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Sugar beet progeny lines screened for both high water use efficiency and high sugar yield under drought stress conditions in the field were assessed for the rate of seed germination and early seedling growth in water deficit stress, induced by mannitol solutions. Seeds of nine different sugar beet progeny lines were grown in three experimental conditions using filter paper, perlite and water agar as substrate. Three levels of 0.0, 0.2 and 0.3 m mannitol concentrations were applied in each experiment. A factorial design was used with three replications. Germination percentage was determined in all experiments. Seedling growth parameters such as cotyledon fresh weight, cotyledon dry weight, root fresh weight, root dry weight (RDW) and root length (RL) were measured experimentally. Abnormality was only recorded in the filter paper experiment. The results showed that drought stress could be simulated by mannitol solution and significant differences were found between stress levels for seedling characteristics. Distinct genetic variances were found among progeny lines with respect to germination and early seedling growth characteristics, except for cotyledons and RDW. Seedling growth and germination rates severely declined at the highest concentration of mannitol. The rate of abnormality was increased progressively at the germination stage with an increase in mannitol concentration but it was more pronounced in the drought-susceptible progeny lines. The highest values of relative germination % and relative growth % of RL were obtained for the most tolerant line. In conclusion, seedling characteristics, in addition to other physiological components involved in the seed germination process under specific stress conditions, may be considered for breeding purposes. [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]

This paper deals with a statistical method for selecting widely adapted genotypes in a target region. Yield was the trait for adaptation analysis although different crop productivity traits could be used for this analysis. Wide adaptation of a genotype was defined as a norm of a trait response in a target region across years. On this norm, a genotype's wide adaptation is the response of a productivity trait at a level not lower than the mean of all genotypes (environmental index) in every location within a target region in every year. The aim of this paper was to present a primary experimental evidence that supports the hypothesis that Kang's yield-stability statistic (YSi) could be a sufficient selection index for selecting widely adapted genotypes. In these studies, real experimental data, obtained from a single year multilocation balanced series of yield trials of spring wheat (Triticum aestivum) and oat (Avena sativa), are used. It has been proved that yield-stability statistic, YSi, could be a useful criterion in selecting spring cereal genotypes, evaluated in a series of variety trials repeated across locations and years, that would be most similar in yielding ability to the norm of wide adaptation. [ABSTRACT FROM PUBLISHER]

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]

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]

Cotton is the main source of renewable fiber in the world and is primarily used for textile production. This study analyzed 3,487 papers on cotton research published during 1990 to 2021 from the agronomy category of the Web of Science (WoS). Papers were mainly written in English (96.329%), from 8,860 authors, 87 countries/territories, 1,661 organizations, and published in 107 journals and book series. The top five core journals were Crop Science (433, 12.418%), Agronomy Journal (310, 8.89%), Weed Technology (205, 5.879%), Field Crops Research (203, 5.822%), and Euphytica (189, 5.42%) with each publishing more than 189 papers. The top five countries and regions were the U.S., Peoples Republic of China, India, Brazil, and Australia. The top five organizations were USDA ARS, Texas A&M Univ., North Carolina State Univ., Univ. Georgia, and Cotton Incorporated. The top five authors were Johnie N. Jenkins, Don C. Jones, Jack C. McCarty, Jr., Jinfa Zhang, and C. Wayne Smith, with each publishing 72 papers or more. Visualizations using VOSviewer were conducted on WoS data to determine co-occurrence and clusters of connected publications, country input, organizations, and author collaboration (coauthorship) as well as clusters of all keywords of interrelated research topics. Based on the analysis of the network map of VOSviewer, there is cooperation among authors, organizations, and countries or regions. All keywords of the cotton research papers published during 1990 to 2021 from WoS agronomy category separated into six clusters based on different research topics. [ABSTRACT FROM AUTHOR]

Copyright of Journal of African Studies is the property of Japan Association for African Studies and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

