripolye mega-structures represent a particular kind of integrative building documented in many non-ranked ethnographic contexts. Based on our results we are interpreting that these buildings were used for various ritual and non-ritual activities, joint decision-making, and the storage and consumption of surplus. In Tripolye giant-settlements at least three different categories of mega-structures could be identified which most likely represent different levels of socio-political integration and decision-making. The emergence of this hierarchical system of high-level integrative buildings for the whole community and different low-level integrative architectures for certain segments of local communities was related to the rise of Tripolye mega-sites. The presence of different integrative levels most likely reflects the fusion of different previously independent communities in the giant-settlements. Later in the mega-site development, we observe how low-level integrative buildings increasingly lose their importance indicated by shrinking size and, finally, their disappearance. This observation might indicate that the power which was previously distributed across the community was transferred to a central institution. It is argued that the non-acceptance of this concentration of power and the decline of lower decision-making levels might be a crucial factor for the disintegration of Tripolye giant-settlements around 3600 BCE. [ABSTRACT FROM AUTHOR]

Our food security depends on finding a sustainable alternative to rock phosphate for fertilizer production. Furthermore, over 2 billion people worldwide are currently affected by micronutrient deficiencies, and crop concentrations of essential minerals are declining. This paper examines whether a novel multi-element fertilizer, Thallo®, can produce crop yields comparable to conventional rock phosphate derived fertilizers, and have an additional benefit of increasing essential mineral concentrations. Thallo®, produced from abattoir and recycled industrial by-products, was tested against conventional mineral fertilizers in a pot trial with wheat and grass. In soil, yields were comparable between the fertilizer types, but, in a low-nutrient substrate, Thallo® showed a yield benefit. Elemental concentrations in the plant material typically reflected the relative concentrations in the fertilizer, and Thallo® fertilized plants contained significantly more of some essential elements, such as selenium and zinc. Furthermore, concentrations of the toxic element cadmium were significantly lower in Thallo® fertilized crops. Among the fertilizers, manganese concentrations were greatest in the Thallo®, but within the fertilized plants, they were greatest under the mineral fertilizer, showing the complexity of assessing whether nutrients will be taken up by crops. In summary, fertilizers from livestock waste have the potential to improve wheat and grass concentrations of essential elements while maintaining yields. [ABSTRACT FROM AUTHOR]

Barley is one of the most relevant crops worldwide and an essential component of agriculture in Europe in general, and in the Mediterranean region in particular. As cropping areas will hardly rise in the future, yield must be improved to enhance global crop production. Naturally, understanding how yield is affected by environmental and genetic factors in two- and six-rowed barley can help us to develop more efficient management and breeding strategies to increase current yield gains. We aimed to determine the relative importance of genetic and environmental factors on numerical and physiological components of GN for two- and six-rowed barley types. To generate a large and unbiased database, we compiled data of yield and its numerical and physiological components from crop-based experiments (i.e., excluding controlled-conditions experiments and/or approaches using isolated plants) reported in figures and tables in every single paper having the word "barley" in the title published over 25 years in four rigorous and prestigious international journals: Field Crop Research, European Journal of Agronomy, Crop Science and Crop and Pasture Science (formerly Australian Journal of Agricultural Research) between January 1996 and December 2021, both inclusive. Spike number (SN) was the most relevant numerical component explaining GN regardless of the source of variation. Regarding physiological components, it seemed that when the driving force was environmental factors, spike dry weight at flowering (SDW F) was more relevant than fruiting efficiency (FE); whilst when the differences were due to genotypic factors, clearly the FE was the component mostly responsible for the changes in GN. When the analysis was restricted to two- and six-rowed barley types, GN improvements were mainly explained by changes in SN for both two- and six-rowed barley types. However, when the physiological components were considered, the responsiveness of GN was more related to SDW F than to FE in two-rowed genotypes, while the opposite was true for the six-rowed type. In barley, SN always explained the responses of GN better than grain number per spike (GNS), regardless the source of variation and the type of barley. Respect to the physiological components, environmental factors affected GN mainly through affecting SDW F , while genotypic factors affected GN through affecting FE. SDW F and FE were more relevant for explaining changes in GN two- and six-rowed barleys, respectively. Breeders and agronomists can be aware that it will be more likely to achieve significant gains in yield through focusing more on SN than on GNS regardless of the barley type, whilst regarding the physiological components it would be more relevant to focus on SDW F in two-rowed barley, and on FE in six-rowed barley. • We quantified grain number components depending on source of variation in barley. • Spike number (SN) explaining grain number regardless of the source of variation. • Spike dry weight (SDW F) was the most relevant component for environment factor. • Fruiting efficiency was more relevant for genotypic factor. • Grain number was more related to SDW F in two-rowed, while FE in six-rowed type. [ABSTRACT FROM AUTHOR]

In natural capital accounting, ecosystems are assets that provide ecosystem services to people. Assets can be measured using both physical and monetary units. In the international System of Environmental-Economic Accounting, ecosystem assets are generally valued on the basis of the net present value of the expected flow of ecosystem services. In this paper we argue that several additional conceptualisations of ecosystem assets are needed to understand ecosystems as assets, in support of ecosystem assessments, ecosystem accounting and ecosystem management. In particular, we define ecosystems’ capacity and capability to supply ecosystem services, as well as the potential supply of ecosystem services. Capacity relates to sustainable use levels of multiple ecosystem services, capability involves prioritising the use of one ecosystem service over a basket of services, and potential supply considers the ability of ecosystems to generate services regardless of demand for these services. We ground our definitions in the ecosystem services and accounting literature, and illustrate and compare the concepts of flow, capacity, capability, and potential supply with a range of conceptual and real-world examples drawn from case studies in Europe and North America. Our paper contributes to the development of measurement frameworks for natural capital to support environmental accounting and other assessment frameworks. [ABSTRACT FROM AUTHOR]

