Search

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.

Among the challenges of sustainable management of meat production, the key issue is to improve the energy efficiency of production processes, which will consequently affect the reduction of greenhouse gas emissions. Such effects are achieved by combining various chilling systems with electrical stimulation that determines the quality of meat at the slaughter stage. The novelties of the research undertaken included determining the impact of various variants of meat production (chilling method: slow, fast, accelerated + HVES/NES) on changes in the basic (industrial) quality indicators (pH and temperature) of beef produced from Polish Holstein-Friesian breed cattle, and then indicating the optimal variant for energy-efficient (sustainable) beef production. The HVES and the fast chilling method yielded positive economic (meat weight loss), technological (high quality, hot-boning), energetic (lower electricity consumption), and organizational effects (reduced chilling and storage surfaces and expenditures for staff wages) compared to the slow and accelerated methods. Reaching the desired final temperature with an increased amount of chilled meat enables obtaining a few-fold decrease in the specific energy consumption and a higher energy efficiency of the process. This allows recommending the above actions to be undertaken by entrepreneurs in the pursuit of sustainable meat production.

The self-cleaning screen filter is one of the most common types used in drip irrigation systems. Backwashing pressure difference and backwashing time for two screen filters with one geometry and two different screens (178 μm and 124 μm) using two water qualities (tap water and sand-water mixture) were studied in a total of 88 runs (42 runs for tap water, 22 and 24 filtration cycles for sand-water mixture and backwashing, respectively). The backwashing pressure difference and backwashing time were calculated using the experimental data, and the results were largely in the range of measured values. Three constraint conditions (flowrate, sand condition and filtration time) of backwashing pressure difference were analysed, and the optimal values of backwashing pressure difference were given as 60.0 and 70.0 kPa for 178 μm and 124 μm filters, respectively. The backwashing time of the screen filter should be an optimal value that ensures that the pressure difference between the internal and external surfaces of the screen decreased to the initial value, and the sand concentration of the backwashed outlet decreased to a small, stable value. Based on the results of the backwashing experiment and prototype observation, the optimal backwashing time was given as 30 to 45 s for both screen filters.

This study investigated 24 tablet crushing devices for drug loss using different methods to recover the crushed tablet. 24 devices were compared: 3 with disposable cups, 6 with disposable bags, 12 without separate vessels and 3 types of mortar and pestle. One paracetamol tablet was crushed and recovered by tapping the powder out. Where appropriate, depending on crusher size and manufacturer instructions, the powder was also recovered by mixing with water or food. Paracetamol recovery (quantity that can be delivered to a patient) and leftover (quantity remaining in the device) were measured using a validated UV method and the entire experiment was replicated 3 times. Drug recovery ranged from 86.7-98.1% when the crushed tablet was tapped out of the crushers (average loss 5.8%). Significant losses were measured for 18 crushers, particularly manually operated hand-twist crushers with a serrated crushing surface, and some devices with disposable bags or cups. Rinsing the crushed powder with water once resulted in an average of 24.2% drug loss, and this was reduced to 4.2% after a second rinse. If crushing is unavoidable, maximizing medication delivery to the patient is essential. Rinsing twice resulted in similar paracetamol recovery to tapping the powder out; however only water rinses have the potential for direct consumption by the patient, minimizing drug loss across the entire crushing and transfer process.

Eucalypt species are a group of flowering trees widely used in pulp production for paper manufacture. For several decades, the wood pulp industry has focused research and development efforts on improving yields, growth rates and pulp quality through breeding and the genetic improvement of key tree species. Recently, this focus has shifted from the production of high quality pulps to the investigation of the use of eucalypts as feedstocks for biofuel production. Here the structure and chemical composition of the heartwood and sapwood of Eucalyptus dunnii, E. globulus, E. pillularis, E. urophylla, an E. urophylla-E. grandis cross, Corymbia citriodora ssp. variegata, and Acacia mangium were compared using nuclear magnetic resonance spectroscopy (NMR), X-ray diffraction (XRD) and biochemical composition analysis. Some trends relating to these compositions were also identified by Fourier transform near infrared (FT-NIR) spectroscopy. These results will serve as a foundation for a more comprehensive database of wood properties that will help develop criteria for the selection of tree species for use as biorefinery feedstocks. © 2012 Çetinkol et al.

The green mirid bug Apolygus lucorum is a regional pest of multiple crops in northern China, and the survival and development of diapausing eggs during winter plays an important role in the population dynamics of this species. The effect of water on the survival and development of A. lucorum eggs was investigated using laboratory-induced diapause. Diapausing eggs were exposed to various humidity regimes under three conditions: (1) termination of diapause with exposure to warm long-day (WLD) conditions (i.e., 26 ± 1°C and 75 ± 5% relative humidity (RH) under a photoperiod of 16 hours light and 8 hours dark), (2) termination of diapause by chilling at 4°C, or (3) during the post-diapause stage, i.e., from transfer to WLD conditions after chilling, until the hatching of nymphs. The results indicate that water availability is crucial for the post-diapause resumption of development of A. lucorum. However, exposure to excessive moisture was detrimental, as indicated by a decrease in diapause termination rate and a prolonged pre-hatching period of diapausing eggs, compared to limited moisture conditions. This implies that both too dry and too humid environmental conditions would suppress survival and postpone hatching of overwintered A. lucorum eggs, and might explain why this pest has not caused severe damage in either southern or western China where the respective climates are very humid or dry.