In this paper we report on an automated procedure to capture and characterize the detailed structure of a crop canopy by means of stereo imaging. We focus attention specifically on the detailed characteristic of canopy height distribution—canopy shoot area as a function of height—which can provide an elaborate picture of canopy growth and health under a given set of conditions. We apply the method to a wheat field trial involving ten Australian wheat varieties that were subjected to two different fertilizer treatments. A novel camera self-calibration approach is proposed which allows the determination of quantitative plant canopy height data (as well as other valuable phenotypic information) by stereo matching. Utilizing the canopy height distribution to provide a measure of canopy height, the results compare favourably with manual measurements of canopy height (resulting in an R2 value of 0.92), and are indeed shown to be more consistent. By comparing canopy height distributions of different varieties and different treatments, the methodology shows that different varieties subjected to the same treatment, and the same variety subjected to different treatments can respond in much more distinctive and quantifiable ways within their respective canopies than can be captured by a simple trait measure such as overall canopy height. [ABSTRACT FROM AUTHOR]

Northern Kazakhstan is the main grain-producing region in the Republic of Kazakhstan. This paper presents a brief characteristic of soil climatic conditions and the results of long-term studies (n=600) on the diagnostics and optimization of the conditions of crops' nitrogen nutrition under insufficient and unstable moistening, which is typical for dryland Northern Kazakhstan. The methodological approach to the evaluation of the soil nitrogen state and the supply of nitrogen to crops were explicated. A new method of determining the need for nitrogen fertilizers and calculating their dose calculation was offered. The method was based on identification of the main factors of soil fertility that determine the efficiency of crops and the effectiveness of nitrogen fertilizers. On the basis of the correlation analysis, the quantitative correlation between the factors and the efficiency of crops was determined. The optimal parameters of nitrogen content in the soil, which provide for the maximum efficiency of crops, and ways of achieving such parameters were presented. The developed method allowed purposefully managing the soil nitrogen regime, with a view to optimizing nutrition and realizing the full potential of crops. [ABSTRACT FROM AUTHOR]

The paper retraces the GRASPgfs endeavor (Geospatial Resource for Agricultural Species and Pests with integrated workflow modelling to support Global Food Security) between multiple disciplines around a common objective of facilitating research and model simulations for sustainable food security. Within this endeavor, the geospatial media has been the enabler for multidisciplinary research in crop modelling. Geospatial genetic-trait variations and associations with environmental forecasting were the main focus of the GRASPgfs. Designing the platform achieving this objective generated a transdisciplinary vision of modelling and forecasting for sustainable agriculture. Based on interoperability principles, seamless access as well as sharing for data, metadata and processing models, the design is described in this paper. This geospatial binding facilitates and supports new types of hypotheses and analysis as illustrated in the paper with a landscape genetic case study (bambara groundnut) and a crop disease modelling (eyespot disease). The approach and the eGRASP platform are generic enough to accommodate further complexity into the integrated modelling that this geospatial binding enables. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Central European Agriculture is the property of Journal of Central European Agriculture and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Senna alata, a flowering shrub, is widely cultivated in the Philippines for its anti-fungal properties. Despite this, its chloroplast genome is not yet established. We assembled and annotated the complete chloroplast genome of accession from the germplasm collection of the Institute of Crop Science, University of the Philippines, Los Baños, using Illumina sequencing data. The complete cp genome was 159,176-bp long characterized by a large single copy of 88,769 bp, short single-copy of 18,301 bp and a pair of inverted repeat regions of 26,053 bp each. The overall GC content of the chloroplast genome was 36.4%. The plastome comprised 37 tRNA genes, 8 rRNA genes and 78 mRNA genes. Phylogenetic analysis showed that S. alata is closely related to S. siamea. [ABSTRACT FROM AUTHOR]