Background: Tobacco industry interference has been identified as the greatest obstacle to the implementation of evidence-based measures to reduce tobacco use. Understanding and addressing industry interference in public health policy-making is therefore crucial. Existing conceptualisations of corporate political activity (CPA) are embedded in a business perspective and do not attend to CPA's social and public health costs; most have not drawn on the unique resource represented by internal tobacco industry documents. Building on this literature, including systematic reviews, we develop a critically informed conceptual model of tobacco industry political activity.Methods and Findings: We thematically analysed published papers included in two systematic reviews examining tobacco industry influence on taxation and marketing of tobacco; we included 45 of 46 papers in the former category and 20 of 48 papers in the latter (n = 65). We used a grounded theory approach to build taxonomies of "discursive" (argument-based) and "instrumental" (action-based) industry strategies and from these devised the Policy Dystopia Model, which shows that the industry, working through different constituencies, constructs a metanarrative to argue that proposed policies will lead to a dysfunctional future of policy failure and widely dispersed adverse social and economic consequences. Simultaneously, it uses diverse, interlocking insider and outsider instrumental strategies to disseminate this narrative and enhance its persuasiveness in order to secure its preferred policy outcomes. Limitations are that many papers were historical (some dating back to the 1970s) and focused on high-income regions.Conclusions: The model provides an evidence-based, accessible way of understanding diverse corporate political strategies. It should enable public health actors and officials to preempt these strategies and develop realistic assessments of the industry's claims. [ABSTRACT FROM AUTHOR]

This article is part of a series of brief commentaries to highlight papers that have resulted in important and distinctly new perspectives in crop science. A criterion for selection of papers is that they must have been published at least 20 yr ago to allow for a long‐range perspective in assessment of the papers. The current article briefly reviews the paper by C.M. Donald and J. Hamblin published in 1976 that provided original insights about the role of harvest index (defined by them as the ratio of economic yield to aboveground mass) in influencing crop yield. Donald and Hamblin reviewed experimental results showing that harvest index was relatively stable across variations in plant size, had high heritability, and was associated with high grain yield. Although their observations were confirmed in subsequent tests, inconsistent results in plant selection in breeding programs for high yield based on harvest index has discouraged the use of harvest index as a basis for selection. Nevertheless, high harvest index is now well ingrained as an essential plant characteristic for high crop yields. [ABSTRACT FROM AUTHOR]

Demand for spring onion seeds is variable and maintaining its supply is crucial to the success of seed companies. Spring onion seed demand forecasting, which can help reduce the high operational costs increased by long-period propagation and complex logistics, has not previously been investigated yet. This paper provides a novel perspective on spring onion seed demand forecasting and proposes a hybrid Holt-Winters and support vector machine (SVM) forecasting model. The model uses dynamic factors, including historical seed sales, seed inventory, spring onion crop market price and weather data, as inputs to forecast spring onion seed demand. Forecasting error, i.e. the difference between actual and forecasted demand, is assessed. Two advanced machine learning models are trained on the same dataset as benchmark models. Numerical experiments using actual commercial sales data for three spring onion seed varieties show the proposed hybrid model outperformed the statistical-based models for all three forecasting errors. Seed inventory, spring onion crop market price and historical seed sales are the most important dynamic factors, among which seed inventory has short-term influence while other two have mid-term influence on seed demand forecasting. The absolute minimum temperature is the only factor having long-term influence. This study provides a promising spring onion seed demand forecasting model that helps understand the relationships between seed demand and other dynamic factors and the model could potentially be applied to demand forecasting of other crop seeds to reduce total operational costs. [ABSTRACT FROM AUTHOR]

When the unmanned aerial vehicle (UAV) is used for aerial spraying, the downwash airflow generated by the UAV rotor will interact with the crop canopy and form a conical vortex shape in the crop plant. The size of the vortex will directly affect the outcome of the spraying operation. Six one-way spraying were performed by the UAV in a rice field with different but random flying altitude and velocities within the optimal operational range to form different vortex patterns. The spraying reagent was clear water, which was collected by water sensitive paper (WSP), and then the WSP was analyzed to study the droplets deposition effects in different vortex states. The results showed that the formation of the vortex significantly influenced the droplet deposition. To be specific, the droplet deposition amount in the obvious-vortex (OV) state was about 1.5 times of that in the small-scale (SV) vortex state, and 7 times of that in the non-vortex (NV) state. In the OV state, the droplets mainly deposited directly below and on both sides of the route. The deposition amount, coverage rate and droplet size increased from top to bottom of the crops with the deposition amount, coverage rate, and volume median diameter (VMD) ranging 0.204–0.470 μL/cm2, 3.31%-7.41%, and 306–367μm, respectively. In the SV state, droplets mainly deposited in the vortex area directly below the route. The deposition amount in the downwind direction was bigger than that in the upwind direction. The maximum of deposition amount, coverage rate and droplet size were found in the middle layer of the crops, the range are 0.177–0.334μL/cm2, 2.71%-5.30%, 295–370μm, respectively. In the NV state, the droplet mainly performed drifting motion, and the average droplet deposition amount in the downwind non-effective region was 29.4 times of that in the upwind non-effective region and 8.7 times of the effective vortex region directly below the route. The maximum of deposition amount, coverage rate and droplet size appeared in the upper layer of the crop, the range are 0.006–0.132μL/cm2, 0.17%-1.82%, 120–309μm, respectively, and almost no droplet deposited in the middle and lower part of the crop. The coefficient of variation (CV) of the droplet deposition amount was less than 40% in the state of obvious-vortex and small-scale vortex, and the worst penetration appeared in the non-vortex amounting to 65.97%. This work offers a basis for improving the spraying performance of UAV. [ABSTRACT FROM AUTHOR]