The challenges which the large scale microalgal industry is facing are associated with the high cost of key operations such as harvesting, nutrient supply and oil extraction. The high-energy input for harvesting makes current commercial microalgal biodiesel production economically unfeasible and can account for up to 50% of the total cost of biofuel production. Co-cultivation of fungal and microalgal cells is getting increasing attention because of high efficiency of bio-flocculation of microalgal cells with no requirement for added chemicals and low energy inputs. Moreover, some fungal and microalgal strains are well known for their exceptional ability to purify wastewater, generating biomass that represents a renewable and sustainable feedstock for biofuel production. We have screened the flocculation efficiency of the filamentous fungus A. fumigatus against 11 microalgae representing freshwater, marine, small (5 µm), large (over 300 µm), heterotrophic, photoautotrophic, motile and non-motile strains. Some of the strains are commercially used for biofuel production. Lipid production and composition were analysed in fungal-algal pellets grown on media containing alternative carbon, nitrogen and phosphorus sources contained in wheat straw and swine wastewater, respectively. Co-cultivation of algae and A. fumigatus cells showed additive and synergistic effects on biomass production, lipid yield and wastewater bioremediation efficiency. Analysis of fungal-algal pellet's fatty acids composition suggested that it can be tailored and optimised through co-cultivating different algae and fungi without the need for genetic modification.

Gradual depletion of the world petroleum reserves and the impact of environmental pollution highlight the importance of developing alternative energy resources such as plant biomass. To address these issues, intensive research has focused on the plant Jatropha curcas, which serves as a rich source of biodiesel because of its high seed oil content. However, producing biodiesel from Jatropha generates large amounts of biomass waste that are difficult to use. Therefore, the objective of our research was to analyze the effects of different conditions of torrefaction on Jatropha biomass. Six different types of Jatropha tissues (seed coat, kernel, stem, xylem, bark, and leaf) were torrefied at four different temperature conditions (200°C, 250°C, 300°C, and 350°C), and changes in the metabolite composition of the torrefied products were determined by Fourier transform-infrared spectroscopy and nuclear magnetic resonance analyses. Cellulose was gradually converted to oligosaccharides in the temperature range of 200°C-300°C and completely degraded at 350°C. Hemicellulose residues showed different degradation patterns depending on the tissue, whereas glucuronoxylan efficiently decomposed between 300°C and 350°C. Heat-induced depolymerization of starch to maltodextrin started between 200°C and 250°C, and oligomer sugar structure degradation occurred at higher temperatures. Lignin degraded at each temperature, e.g., syringyl (S) degraded at lower temperatures than guaiacyl (G). Finally, the toxic compound phorbol ester degraded gradually starting at 235°C and efficiently just below 300°C. These results suggest that torrefaction is a feasible treatment for further processing of residual biomass to biorefinery stock or fertilizer.

The composting industry has been growing rapidly in China because of a boom in the animal industry. Therefore, a rapid and accurate assessment of the quality of commercial organic fertilizers is of the utmost importance. In this study, a novel technique that combines near infrared (NIR) spectroscopy with partial least squares (PLS) analysis is developed for rapidly and accurately assessing commercial organic fertilizers quality. A total of 104 commercial organic fertilizers were collected from full-scale compost factories in Jiangsu Province, east China. In general, the NIR-PLS technique showed accurate predictions of the total organic matter, water soluble organic nitrogen, pH, and germination index; less accurate results of the moisture, total nitrogen, and electrical conductivity; and the least accurate results for water soluble organic carbon. Our results suggested the combined NIR-PLS technique could be applied as a valuable tool to rapidly and accurately assess the quality of commercial organic fertilizers.

Betula platyphylla Suk (birch) is a fast-growing woody species that is important in pulp industries and the biofuels. However, as an important pulp species, few studies had been performed on its wood formation. In the present study, we investigated the molecular responses of birch xylem to artificial bending and gravitational stimuli. After trunks of birch trees were subjected to bending for 8 weeks, the cellulose content was significantly greater in tension wood (TW) than in opposite wood (OW) or normal wood (NW), whereas the lignin content in TW was significantly lower than that in OW and NW. In addition, TW grew more rapidly than OW and generated TW-specific fibers with an additional G-layer. Three transcriptome libraries were constructed from TW, OW and NW of B. platyphylla, respectively, after the plants were subjected to artificial bending. Overall, 80,909 nonredundant unigenes with a mean size of 768 nt were assembled. Expression profiles were generated, and 9,684 genes were found to be significantly differentially expressed among the TW, OW and NW libraries. These included genes involved in secondary cell wall structure, wood composition, and cellulose or lignin biosynthesis. Our study showed that during TW formation, genes involved in cellulose synthesis were induced, while the expression of lignin synthesis-related genes decreased, resulting in increased cellulose content and decreased lignin levels in TW. In addition, fasciclin-like arabinogalactan proteins play important role in TW formation. These findings may provide important insights into wood formation at the molecular level.