Climate change is an apparent phenomenon affecting life in many aspects including crop production, so the assessment of its impact on crop production is urgently required to establish strategies and technologies to mitigate and adapt to climate change. Numerous efforts have been made to investigate the effects of climate change with emphases on elevated temperature and CO on crops, to assess climate change impact on crop production, and to develop application technologies for coping with climate change in a sustainable manner. This special issue of JCSB contains a collection of peer-reviewed research articles covering the impact of microclimate conditions on crop production (4 papers), modeling approaches for impact assessment (3 papers), and applications of crop science and biotechnology for climate change adaptation (3 papers). It is believed that this special issue will help crop scientists broaden their knowledge and understanding on climate change issues in crop production and facilitate research in crop science and biotechnology in battling against climate change to sustain current crop production and increase future crop production to feed ever continuously increasing human population. [ABSTRACT FROM AUTHOR]

Abstract Research in crop science in recent years has advanced at an unprecedented rate, and the intermingling of old and new crop breeding technologies has made the term "genetically modified" – and its variant, Genetically Modified Organism, or "GMO" – virtually obsolete. A kind of pseudo-category, it is primarily used pejoratively to refer to the use of the newest, most precise, most predictable, molecular genetic techniques. Prodigious amounts of time, effort and care have been expended to ensure that crops developed for commercialization using molecular techniques are safe, and that new traits are beneficial. Â Yet, despite these advances, some skepticism persists about them, partly due to the publication of fraudulent, poorly designed, and biased studies by a few "rogue scientists" whose intention is to contaminate the scientific literature and sow mistrust about molecular genetic modification among regulators and the public. We discuss how such flawed studies make it to publication and how the scientific community can combat such disinformation. [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]

Purpose - The purpose of this paper is to evaluate the soybean agricultural production system and the subsequent industrialization processes in order to assess the environmental sustainability of the soybean chain in Brazil and, also, to evaluate the amount emergy exchanged in the soybean trade. Design/methodology/approach - The emergy accounting methodology was used as analysis tool in this paper. Findings - The main findings were, first, the distribution of emergy flows inputs according to soybean chain stages, being 94 percent used by the agricultural production system, 1 percent used by transport to industry, 4 percent used by crushing, and 1 percent for oil refining. Second, emergy indicators showed negative sustainability trends trough the soybean chain stages. Third, the emergy exchange ratio demonstrated that the soybean farmers are delivering around five times more emergy with the soybean sold that the emergy they are receiving with the money paid for it and, thereby, depleting its local natural resources. Practical implications - The agricultural production stage uses the highest amount of resources. Therefore, any improvement in the management of this stage will result in improvement of the whole soybean chain. In this context, the adoption of more sustainable soybean agricultural production systems becomes fundamental for the long-term environmental sustainability of the soybean chain. Organic production models and agro-forestry technologies should be used toward more sustainable soybean chain because it can help to decrease the dependence of the soybean production systems on external non renewable resources. Originality/value - Emergy accounting methodology provides a very comprehensive tool to complement and complete energy, economic and social information about the soybean chain in Brazil. The emergy exchange ratio provides information to access and enrich the discussion about soybean fair trade. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) is increasingly used within plant science, yet it is far from being routinely and effectively implemented in this domain. Particularly relevant to the development of novel food and agricultural technologies is the development of validated, meaningful and usable ways to integrate, compare and visualise large, multi-dimensional datasets from different sources and scientific approaches. After a brief summary of the reasons for the interest in data science and AI within plant science, the paper identifies and discusses eight key challenges in data management that must be addressed to further unlock the potential of AI in crop and agronomic research, and particularly the application of Machine Learning (AI) which holds much promise for this domain.

This paper lends weight to the argument that user-centred design is important in design and development of software systems by describing the case of decision support systems for crop production. Decision support systems (DSS) are increasingly being seen as useful mechanisms for the transfer of scientific knowledge and 'best practice'; particularly in the field of agriculture. Although many systems have been developed, few can be termed 'successful' (i.e. have a significant uptake by intended users, and used by them). This paper provides evidence to support the importance of a user-centred approach by showing that each issue considered to be relevant to the failure of DSS in crop production can be addressed by the appropriate inclusion of users in the design and development process. Positive evidence in the shape of successful systems that have employed UCD is also presented. [ABSTRACT FROM AUTHOR]

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]