The current physical goods economy produces materials by extracting finite valuable resources without taking their end of the life and environmental impact into account. Mycelium-based materials offer an alternative fabrication paradigm, based on the growth of materials rather than on extraction. Agricultural residue fibres are inoculated with fungal mycelium, which form an interwoven three-dimensional filamentous network binding the feedstock into a lightweight material. The mycelium-based material is heat-killed after the growing process. In this paper, we investigate the production process, the mechanical, physical and chemical properties of mycelium-based composites made with different types of lignocellulosic reinforcement fibres combined with a white rot fungus, Trametes versicolor. This is the first study reporting the dry density, the Young’s modulus, the compressive stiffness, the stress-strain curves, the thermal conductivity, the water absorption rate and a FTIR analyse of mycelium-based composites by making use of a fully disclosed protocol with T. versicolor and five different type of fibres (hemp, flax, flax waste, softwood, straw) and fibre processings (loose, chopped, dust, pre-compressed and tow). The thermal conductivity and water absorption coefficient of the mycelium composites with flax, hemp, and straw have an overall good insulation behaviour in all the aspects compared to conventional materials such as rock wool, glass wool and extruded polystyrene. The conducted tests reveal that the mechanical performance of the mycelium-based composites depends more on the fibre processing (loose, chopped, pre-compressed, and tow), and size than on the chemical composition of the fibres. These experimental results show that mycelium-composites can fulfil the requirements of thermal insulation and have the potential to replace fosile-based composites. The methology used to evaluate the suitability and selection of organic waste-streams proved to be effective for the mycelium-material manufacturing applications. [ABSTRACT FROM AUTHOR]

Constructed wetlands are sustainable technologies for the treatment of wastewater. These biological systems have been widely studied throughout the world for more than 30 years; however, most studies have focused on the effects of design and engineering on pollutant removal from wastewater. Undoubtedly, agro-technical aspects have been given too little consideration by research. This paper reports the main results of a set of experiments carried out on two pilot horizontal subsurface flow systems in Sicily (Italy). Festuca, Lolium and Pennisetum spp. in combination and three emergent macrophytes–Arundo donax L., Cyperus alternifolius L. and Typha latifolia L.–alone, were assessed. The aim of the study was to demonstrate that, under predetermined hydraulic and design conditions, the choice of plant species and the management of the vegetation can significantly affect the pollutant removal performance of constructed wetlands. In addition, wastewater (after treatment) can also be used for agricultural purposes leading to increased sustainability in agricultural systems. Arundo and Typha-planted units performed better than Cyperus-planted units in terms of chemical, physical and microbiological contaminant removal. All the species adapted extremely well to wetland conditions. Polyculture systems were found to be more efficient than monocultures in the removal of dissolved organic compounds. The reuse of treated wastewater for the irrigation of open fields and horticultural crops led to significant savings in the use of freshwater and fertilizers. The results of physical-energy characterization of A. donax above-ground plant residues and pellets highlighted the fact that a constructed wetland could also be a potential source of bioenergy. [ABSTRACT FROM AUTHOR]

Concerns about the use of child labor in West African cocoa production became widespread in the early 2000s in many high-income countries. In 2015 in Ghana, 91.8% (or a total of 878,595) of the children working in the cocoa sector were involved in a form of hazardous work. Child labor in cocoa production is not just a symptom of poverty but also a contributing factor, as children often forgo a formal education to work in cocoa orchards. Current Ghanaian law prohibits child labor, but, with many cocoa households living in poverty, child labor becomes a necessity for survival, and as such, current child labor laws are rarely enforced. Therefore, an effective policy that eliminates child labor could compensate farmers by providing an economic incentive. In this paper, we develop and calibrate a farm household model to estimate the cocoa price premium necessary to eliminate child labor from cocoa production while leaving the farm household welfare unchanged. This welfare-neutral price premium removes the negative effects of eliminating child labor for the farm household. Varying degrees of child labor exists, with certain forms posing a greater risk to children’s wellbeing. The results show that eliminating the worst forms of child labor would require a cocoa price premium of 2.81% and eliminating regular work (non-hazardous work but over the maximum hours allowed for a child) and the worst forms would require an 11.81% premium, which could be paid for by the well-established Ghanaian Cocoa Marketing Board. An incentive for the Cocoa Marketing Board to pay the price premium and monitor and enforce this policy would be the ability to differentiate their cocoa as child-labor free and not lose market share to countries who cannot currently certify this practice. [ABSTRACT FROM AUTHOR]