In order to study the impact of inclusive finance on agricultural green development, This paper uses both static panel and dynamic panel (system GMM model) estimation methods to make empirical analysis of the impact of inclusive financial development on agricultural green development. The results both find that there is a significant positive correlation between the level of inclusive financial development, real GDP per capita, the proportion of the added value of agriculture, forestry, animal husbandry and fishery in GDP and agricultural green development. This paper puts forward some countermeasures and suggestions to promote agricultural green development, including vigorously developing inclusive finance, promoting economic growth, promoting the development of agriculture, forestry, animal husbandry and fishery, and increasing environmental protection expenditures.

The deep neural network is used to establish a neural network model to solve the problems of low accuracy and poor accuracy of traditional algorithms in screening differentially expressed genes and function prediction during the walnut endocarp hardening stage. The paper walnut is used as the research object to analyze the biological information of paper walnut. The changes of lignin deposition during endocarp hardening from 50 days to 90 days are observed by microscope. Then, the Convolutional Neural Network (CNN) and Long and Short-term Memory (LSTM) network model are adopted to construct an expression gene screening and function prediction model. Then, the transcriptome and proteome sequencing and biological information of walnut endocarp samples at 50, 57, 78, and 90 days after flowering are analyzed and taken as the training data set of the CNN + LSTM model. The experimental results demonstrate that the endocarp of paper walnut began to harden at 57 days, and the endocarp tissue on the hardened inner side also began to stain. This indicates that the endocarp hardened laterally from outside to inside. The screening and prediction results show that the CNN + LSTM model’s highest accuracy can reach 0.9264. The Accuracy, Precision, Recall, and F1-score of the CNN + LSTM model are better than the traditional machine learning algorithm. Moreover, the Receiver Operating Curve (ROC) area enclosed by the CNN + LSTM model and coordinate axis is the largest, and the Area Under Curve (AUC) value is 0.9796. The comparison of ROC and AUC proves that the CNN + LSTM model is better than the traditional algorithm for screening differentially expressed genes and function prediction in the walnut endocarp hardening stage. Using deep learning to predict expressed genes’ function accurately can reduce the breeding cost and significantly improve the yield and quality of crops. This research provides scientific guidance for the scientific breeding of paper walnut.

Taking 30 provinces in China from 2011 to 2020 as a research sample, this paper empirically tests the impact of digital village construction on carbon emissions. This study found that there is an "inverted U" curve relationship between digital rural construction and rural carbon emissions. Agricultural planting structure and agricultural technical efficiency are important ways for digital village construction to produce carbon emission reduction effects. This study also found that the higher the level of economic development, the stronger the carbon emission reduction effect of digital village construction. In addition, there are also significant differences in the carbon emission reduction effect of digital village construction in regions with different environmental regulation intensities. Finally, in terms of the relationship between digital economic activities and carbon emission reduction, the research conclusions of this paper have important implications.

This paper aims to test whether agricultural insurance significantly impacts farmers’ income increase or not. We have used the ordinary least squares method (OLS), panel fixed effects, and system generalized moment estimation (GMM) for the test. The results show that the increase in agricultural insurance density and the increase in agricultural insurance per capita compensation positively impact farmers’ income growth significantly. Agricultural insurance density and per capita compensation are the indicators used in this article to measure agricultural insurance development. Therefore, it can be considered that the development of agricultural insurance in Guangdong Province (China) can effectively increase the income level of farmers. Based on the results of theoretical and empirical analysis, combined with the current situation of agricultural insurance development in Guangdong Province, this paper finally puts forward relevant countermeasures and suggestions. It provides some ideas for giving full play to the role of agricultural insurance in promoting farmers’ income from the perspectives of pertinent system design, subsidy methods, insurance innovation, service level, and publicity.

This study was carried out to investigate the risks of simultaneous exposure to pesticide residues and bacteria contaminants in locally produced fresh vegetables and vegetables in Tanzania. A total of 613 samples were analyzed for pesticide residues, out of which 250 were also analyzed for bacterial contamination. Overall, 47.5% had pesticide residues, 74.2% exceeded Maximum Residue Levels (MRLs). Organophosphorus (95.2%), organochlorines (24.0%), pyrethroids (17.3%), and carbamates (9.2%) residues dominated. MRL values were mostly exceeded in tomatoes, onions, watermelons, cucumbers, Chinese cabbage, and sweet paper. Tetramethrin (0.0329-1.3733 mg/kg), pirimiphos-methyl (0.0003-1.4093 mg/kg), permethrin (0.0009-2.4537 mg/kg), endosulfan (beta) (0.0008-2.3416 mg/kg), carbaryl (0.0215-1.5068 mg/kg), profenofos (0.0176-2.1377 mg/kg), chlorpyrifos (0.0004-1.2549 mg/kg) and dieldrin (0.0011-0.5271 mg/kg) exceeded MRLs. The prevalence of bacteria contamination was high (63.2%). Enterobacter (55.6%) Pseudomonas aeruginosa (32.4%), E. coli (28.2%), Citrobacter (26.8%), Klebsiella oxytoca (14.8%), and Salmonella (7.7%) were isolated. Furthermore, 46.4% tested positive for both pesticide residues and bacterial contaminants. Vegetables from farms (60.7%) contained more dual contaminants than market-based vegetables (41.8%). This may have resulted from excessive pesticide use and unhygienic handling of fresh fruits and vegetables at production level. Binary logistic regression showed that fresh fruits and vegetables with pesticide residues were 2.231 times more likely to have bacteria contaminants (OR: 2.231; 95% CI: 0.501, 8.802). The contamination levels of pesticide residues and bacterial contaminants could be perceived as a serious problem as most fresh fruits and vegetables recorded values of pesticide residues far above the MRLs with pathogenic bacteria isolated in higher proportions. MRLs was higher in most vegetables consumed raw or semi-cooked such as watermelons, carrots, cucumber, tomatoes, onion and sweet paper. There is an urgent need to develop pesticide monitoring and surveillance systems at farmer level, educating farmers and promoting the use of greener pesticides to mitigate the health effects of pesticides and bacterial contaminants.