'Biasong' (Citrus micrantha), native to the Southern Philippine Islands, is an important cultivated fruit tree but has no published plastome sequence. We assembled and characterized the C. micrantha chloroplast genome from accession in the germplasm collection of the Institute of Crop Science, University of the Philippines Los Baños. The complete chloroplast (cp) genome sequence is 159,928-bp long with 128 coding genes comprising 83 mRNA genes, 37 tRNA genes, and eight rRNA genes. Out of the mRNA genes, 45 genes code for photosynthesis, 30 genes code for self-replication, and five genes code for other functions. A phylogenetic analysis of the assembled genome, along with 24 Citrus species and three other Rutaceae species, identified Citrus aurantiifolia as its closest relative with available complete cpDNA sequence. [ABSTRACT FROM AUTHOR]

The prediction of phenotypic traits using high-density genomic data has many applications such as the selection of plants and animals of commercial interest; and it is expected to play an increasing role in medical diagnostics. Statistical models used for this task are usually tested using cross-validation, which implicitly assumes that new individuals (whose phenotypes we would like to predict) originate from the same population the genomic prediction model is trained on. In this paper we propose an approach based on clustering and resampling to investigate the effect of increasing genetic distance between training and target populations when predicting quantitative traits. This is important for plant and animal genetics, where genomic selection programs rely on the precision of predictions in future rounds of breeding. Therefore, estimating how quickly predictive accuracy decays is important in deciding which training population to use and how often the model has to be recalibrated. We find that the correlation between true and predicted values decays approximately linearly with respect to either FST or mean kinship between the training and the target populations. We illustrate this relationship using simulations and a collection of data sets from mice, wheat and human genetics. [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]

Introduction: Agricultural technologies developed by national and international research institutions were not benefiting the rural population of Ethiopia to the extent desired. As a response, integrated agricultural extension approaches are proposed as a key strategy to transform the smallholder farming sector. Improving Productivity and Market Success (IPMS) of Ethiopian Farmers project is one of the development projects initiated by integrating productivity enhancement technological schemes with market development model. This paper explores the impact of the project intervention in the smallholder farmers’ wellbeing. Methods: To test the research hypothesis of whether the project brought a significant change in the input use, marketed surplus, efficiency and income of farm households, we use a cross-section data from 200 smallholder farmers in Northwest Ethiopia, collected through multi-stage sampling procedure. To control for self-selection from observable characteristics of the farm households, we employ Propensity Score Matching (PSM). We finally use Data Envelopment Analysis (DEA) techniques to estimate technical efficiency of farm households. Results: The outcome of the research is in line with the premises that the participation of the household in the IPMS project improves purchased input use, marketed surplus, efficiency of farms and the overall gain from farming. The participant households on average employ more purchased agricultural inputs and gain higher gross margin from the production activities as compared to the non-participant households. The non-participant households on average supply less output (measured both in monetary terms and proportion of total produce) to the market as compared to their participant counterparts. Except for the technical efficiency of production in potato, project participant households are better-off in production efficiency compared with the non-participant counterparts. Conclusion: We verified the idea that Improving Productivity and Market Success (IPMS) of Ethiopian farmers’ project has contributed for the input and out market integration and/or market oriented agricultural production. Overall, we argue that these can be seen as an experimental model with a promising potential to improve the livelihood of the poor. Furthermore, we suggest that it is worthwhile to employ integrated agricultural extension programs with further targeting in the developing world. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses articles within the issue on topics including the history of crop science, food security, agricultural economy and development, and the global food system.