Convolutional neural networks (CNNs) can not only classify images but can also generate key features, e.g., the Google neural network that learned to identify cats by simply watching YouTube videos, for the classification. In this paper, crop models are distilled by CNN to evaluate the ability of deep learning to identify the plant physiology knowledge behind such crop models simply by learning. Due to difficulty in collecting big data on crop growth, a crop model was used to generate datasets. The generated datasets were fed into CNN for distillation of the crop model. The models trained by CNN were evaluated by the visualization of saliency maps. In this study, three saliency maps were calculated using all datasets (case 1) and using datasets with spikelet sterility due to either high temperature at anthesis (case 2) or cool summer damage (case 3). The results of case 1 indicated that CNN determined the developmental index of paddy rice, which was implemented in the crop model, simply by learning. Moreover, CNN identified the important individual environmental factors affecting the grain yield. Although CNN had no prior knowledge of spikelet sterility, cases 2 and 3 indicated that CNN realized about paddy rice becoming sensitive to daily mean and maximum temperatures during specific periods. Such deep learning approaches can be used to accelerate the understanding of crop models and make the models more portable. Moreover, the results indicated that CNN can be used to develop new plant physiology theories simply by learning. [ABSTRACT FROM AUTHOR]

In the 2015 Paris Agreement, nations worldwide pledged emissions reductions (Nationally Determined Contributions—NDCs) to avert the threat of climate change, and agreed to periodically review these pledges to strengthen their level of ambition. Previous studies have analyzed NDCs largely in terms of their implied contribution to limit global warming, their implications on the energy sector or on mitigation costs. Nevertheless, a gap in the literature exists regarding the understanding of implications of the NDCs on countries’ Energy-Water-Land nexus resource systems. The present paper explores this angle within the regional context of Latin America by employing the Global Change Assessment Model, a state-of-the-art integrated assessment model capable of representing key system-wide interactions among nexus sectors and mitigation policies. By focusing on Brazil, Mexico, Argentina and Colombia, we stress potential implications on national-level water demands depending on countries’ strategies to enforce energy-related emissions reductions and their interplays with the land sector. Despite the differential implications of the Paris pledges on each country, increased water demands for crop and biomass irrigation and for electricity generation stand out as potential trade-offs that may emerge under the NDC policy. Hence, this study underscores the need of considering a nexus resource planning framework (known as “Nexus Approach”) in the forthcoming NDCs updating cycles as a mean to contribute toward sustainable development. [ABSTRACT FROM AUTHOR]

This paper highlights the importance of optimized shape index for agricultural management system analysis that utilizes the contiguous bands of hyperspectral data to define the gradient of the spectral curve and improve image classification accuracy. Currently, a number of machine learning methods would resort to using averaged spectral information over wide bandwidths resulting in loss of crucial information available in those contiguous bands. The loss of information could mean a drop in the discriminative power when it comes to land cover classes with comparable spectral responses, as in the case of cultivated fields versus fallow lands. In this study, we proposed and tested three new optimized novel algorithms based on Moment Distance Index (MDI) that characterizes the whole shape of the spectral curve. The image classification tests conducted on two publicly available hyperspectral data sets (AVIRIS 1992 Indian Pine and HYDICE Washington DC Mall images) showed the robustness of the optimized algorithms in terms of classification accuracy. We achieved an overall accuracy of 98% and 99% for AVIRIS and HYDICE, respectively. The optimized indices were also time efficient as it avoided the process of band dimension reduction, such as those implemented by several well-known classifiers. Our results showed the potential of optimized shape indices, specifically the Moment Distance Ratio Right/Left (MDRRL), to discriminate between types of tillage (corn-min and corn-notill) and between grass/pasture and grass/trees, tree and grass under object-based random forest approach. [ABSTRACT FROM AUTHOR]

This paper demonstrates the application of aerial multispectral images in cotton plant phenotyping. Four phenotypic traits (plant height, canopy cover, vegetation index, and flower) were measured from multispectral images captured by a multispectral camera on an unmanned aerial system. Data were collected on eight different days from two fields. Ortho-mosaic and digital elevation models (DEM) were constructed from the raw images using the structure from motion (SfM) algorithm. A data processing pipeline was developed to calculate plant height using the ortho-mosaic and DEM. Six ground calibration targets (GCTs) were used to correct the error of the calculated plant height caused by the georeferencing error of the DEM. Plant heights were measured manually to validate the heights predicted from the imaging method. The error in estimation of the maximum height of each plot ranged from -40.4 to 13.5 cm among six datasets, all of which showed strong linear relationships with the manual measurement (R2 > 0.89). Plot canopy was separated from the soil based on the DEM and normalized differential vegetation index (NDVI). Canopy cover and mean canopy NDVI were calculated to show canopy growth over time and the correlation between the two indices was investigated. The spectral responses of the ground, leaves, cotton flower, and ground shade were analyzed and detection of cotton flowers was satisfactory using a support vector machine (SVM). This study demonstrated the potential of using aerial multispectral images for high throughput phenotyping of important cotton phenotypic traits in the field. [ABSTRACT FROM AUTHOR]