Seemingly empty spaces in various archaeological settings have left many unanswered questions. This paper focuses on the appearance, maintenance and possible function of a large empty area situated at the summit plateau of the Iron Age oppidum Bibracte in France. Multidisciplinary research of the infill of the ditch that delimited this area in the 1st century BC has provided evidence on the primary function and the formation processes of the structure itself, and for the reconstruction of the appearance, maintenance and function of the area it enclosed. The results allow us to gain insight into a variety of topics, including the role of trees, hygiene measures and waste management strategies at this urbanised hilltop centre. This paper demonstrates that multi-proxy analyses provide detailed insight into the function of archaeological features in a local environmental context and the potential of such approaches in archaeology. U domněle prázdných(nezastavěných) míst v archeologickém kontextu je řada nezodpovězených otázek. Článek se zaměřuje na vzhled, způsob udržování a možnou funkci velkého prázdného prostoru v době železné v rámci vrcholového plateau oppida Bibracte ve Francii. Multidisciplinární přístup k výzkumu výplně příkopu, který tento prostor vymezoval v 1. století př. Kr., poskytl doklady o primárním využití a vzniku výplně v příkopu a dále k rekonstrukci vzhledu, managementu a funkce území, které jej obklopovalo. Výsledky nám umožňují vhled do řady témat, včetně role stromů, úrovně hygieny a nakládání s odpadem v urbanizovaném prostředí oppida. Článek prokazuje důležitost multi-proxy přístupu pro řešení funkce archeologických objektů v lokálním environmentálním kontextu a potenciál tohoto přístupu v archeologii.

Selecting a target journal is a universal decision faced by authors of scientific papers. Components of the decision, including expected turnaround time, journal acceptance rate, and journal impact factor, vary in terms of accessibility. In this study, I collated recent turnaround times and impact factors for 82 journals that publish papers in the field of fisheries sciences. In addition, I gathered acceptance rates for the same journals when possible. Findings indicated clear among-journal differences in turnaround time, with median times-to-publication ranging from 79 to 323 days. There was no clear correlation between turnaround time and acceptance rate nor between turnaround time and impact factor; however, acceptance rate and impact factor were negatively correlated. I found no field-wide differences in turnaround time since the beginning of the COVID-19 pandemic, though some individual journals took significantly longer or significantly shorter to publish during the pandemic. Depending on their priorities, authors choosing a target journal should use the results of this study as guidance toward a more informed decision.

Eggs contain the essential cholesterol and protein for the human body, which plays an irreplaceable role in human survival, production and life. There are significant differences in the development of laying hens feeding in different regions. It is of great significance to improve egg production and reduce pollution emission for China’s laying hens industry. Based on the SBM model, this paper constructs MML index, considering unexpected output under common frontier, to comprehensively evaluate the green total factor productivity on Chinese laying hens (GTCL). The results show that: (1) GTCL shows a large spatial and temporal differentiation under both the common frontier and the regional frontier. Compared with the eastern region and central region, the western region has obvious advantages in GTCL. (2) GTCL overall shows a downward trend, however, it emerges an upward trend in recent years. (3) Compared with small-scale and large-scale, middle-scale GTCL has advantages. According to the above empirical results, combined with the China’s actual national situation, this paper finally puts forward some policy recommendations to improve GTCL.

In this paper, we describe a novel approach to the development of a reference standard for the quality control of complex natural products, which will assist in the assessment of their authenticity and purity. The proposed method provides a template for the selection of samples, which can be pooled to obtain a reference standard. A shortfall of such an approach is, however, that the pooled sample is static in nature and therefore unable to capture difference in processing conditions or natural variations triggered by geographical or climatic impacts over time. To address this, the paper also outlines the development of a dynamic reference standard, which allows for ongoing adjustments to future variations. The method employs High-Performance Thin Layer Chromatography (HPTLC) derived extract profiles processed by multivariate analysis. The development of the dynamic reference standard is illustrated using honey, a complex natural matrix, as an example.