Societal Impact Statement: Studies that show how empire influenced the development of plant genetics add to the established history of genetics and 20th‐century agricultural science. One approach to broadening this history is to consider the contributions of students studying abroad and their greater careers back home. Research agendas differed between and within institutions, much as they do today. This article explores the postgraduate education of an Indian groundnut breeder. It highlights the structural challenges faced by researchers at agricultural departments who sought promotion through education and examines the consequences for plant breeding and for farmers. Summary: Through the biography of V.K. Badami, this article contributes to debates about genetics and plant breeding in the history of science. Badami, an accomplished breeder in the Mysore Department of Agriculture, took a leave to study genetics at the University of Cambridge. His professors nearly failed him, yet Badami's groundnut breeding experiments proved influential for Indian farmers as well as advances in crop science. This history adds to the thesis that academic genetics varied in support of professional plant breeding by comparing institutional expections between Mysore and Cambridge.The argument is developed by reading Badami's student records along with his groundnut breeding experiments in South India.The study connects the disciplinary history of genetics to plant breeding for the British empire.Badami's experience at Cambridge is indicative of the power relationship between academic genetics and imperial plant breeding in the early 20th century. In this case, his commitments as an Indian agricultural officer conflicted with the discipline's devotion to quantitative analysis. [ABSTRACT FROM AUTHOR]

The field of agronomy and crop science plays a crucial role in ensuring global food security and sustainable agricultural practices. In the realm of scholarly publications, bibliometric indicators have emerged as invaluable tools for quantifying and comparing the impact, reach, and significance of such contributions. Various bibliometric indicators were employed for the study, including Impact Factor, Eigenfactor Score, Cite Score, and h-index. To accomplish this, we compiled a roster of 90 agronomy and crop science journals using the Journal Citation Report (JCR) within the Web of Science (WOS), journal metrics from the Scopus database (Cite Score and SNIP), and h5-index from Google Scholar. The SCImago Journal Ranking (SJR) was obtained from its official website. Subsequently, we conducted Bivariate Pearson's (r) and Spearman's (ρ) correlation coefficient tests to assess ranking correlations. The study revealed notable positive correlations particularly, a strong Pearson's (r) correlation evident between the Impact Factor (JIF) and both the Cite Score (CS) and SCImago Journal Rank (SJR) indicators, yielding values of (r = 0.962) and (r = 0.932), respectively. Interestingly, despite the distinct mathematical foundations underpinning the various citation-based bibliometric indices scrutinized, our findings underscored their robust correlations when it comes to ranking agronomy and crop science journals. [ABSTRACT FROM AUTHOR]

Societal Impact Statement Maize is the world's second most important agricultural crop. The cereal was unknown to Europeans before the end of the 15th century, but since its arrival in Europe, it has changed agriculture, food and landscapes. Terraces where maize was cultivated in the Northwest of the Iberian Peninsula contributed to the formation of local cultures and identities. The history of maize and maize landscape are mementos that help to recover traditional practices, fostering identities, and are crucial for the successful implementation of sustainable policies to provide prosperous futures. Summary Maize (Zea mays L.) in the Iberian Peninsula embodies a history of landscape changes where the concepts of ‘exotic’, ‘traditional’ and ‘hybrid’ help to understand the engagements between landscape, farmers, agronomists (since the 19th and 20th centuries) and seeds. Today, landscapes reveal biophysical and ecological changes that reflect a panoply of intentions. A multitude of agents, and their interactions, acted upon those territories over time. Using historical sources from the leading institutions dedicated to agricultural research in the Iberian Peninsula, this paper aims to (1) contribute to a better understanding of the maize landscape and culture in the Iberian Peninsula and (2) interrogate how landscape changes (and the landscape history of maize) can frame local or regional heritage and identities reflecting customs or ways of life. The analysis unveils networks of knowledge, agricultural technologies and seed exchange. Politicians, economists, engineers, agronomists, farmers, governmental officials and agricultural industries planned and transformed traditional rural practices into modern and industrialised ones. Experts and politicians, willing to improve agricultural practices and seeds, using hybrid seeds or building new irrigation systems, led to deep social and landscape changes, allowing maize to cover territories far away from its traditional domains. Moreover, despite farmers' resistance, hybrid maize substituted landraces, eroding agrobiodiversity. Nowadays, the south and east regions of the Iberian Peninsula are the main producers of maize (hybrid), whereas in the Northwest maize is an occasional crop, being replaced by vineyards for economic reasons.

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]

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]

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]