Earthworms are primary candidates for national soil health monitoring as they are ecosystem engineers that benefit both food production and ecosystem services associated with soil security. Supporting farmers to monitor soil health could help to achieve the policy aspiration of sustainable soils by 2030 in England; however, little is known about how to overcome participation barriers, appropriate methodologies (practical, cost-effective, usefulness) or training needs. This paper presents the results from a pilot #60minworms study which mobilised farmers to assess over >1300 ha farmland soils in spring 2018. The results interpretation framework is based on the presence of earthworms from each of the three ecological groups at each observation (20 x 20 cm x 20 cm pit) and spatially across a field (10 soil pits). Results showed that most fields have basic earthworm presence and abundance, but 42% fields may be over-worked as indicated by absence/rarity of epigeic and/or anecic earthworms. Tillage had a negative impact (p < 0.05) on earthworm populations and organic matter management did not mitigate tillage impacts. In terms of farmer participation, Twitter and Farmers Weekly magazine were highly effective channels for recruitment. Direct feedback from participants included excellent scores in trust, value and satisfaction of the protocol (e.g. 100% would do the test again) and 57% would use their worm survey results to change their soil management practices. A key training need in terms of earthworm identification skills was reported. The trade-off between data quality, participation rates and fieldwork costs suggests there is potential to streamline the protocol further to #30minworms (5 pits), incurring farmer fieldwork costs of approximately £1.48 ha-1. At national scales, £14 million pounds across 4.7 M ha-1 in fieldwork costs per survey could be saved by farmer participation. [ABSTRACT FROM AUTHOR]

Seed moisture content (SMC) is an important attribute to seed quality. Maintaining seed dryness throughout supply chain (The Dry Chain) prevents seed germination and quality losses. Ambient relative humidity (RH) and temperature affect seed moisture and thereof seed moisture isotherm. Present study was conducted to compare the moisture adsorption isotherms of wheat, maize, cotton and quinoa seeds packed in hermetic Super Bag and traditional packaging materials including paper, polypropylene (PP), jute and cloth bags. Seeds were incubated at 60, 70, 80 and 90% static RH. Nearly straight line moisture isotherms for all crop seeds were obtained in Super Bag. Seed moisture contents increased in traditional packaging materials with increasing RH. At higher level of RH, moisture contents increased slightly (1–2%) in Super Bag, whereas this increase was much higher in traditional packaging materials (≈9% higher than original SMC at 90% RH). In second study, seeds were dried to 8 and 14% initial seed moisture contents using zeolite drying beads and were stored in hermetic and conventional packaging materials for a period of 18 months. For all crop seeds, germination was severely affected in all packaging materials both at 8 and 14% initial SMC except storage in Super Bag at 8% SMC. Wheat seed stored in Super Bag at 8% SMC almost maintained initial germination while germination of cotton, maize and quinoa seeds declined 7%, 14% and 30% respectively in Super Bag at 8% SMC. Seed storage in Super Bag can help to prevent the significant increase in seed moisture at higher RH as is evident from moisture isotherm study, thus helps to preserve quality of maize, wheat, cotton and quinoa seeds by maintaining The Dry Chain throughout the storage period. [ABSTRACT FROM AUTHOR]

This paper evaluates the development impacts of migration and remittances in migrant source communities by applying insights from the New Economics of Labor Migration (NELM) theory to Ethiopia’s migration. Using household survey data, we empirically evaluate how household participation in migration arises and so that the subsequent labor losses and the influx of remittances affect income sources and asset accumulation of smallholder farm households. To account several econometric issues and consistently estimate the impacts of migration and remittances, we adopted three-stage least-squares method complemented with endogeneity and multicollinearity test. Besides, using logistic and multinomial logistic regressions respectively, we estimate the determinants of the household migration decision to have migrants, as well as the probability of the household to send out temporary or permanent migrants. Findings suggest that larger and wealthier households are less likely to have migrant family members, while households living below the poverty line, as well as villages with the highest unemployment rate, are the most likely to have both temporary and permanent migrants. However, a rise in months spent out of agriculture has a significant negative effect on crop income and asset accumulation, but only for permanent migration. By contrast, the influx of remitted income from migrants has led to increased crop income and asset values in the form of land and livestock holdings. Finally, this manuscript provides more comprehensive evidence by showing the net-returns of migration in terms of initial lost-labor effects and the positive developmental impacts that it produces varied for households with different types of migration and production conditions. [ABSTRACT FROM AUTHOR]

This paper contributes to the contentious topic of whether shocks to agricultural commodity prices are permanent or transitory. This is an important issue with regards to forecasting, economic modelling of agricultural prices and risk management. Past studies have not accounted for important characteristics of agricultural prices that matter when testing whether shocks to prices are permanent or transitory. These include the presence or absence of a deterministic trend, the possible break in the trend, non‐stationary volatility, and the problem of the initial deviation of commodity prices from their long‐run mean or trend. We conduct a comprehensive test that incorporates all these characteristics known to plague agricultural commodity prices. Though the conclusion is mixed, the balance is in favour of agricultural price shocks being permanent in nature. This result departs from the general view that in theory, agricultural prices should be stationary, suggesting that the controversy of whether shocks to agricultural prices are temporary or permanent is not yet over. [ABSTRACT FROM AUTHOR]

This paper establishes the quantitative relationships between hail fall parameters and crop damages by examining the impacts of 49 hail hazard scenarios on cotton in the bud stage and boll stage. This study utilizes simulated cotton hail hazard to analyze the following data: hail size, hail fall density, and crop damages (i.e., defoliation rate, branch breaking rate, and the fruit falling rate). The results are as follows: 1) cotton vulnerability increased via an increase in crop damages as the hail hazard magnitude increased; 2) crop damages exhibit significant logistic relationships with hail diameter and hail fall density, and the fit was better at the bud stage than at the boll stage; 3) cotton is more vulnerable to hail hazard at the bud stage than at the boll stage, and the bud stage is a critical period for cotton hail disaster prevention and mitigation; and 4) damages to cotton plant at the bud stage and boll stage were less sensitive to hail size from hail fall density. Thus, we suggest that hail diameter can be used as the priority indicator to predict hail-induced crop damages. These results provide a sound basis for developing a comprehensive evaluation of hail damage in cotton, which is crucial for promoting sustainable cotton production. We recommend that the impacts of hail-induced crop damages on yield and fiber quality need to be addressed further in future studies. [ABSTRACT FROM AUTHOR]