Supply chain integration plays an important role in the development of the vegetable industry in terms of vegetable quality, vegetable safety, and vegetable security in rural China. This paper explores how agricultural cooperatives integrate the vegetable supply chain by taking a trinity cooperative as an example in China. It explains the translation concatenation of supply chain integration for this cooperative by constructing actor networks in four development stages, including the seed stage, start-up stage, development stage, and mature stage. The findings show that supply chain integration in production cooperation, supply & sales cooperation, and credit cooperation is a useful trinity cooperative model of supply chain integration for investigating vegetable supply chain integration through internal integration and external integration. This paper suggests that cooperatives in the vegetable supply chain should facilitate close coordination among different shareholders and further improve the efficiency of supply chain integration. The government should provide training opportunities and funding to encourage cooperatives to participate in supply chain integration within the vegetable industry.

Scaling is a ubiquitous concept in agricultural research in the global south as donors require their research grantees to prove that their results can be scaled to impact upon the livelihoods of a large number of beneficiaries. Recent studies on scaling have brought critical perspectives to the rather technocratic tendencies in the agricultural innovations scaling literature. Drawing on theoretical debates on spatial strategies and practical experience of agricultural innovation scaling in Ethiopia, this paper adds to the current debate on what constitutes scaling and how to overcome critical scaling constraints. The data for the paper came from a qualitative assessment using focus group discussions, key informant interviews, and document analysis on scaling work done in Ethiopia by a USAID-funded research for development project. The paper concludes with four broad lessons for the current understating of agricultural innovation scaling. First, scaling of agricultural innovations requires a balanced focus on technical requirements and associated social dynamics surrounding scaling targets, actors involved and their social relations. Second, appreciating the social dynamics of scaling emphasizes the fact that scaling is more complex than a linear rolling out of innovations towards diffusion. Third, scaling may not be strictly planned; instead, it might be an extension of the innovation generation process that relies heavily on both new and long-term relationships with key partners, trust, and continuous reflection and learning. Fourth, the overall implication of the above three conclusions is that scaling strategies need to be flexible, stepwise, and reflective. Despite the promises of flourishing scaling frameworks, scaling strategies it would appear from the Africa RISING experience that, if real impact is to be achieved, approaches will be required to be flexible enough to manage the social, processual and emergent nature of the practice of scaling.

Tropical tuna support some of the largest and most valuable artisanal and industrial fisheries worldwide, conducted to a large degree with Fish Aggregating Devices (FADs). Yellowfin, bigeye and skipjack are the main tuna species found in mixed aggregations around FADs and they are simultaneously encircled by the purse seining operation. One of the key challenges that purse seine fleets fishing with drifting FADs face in all oceans is to be able to target species in healthy condition such as skipjack, while reducing impacts on bigeye and yellowfin in areas where there is a need to reduce fishing pressure on these species. The present paper explores a technical solution for selective fishing at FADs by means of acoustic equipment used by purse seiners. Acoustic frequency response of skipjack and bigeye tuna were determined at 38, 120 and 200 kHz. Skipjack showed stronger response at higher frequencies. On the contrary, bigeye showed stronger responses at lower frequencies. The robust pattern shown in frequency responses of the two species demonstrates the potential to predict abundance and species proportions based on purely acoustic measures. The paper also addresses the conditions that need to be met to successfully apply this technology for selective fishing as well as other uses of direct acoustic observations to support tuna conservation.

Population is a major production factor in rural development in China, which makes the study of rural population distribution patterns at different times and the factors influencing the population distribution an important foundation for understanding the issues in rural China and moving forward with the implementation of rural revitalization strategies. This paper analyzed the spatial evolution of the population in rural China based on population census data for the People’s Republic of China by county in 1990, 2000 and 2010. Applying the geographical detector method, this paper also delved into the contributing factors that influenced the distribution based on the natural, social and economic data, such as the potential crop productivity, the average slope, the urbanization rate and the time cost to reach the nearest cities. The results indicate that the migration of the population from the rural areas into the cities, which was a result of rapid urbanization, did not change the original population distribution in rural China significantly. The rural population was still concentrated in the eastern plains, basins and deltas, and the North China Plain and Sichuan Basin still house the bulk of rural residents, but the population density of rural residents in the North China Plain and Sichuan Basin decreased from 1990 to 2010. The rural population in China tended to be distributed around the cities. Seventy-four percent of the rural population lived in an area within a 60-minute driving distance from the surrounding cities. The areas with dense rural population were basically consistent with the locations of the current major urban agglomerations in China. The current distribution of the rural population in China was a result of natural, social and economic conditions and location factors. Among them, natural factors such as the potential crop productivity and the degree of surface fragmentation had the most significant influence.

Recreational fishing is often perceived as harmless when it comes to fisheries management, and its impact often estimated to surpass the economic outcomes of e.g. large-scale fisheries. Recreational fisheries are often an indication of political stability and sound ecosystem management. However, despite a high economic impact, the economic costs on traditional and small-scale commercial fishers is yet to be known. This paper answers the question of how unregulated recreational fisheries could rather generate a loss to an economy, and cause unfair competition with existing commercial sectors using the example of Algeria. This paper assesses catches and economic value of recreational fisheries in Algeria, and finds that over 6,000 tonnes reach commercial markets annually, competing directly with the small-scale artisanal sector, while selling recreationally caught fish is still illegal. The paper further finds that the public is thereby deprived-through lost tax, licence income and landed value of $45 million US annually.

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.

The challenge of detecting research topics in a specific research field has attracted attention from researchers in the bibliometrics community. In this study, to solve two problems of clustering papers, i.e., the influence of different distributions of citation links and involved textual features on similarity computation, the authors propose a hybrid self-optimized clustering model to detect research topics by extending the hybrid clustering model to identify "core documents". First, the Amsler network, consisting of bibliographic coupling and co-citation links, is created to calculate the citation-based similarity based on the cosine angle of papers. Second, the cosine similarity is also used to compute the text-based similarity, which consists of the textual statistical and topological features. Then, the cosine angle of the linear combination of citation- and text-based similarity is considered as the hybrid similarity. Finally, the Louvain method is applied to cluster papers, and the terms based on term frequency are used to label clusters. To test the performance of the proposed model, a dataset related to the data envelopment analysis field is used for comparison and analysis of clustering results. Based on the benchmark built, different clustering methods with different citation links or textual features are compared according to evaluation measures. The results show that the proposed model can obtain reasonable and effective clustering results, and the research topics of data envelopment analysis field are also analyzed based on the proposed model. As different features are considered in the proposed model compared with previous hybrid clustering models, the proposed clustering model can provide inspiration for further studies on topic identification by other researchers.

This paper investigates the consequences of ignoring the clustered data structure on allometric models. Clustered data, in the form of multiple trees sampled from multiple forest stands is commonly used to develop biomass allometric models. Of 102 reviewed papers published between 2012 and 2016 that reported biomass allometric models, 84 (82%) have used a clustered sampling design. However, in as many as 80% of these, the clustered data structure was ignored, potentially violating the independence assumption in ordinary least squares methods. The consequences of ignoring clustered data structure were empirically validated using two clustered biomass datasets (of 110 and 220 trees, with the cluster size of 5 and 10 trees respectively). We showed that when Intraclass Correlation Coefficient (ICC) was higher than zero, ignoring the clustered data structure returned underestimated standard errors, affecting further the confidence interval and t-test results. The underestimation level depended on ICC (which shows the variance proportion that was caused by the forest stand) and on cluster size (the number of trees sampled from one forest stand). We also showed that using first-order autocorrelation tests, such as the traditional Durbin-Watson statistic, to detect the autocorrelation due to clustered structure could be misleading as the test may show lack of autocorrelation even though ICC is different from zero. In conclusion, when ICC is higher than zero, ignoring the clustered data structure yields over-confident biomass predictions (due to underestimated confidence interval) and/or incorrect research conclusions (due to overestimated evidence against null hypothesis in t-test). Therefore, using a modelling approach that accounts for the hierarchical structure of the data is highly recommended when any form of clustering can be identified, even if the autocorrelation is not significant.

The use of elasticities of substitution between inputs is a standard method for addressing the effect of a change in the mix of inputs used for production from a technical or cost standpoint. Most estimation methods use parametric production or cost functions or frontiers to estimate these elasticities. A potentially useful nonparametric alternative is data envelopment analysis (DEA). The purpose of this paper is to derive elasticities of input substitution for both technical and cost frontiers using DEA, extending the use of this approach in the field of economics and associated fields. The paper provides derivations for both Hicksian (production and cost frontier) and Morishima (cost frontier) elasticities of input substitution, as well as a parsimonious method for estimating them using DEA. The derivations are presented using an agricultural example form Kansas, USA.

Food safety is a global public health issue, which often arises from asymmetric information between consumers and suppliers. With the development of information technology in human life, building a food traceability information sharing platform is viewed as one of the best ways to overcome the trust crisis and resolve the problem of information asymmetry in China. However, among the myriad information available from the food supply chain, there is a lack of knowledge on consumer preference. Based on the best-worst scaling approach, this paper investigated consumer preferences for vegetable, pork, and dairy product traceability information. Specifically, this paper measured the relative importance that consumers place on the traceable information. The results indicate that consumers have varying priorities for information in different cases. "Pesticide/veterinary use," "picking/slaughtering date," and "fertilizer/feed use" are the most preferred traceable information for Chinese consumers in the case of vegetables, while "picking/slaughtering date" and "history of illness and taking protective measures" are the most preferred information in the case of pork. In the case of dairy products, consumers prefer "processing information," "environmental information of the origin," and "traceable tag certification information" most. The results of this study call for the direct involvement of the Chinese government in the food safety information sharing system as following. First, given consumers' diverse preferences, different types of traceable information should be recorded into the information sharing platform depending on food types. Second, the government could promote the step-by-step construction of such a platform based on the priority of consumers' preferences. Third, new technology should be applied to guarantee the reliability of traceable information. Finally, local preferences in terms of the way consumers receive and understand information should be taken into consideration.

One of the main strategies to control the spread of infectious animal diseases is the implementation of movement restrictions. This paper shows a loss in efficiency of the movement restriction policy (MRP) when behavioral responses of farmers are taken into account. Incorporating the strategic behavior of farmers in an epidemiologic model reveals that the MRP can trigger premature animal sales by farms at high risk of becoming infected that significantly reduce the efficacy of the policy. The results are validated in a parameterized network via Monte Carlo simulations and measures to mitigate the loss of efficiency of the MRP are discussed. Financial aid to farmers can be justified by public health concerns, not only for equity. This paper contributes to developing an interdisciplinary analytical framework regarding the expansion of infectious diseases combining economic and epidemiologic dimensions.