This paper explores the social inclusiveness of agricultural extension services in India. We estimate the probability and frequency of farmers’ access to extension services and resulting changes in crop income across different caste groups. The literature suggests that caste-based social segregation manifests in various spheres of life, and perpetuates economic inequality and oppression. An econometric analysis of nationally-representative data from rural India verifies this with respect to the agricultural sector. Farmers belonging to the socially-marginalized castes are found to have a lower chance of accessing the public extension services, primarily due to their inferior resource-endowment status. Contacting extension agents at least once increased the average annual crop income by about 12 thousand Indian rupees per household, which is equivalent to 36% of the annual crop income of those without access to extension services. There exists significant impact heterogeneity. Farmers from the socially-marginalized castes hardly benefited from accessing the extension services. Based on these observations, we have developed a number of policy recommendations that could improve the social inclusiveness of agricultural development strategies in rural India. [ABSTRACT FROM AUTHOR]

Metric data are usually assessed on a continuous scale with good precision, but sometimes agricultural researchers cannot obtain precise measurements of a variable. Values of such a variable cannot then be expressed as real numbers (e.g., 1.51 or 2.56), but often can be represented by intervals into which the values fall (e.g., from 1 to 2 or from 2 to 3). In this situation, statisticians talk about censoring and censored data, as opposed to missing data, where no information is available at all. Traditionally, in agriculture and biology, three methods have been used to analyse such data: (a) when intervals are narrow, some form of imputation (e.g., mid‐point imputation) is used to replace the interval and traditional methods for continuous data are employed (such as analyses of variance [ANOVA] and regression); (b) for time‐to‐event data, the cumulative proportions of individuals that experienced the event of interest are analysed, instead of the individual observed times‐to‐event; (c) when intervals are wide and many individuals are collected, non‐parametric methods of data analysis are favoured, where counts are considered instead of the individual observed value for each sample element. In this paper, we show that these methods may be suboptimal: The first one does not respect the process of data collection, the second leads to unreliable standard errors (SEs), while the third does not make full use of all the available information. As an alternative, methods of survival analysis for censored data can be useful, leading to reliable inferences and sound hypotheses testing. These methods are illustrated using three examples from plant and crop sciences. [ABSTRACT FROM AUTHOR]

Studying soil nutrient variability and its effect on the growth and development of crops under a traditional tillage mode is the foundation for comprehensively implementing precision agriculture policies at the field scale and ensuring excellent crop management. In this paper, a 28.5 hm2 winter wheat field under the traditional cultivation model in Tianzhuang town of Huantai County was selected as the research area. The mesh point method was utilized for sampling (60×60 m), and the characteristics of soil available nitrogen (AN), available phosphorus (AP) and available potassium (AK) variations in the before sowing, reviving, jointing, and filling stages of winter wheat were analyzed using geostatistical and GIS methods. Moreover, Pearson correlation analysis was used to study the response of wheat growth and development to soil nutrient variations. As the growth stages progressed, 1) each nutrient showed the characteristics of low-high-low and moderate variability. The highest AN and AK contents were found at the reviving stage, while AP reached a turning point at the jointing stage. The order of variability of each nutrient was AN>AP>AK. 2) The nutrient variations first increased and then decreased and showed medium to strong spatial correlation. The three nutrients were strongly spatially correlated in the before sowing stage and moderately spatially correlated during the reviving stage. During the jointing and filling stages, AN had moderate spatial correlation, and AP and AK had strong spatial correlation. The spatial correlation of each nutrient was the weakest in the reviving stage, and the spatial correlation of AN was strongest in the before sowing stage, while the spatial correlations of AP and AK were strongest in the jointing stage. The spatial correlation of each soil nutrient decreased from the before sowing stage to the reviving stage and from the jointing stage to the filling stage, and the spatial correlation increased from the reviving stage to the jointing stage. 3) The soil nutrient content first increased and then decreased, and the grades of the nutrients gradually decreased. 4) The correlation between soil nutrients and wheat growth gradually increased. AN had the highest correlation with wheat growth, followed by AK and AP. The effect of soil nutrients on the growth of wheat at the reviving stage was greater than the effect of nutrients in the current stage. The growth of wheat at the jointing stage was mainly influenced by nutrients in the current stage, while the growth of wheat at the filling stage was influenced by the nutrient contents of both the previous and current stages. Thus, the date of fertilizer supplementation should be postponed properly. In this study, the soil nutrient dynamics and their influence on the growth of wheat during the winter wheat growth period under the traditional field model were well described, and these results could provide a theoretical basis for the precision management of soil nutrients in the northern winter wheat area where the planting environment and cultivation management are relatively uniform. [ABSTRACT FROM AUTHOR]

Driven by factors such as an increased reliance on genetically modified crops, government policies, and market forces, the crop mix in South Dakota and elsewhere in the United States has become less diverse and moved toward the production of corn and soybeans as the most predominant cash crops over the past two decades. Coinciding with a reduced complexity of crop rotation practices, the prevalence of mono-cropping has increased and crop chemical usage has changed as well. Overall, the reduced reliance on traditional crop rotation practices for mitigating pests corresponds with an increase in crop acres treated with insecticides, expressed as a proportion of total cropland acres, and referred to in the literature as the extensive usage of insecticides. In this paper, we identify how changing cropping patterns in South Dakota have affected the extensive usage of insecticides, an aspect often overlooked by producers and policy makers. Results indicate that increased corn production has contributed to an increase in the share of cropland acres treated with insecticides at the county level in eastern South Dakota. [ABSTRACT FROM AUTHOR]

Recent studies highlight a growing concern over the limited adoption of climate smart agricultural (CSA) practices despite their potential benefits on adaptation, mitigation and productivity. Literature indicates several factors behind the lack of adoption including socio-demographic and economic conditions, agro-ecological scales and the nature of the practices. This paper examines to what extent and under which conditions such factors influence the adoption of CSA practices at farm, household and community level across three study sites in different continents: Vietnam, Nicaragua and Uganda. While cost benefit analysis (CBA) is employed to assess the farm-level profitability of CSA practices, the aggregate community impact disaggregated by different groups of farmer typologies with specific socio-economic features is derived from the adoption rate estimated by the relative advantage of practices and the income level of each group. Our main findings show great variation of farm-profitability of CSA practices across scales. Similar practices could generate different profitability depending on crop typologies, input access and prices, household types and local context. Regarding the aggregate profitability of CSA practices at regional scale, we found that under particular conditions, relevant factors of adoption matter to the adoption pattern and thereby affects the ranking. Such conditions include (i) high income inequality, (ii) large profitability gap of prioritized CSA practices, and (iii) large proportion of cost and benefit of the practices in the level of income. This study contributes to enhancing the prioritization process of CSA practices and provides practical guidance for research and policy to tailor the investment to appropriate end-users to assure the greatest impact for the community. [ABSTRACT FROM AUTHOR]

Background: The 2015 earthquake in Nepal caused massive damages and triggered relief activities to minimize human suffering. The post-earthquake nutrition and food security situation in the hardest hit areas remains uncertain. Methods: Two national cross-sectional surveys were conducted in 2014 and 2016 among households (HH) with pre-school aged children or newly married women. Of the 21 village development committees (VDCs) included in this sample, 7 fell within “earthquake-affected” areas. This paper presents data from 982 HH, 1015 women, and 883 children from 2014 and 1056 HH, 1083 women, and 998 children from 2016 living in these areas, with longitudinal overlap of about 55%. Prevalence estimates and 95% confidence intervals were calculated, and logistic regression was used to calculate p-values, both using robust estimates of standard errors to account for clustering. Results: From 2014 to 2016, child wasting (weight-for-height z score <-2) fell from 4.5% (95% CI 3.3%– 6.1%) to 2.1% (1.4%– 3.1%) and food insecurity (assessed using the household food insecurity access scale) dropped from 17.6% (11.7%– 25.6%) to 12.4% (6.9%– 21.2%). Child stunting prevalence remained similar at both time-points. Improvements were also evident in dietary diversity and breastfeeding indicators. Conclusions: Nutrition and food security conditions remained comparable or improved one year after the earthquake despite evidence of structural and other damage. Livelihood resilience to shocks and/or effective nutrition, food or health interventions may have helped buffer the impact on nutrition, although this hypothesis requires further exploration. [ABSTRACT FROM AUTHOR]

The global production of cereal straw as an agricultural by-product presents a significant source of biomass, which could be used as feedstock for the production of second generation biofuels by fermentation. The production of sugars for fermentation is an important measure of straw quality and in its suitability for biofuel production. In this paper, we present a characterization of straw digestibility from a wide range of cereal. Our main objective is to evaluate the variability of fermentable sugars released from different species including wheat (Triticum durum L., Triticum aestivum L.), barley (Hordeum vulgare L.) and triticale (X Triticosecale Wittmack). To this end, we adapted a saccharification method (IAS Method) capable of detecting significant differences of released sugars between cultivars and species, while using separately another method that would serve as a control and with which we could contrast our results (CNAP method). ANOVA analyses revealed that barley has a higher saccharification potential than wheat and triticale and shows more variation between genotypes. Thus, populations derived from crosses among them such as Steptoe × Morex and OWB Dominant × OWB Recessive hold potential for the identification of genetic basis for saccharification-related traits. The correlation of glucose released between the two methods was moderate (R2 = 0.57). An evaluation of the inter- and intra- specific correlation between a number of chemical and agronomical parameters and saccharification suggests that the cell wall thickness and lignin content in straw could be used in breeding programs for the improvement of the saccharification potential. Finally, the lack of correlation between grain yield and saccharification suggests that it would be possible to make a selection of genotypes for dual purpose, low recalcitrance and grain yield. [ABSTRACT FROM AUTHOR]