Traffic congestion in freeway network is a prevalent transportation problem and leads to a strong degradation of freeway network facilities. This paper proposes a new coordinated optimization approach for freeway network, aiming to relieve the traffic congestion in freeway network equipped with the coordinated traffic controllers. The challenge is how to solve the problem between the traffic control goals of each path and those of the network. In this paper, the bi-level programming theory is used to address this problem. More exactly, in the path level, the optimal control model is designed to relieve congestion in each path of the test network. Furthermore, in the network level, the optimal model considers the traffic equilibrium and cost optimization. The efficiency of the proposed approach is tested on a well-known traffic network calibrated by the field test data of freeway network. The results show that the proposed approach has positive effects in balancing traffic load and improving the service level of freeway networks.

International audience; Vagus nerve stimulation (VNS) is an established adjunctive therapy for pharmacologically refractory epilepsy and depression and is currently in active clinical research for other applications. In current clinical studies, VNS is delivered in an open-loop approach, where VNS parameters are defined during a manual titration phase. However, the physiological response to a given VNS configuration shows significant inter and intra-patient variability and may significantly evolve through time. VNS closed-loop approaches, allowing for the optimization of the therapy in an adaptive manner, may be necessary to improve efficacy while reducing side effects. This paper proposes a generic, closed-loop control VNS system that is able to optimize a number of VNS parameters in an adaptive fashion, in order to keep a control variable within a specified range. Although the proposed control method is completely generic, an example application using the cardiac beat to beat interval (RR) as control variable will be developed in this paper. The proposed controller is based on a state transition model (STM) that can be configured using a partially or a fully-connected architecture, different model orders and different state-transition algorithms. The controller is applied to the adaptive regulation of heart rate and evaluated on 6 sheep, for 13 different targets, using partially-connected STM with 10 states. Also, partially and fully-connected STM defined by 30 states were applied to 7 other sheep for the same 10 targets. Results illustrate the interest of the proposed fully-connected STM and the feasibility of integrating this control system into an implantable neuromodulator.

Organizations are increasingly using sustainability reports to inform their stakeholders and the public about their sustainability practices. We apply topic modelling to 9,514 sustainability reports published between 1999 and 2015 in order to identify common topics and, thus, the most common practices described in these reports. In particular, we identify forty-two topics that reflect sustainability and focus on the coverage and trends of economic, environmental, and social sustainability topics. Among the first to analyse such a large amount of data on organizations' sustainability reporting, the paper serves as an example of how to apply natural language processing as a strategy of inquiry in sustainability research. The paper also derives from the data analysis ten propositions for future research and practice that are of immediate value for organizations and researchers.

Background: Biosensor-based detection provides a rapid and low-cost alternative to conventional analytical methods for revealing the presence of the contaminants in water as well as solid matrices. Although important to be detected, small analytes (few hundreds of Daltons) are an issue in biosensing since the signal they induce in the transducer, and specifically in a Quartz-Crystal Microbalance, is undetectable. A pesticide like parathion (M = 292 Da) is a typical example of contaminant for which a signal amplification procedure is desirable. Methods/Findings: The ballasting of the analyte by gold nanoparticles has been already applied to heavy target as proteins or bacteria to improve the limit of detection. In this paper, we extend the application of such a method to small analytes by showing that once the working surface of a Quartz-Crystal Microbalance (QCM) has been properly functionalized, a limit of detection lower than 1 ppb is reached for parathion. The effective surface functionalization is achieved by immobilizing antibodies upright oriented on the QCM gold surface by a simple photochemical technique (Photonic Immobilization Technique, PIT) based on the UV irradiation of the antibodies, whereas a simple protocol provided by the manufacturer is applied to functionalize the gold nanoparticles. Thus, in a non-competitive approach, the small analyte is made detectable by weighing it down through a “sandwich protocol” with a second antibody tethered to heavy gold nanoparticles. The immunosensor has been proved to be effective against the parathion while showing no cross reaction when a mixture of compounds very similar to parathion is analyzed. Conclusion/Significance: The immunosensor described in this paper can be easily applied to any small molecule for which polyclonal antibodies are available since both the functionalization procedure of the QCM probe surface and gold nanoparticle can be applied to any IgG, thereby making our device of general application in terms of target analyte. Published version

The present contribution focuses on investigating the interaction of people and environment in small-scale farming societies. Our study is centred on the particular way settlement location constraints economic strategy when technology is limited, and social division of work is not fully developed. Our intention is to investigate prehistoric socioeconomic organisation when farming began in the Old World along the Levant shores of Iberian Peninsula, the Neolithic phenomenon. We approach this subject extracting relevant information from a big set of ethnographic and ethnoarchaeological cases using Machine Learning methods. This paper explores the use of Bayesian networks as explanatory models of the independent variables–the environment- and dependent variables–social decisions-, and also as predictive models. The study highlights how subsistence strategies are modified by ecological and topographical variables of the settlement location and their relationship with social organisation. It also establishes the role of Bayesian networks as a suitable supervised Machine Learning methodology for investigating socio-ecological systems, introducing their use to build useful data-driven models to address relevant archaeological and anthropological questions.