Maintaining crop outputs to feed its large population with limited resources while simultaneously mitigating carbon emissions are great challenges for China. Improving the efficiency of resource use in crop production is important in reducing carbon emissions. This paper constructs a methodological framework combining emergy-based indicator accounting and a nonseparable undesirable output slack-based measurement (SBM) data envelopment analysis (DEA) model. This framework is used to explore the efficiency of inputs and outputs and the greenhouse gas (GHG) emissions reduction potential for crop production systems, using Zhejiang province, China, as a case study. It is found that an emergy synthesis and a nonseparable undesirable output SBM-DEA framework is compatible with the case study. Crop production in Zhejiang province has relied heavily on an increase in agrochemical inputs to maintain agricultural output. Energy and chemical fertilizer use are determined as the province’s major carbon emissions sources. Although carbon emissions per unit of monetary output has decreased sharply, the carbon emissions per unit emergy output has increased, demonstrating a high carbon intensity reality. The DEA highlighted the differences in crop production efficiency, resource factor redundancy and carbon mitigation potential in the different prefectures of the province. To conclude this research, policies to support low carbon agriculture development, including subsidizing low carbon agriculture technology development and expansion and the cancellation of subsidies to high carbon production factors, such as chemical fertilizer production and sales, are discussed to conclude the research. [ABSTRACT FROM AUTHOR]

Background: Climate change is affecting food systems globally, with implications for food security, nutrition, and the health of human populations. There are limited data characterizing the current and future consequences of climate change on local food security for populations already experiencing poor nutritional indicators. Indigenous Amazonian populations have a high reported prevalence of nutritional deficiencies. This paper characterizes the food system of the Shawi of the Peruvian Amazon, climatic and non-climatic drivers of their food security vulnerability to climate change, and identifies potential maladaptation trajectories. Methods and findings: Semi-structured interviews with key informants (n = 24), three photovoice workshops (n = 17 individuals), transect walks (n = 2), a food calendar exercise, and two community dissemination meetings (n = 30 individuals), were conducted within two Shawi communities in Balsapuerto District in the Peruvian Loreto region between June and September of 2014. The Shawi food system was based on three main food sub-systems (forest, farming and externally-sourced). Shawi reported collective, gendered, and emotional notions related to their food system activities. Climatic and non-climatic drivers of food security vulnerability among Shawi participants acted at proximal and distal levels, and mutually reinforced key maladaptation trajectories, including: 1) a growing population and natural resource degradation coupled with limited opportunities to increase incomes, and 2) a desire for education and deforestation reinforced by governmental social and food interventions. Conclusion: A series of maladaptive trajectories have the potential to increase social and nutritional inequities for the Shawi. Transformational food security adaptation should include consideration of Indigenous perceptions and priorities, and should be part of Peruvian food and socioeconomic development policies. [ABSTRACT FROM AUTHOR]

A large amount of medical waste is produced during disaster relief, posing a potential hazard to the habitat and the environment. A comprehensive understanding of the composition and characteristics of medical waste that requires management is one of the most basic steps in the development of a plan for medical waste management. Unfortunately, limited reliable information is available in the open literature on the characteristics of the medical waste that is generated at disaster relief sites. This paper discusses the analysis of the composition and characteristics of medical waste at a disaster relief site using the retrospection-simulation-revision method. For this study, we obtained 35 medical relief records of the Wenchuan Earthquake, Sichuan, May 2008 from a field cabin hospital. We first present a retrospective analysis of the relief medical records, and then, we simulate the medical waste generated in the affected areas. We ultimately determine the composition and characteristics of medical waste in the affected areas using untreated medical waste to revise the composition of the simulated medical waste. The results from 35 cases showed that the medical waste generated from disaster relief consists of the following: plastic (43.2%), biomass (26.3%), synthetic fiber (15.3%), rubber (6.6%), liquid (6.6%), inorganic salts (0.3%) and metals (1.7%). The bulk density of medical relief waste is 249 kg/m3, and the moisture content is 44.75%. The data should be provided to assist the collection, segregation, storage, transportation, disposal and contamination control of medical waste in affected areas. In this paper, we wish to introduce this research method of restoring the medical waste generated in disaster relief to readers and researchers. In addition, we hope more disaster relief agencies will become aware of the significance of medical case recording and storing. This may be very important for the environmental evaluation of medical waste in disaster areas, as well as for medical waste management and disposal. [ABSTRACT FROM AUTHOR]

One of the main manifestations of climate change will be increased rainfall variability. How to deal with this in agriculture will be a major societal challenge. In this paper we explore flexibility in land use, through deliberate seasonal adjustments in cropped area, as a specific strategy for coping with rainfall variability. Such adjustments are not incorporated in hydro-meteorological crop models commonly used for food security analyses. Our paper contributes to the literature by making a comprehensive model assessment of inter-annual variability in crop production, including both variations in crop yield and cropped area. The Ganges basin is used as a case study. First, we assessed the contribution of cropped area variability to overall variability in rice and wheat production by applying hierarchical partitioning on time-series of agricultural statistics. We then introduced cropped area as an endogenous decision variable in a hydro-economic optimization model (WaterWise), coupled to a hydrology-vegetation model (LPJmL), and analyzed to what extent its performance in the estimation of inter-annual variability in crop production improved. From the statistics, we found that in the period 1999–2009 seasonal adjustment in cropped area can explain almost 50% of variability in wheat production and 40% of variability in rice production in the Indian part of the Ganges basin. Our improved model was well capable of mimicking existing variability at different spatial aggregation levels, especially for wheat. The value of flexibility, i.e. the foregone costs of choosing not to crop in years when water is scarce, was quantified at 4% of gross margin of wheat in the Indian part of the Ganges basin and as high as 34% of gross margin of wheat in the drought-prone state of Rajasthan. We argue that flexibility in land use is an important coping strategy to rainfall variability in water stressed regions. [ABSTRACT FROM AUTHOR]