Background In the wake of the severe impact of COVID-19 on the food security of the vulnerable groups in rural areas, the issue of how to achieve the Sustainable Development Goals 2 aims to “Zero Hunger” (SDG 2) and ensure the food safety of farmers has drawn unprecedented attention. Nutritional intake is generally used as an important indicator to reflect family food security. Under the background that Chinese farmers have gradually changed from the traditional diversified production mode to the specialized production of crops, the main purpose of this article is to explore what are the impact of crop specialization on farmers’ nutritional intake? Could the specialization of crop production be taken as an important measure to ensure the food safety of farmers and achieve the SDG 2? Methods Based on the micro-survey data from 866 farmer households in China, this paper using Seemingly Unrelated Regressions model, Group Regression model and Mediating Effect model to analyze the average and heterogeneous effects of crop specialization on the nutritional intake of farmers, as well as the mediating effect of income. In addition, robustness test and endogenous treatment were performed by using alternative explanatory variables and IV-2SLS method was used to estimate the results. Results After correcting for endogenous bias, crop specialization had a significant negative impact on energy intake and fat intake of farmers at the statistical level of 5% and 1% respectively, especially for farmers in mountainous areas. Household income played a mediating effect on the effect of crop specialization on farmers’ energy and fat intake, and the proportion of the masking effect was 8.43% and 8.96% respectively. In addition, household financial capital and social capital have a significant positive impact on farmers’ nutritional intake. Conclusions Crop specialization cannot guarantee the food safety of farmers in terms of nutritional intake. However, when the development trend of crop specialization is irreversible, more attention should be paid to improving the level of various livelihood capital of farmers, especially those in mountainous areas, and to continuously increasing their income to ease and ultimately eliminate the negative impact of crop specialization on farmers’ nutritional intake, which finally make everyone realize the SDG 2.

The electric tractor has the advantages of zero-emission, high efficiency, and low noise, which is the direction of future development and transformation of agricultural power machinery. Aim at the problem that the simulation methods commonly used in the development of electric tractor drive system are poorly generalized and cannot meet the simulation needs of complex multi-domain physical systems. This paper proposes a modeling method for an electric tractor drive system, takes the YTO-500 tractor as the research object, designs and calculates the overall scheme and parameters of its drive system, divides the drive system into modules, establishes the energy system, motor system and mechanical parts model based on Modelica, and integrates the simulation model of electric tractor drive system on this basis. The traction performance and transportation working conditions were simulated and tested. With compared and analyzed, in the traction characteristics, the simulation and test results of maximum speed, maximum traction force, and maximum traction power of each gear are consistent; within 400s transportation simulation conditions, the speed range of electric tractor is 13~28km·h-1, which is consistent with the speed range of electric tractor transportation gear. The results show that the simulation and the test results are consistent, which verifies the credibility of the simulation and the correctness of the model built, providing a basis for future research and development of agricultural machinery.

Land ecological security is the core of regional coordinated economic development and land ecological security planning. In this paper, with Shenzhen as the research area, 28 evaluation indicators were selected from 5 dimensions based on the DPSIR model to construct an indicator system for land ecological security evaluation, so as to evaluate the land ecological security status in the research area from 2009 to 2019. Based on the TOPSIS evaluation model, regional levels were determined, and finally the GM (1,1) model was adopted to scientifically predict the land ecological security system of Shenzhen from 2020 to 2025. The results showed that: (1) from the perspective of the main influencing factors, the weight of 16 indicators of Shenzhen’s land ecological security exceeds 0.03, including the total output value of agriculture, forestry, animal husbandry and fishery (D5) and Engel coefficient (I4). These factors are the main factors that have led to the deterioration of land ecological security in Shenzhen in the past decade; (2) comprehensive situation analysis revealed that from 2009 to 2019, the level of land ecological security in Shenzhen exhibited an increasing trend overall, but the land ecological security in Shenzhen still needs to be greatly improved; (3) regarding various subsystems, from 2009 to 2019, except the pressure subsystem which was in a downward trend, other subsystems showed a fluctuating and upward trend; (4) after modeling and calculation using the GM (1,1) model, it was concluded that most of the indicator factors are in a slow growing trend with the social and economic development of Shenzhen, but severe land ecological problem still exists. The research result is expected to provide a reference for the stable and sustainable development of society and economy and regional land ecosystem protection.

This paper addresses whether the ecosystem service of animal production from grasslands depends upon plant functional identity, plant functional diversity or if the resilience of production is a function of this diversity. Using the results of nine grazing experiments the paper shows that productivity is highly dependent on one leaf trait, leaf dry matter content, as well as rainfall. Animal (secondary) productivity is not dependent on plant functional diversity, but the variability in productivity of grasslands is related to the functional diversity of leaf dry matter content. This and a range of independent studies have shown that functional diversity is reduced at high levels of grassland productivity, so it appears that there is a trade-off between productivity and the resilience of productivity in the face of environmental variation.

BACKGROUND: Currently there is a critical need for accurate and standardized wildlife-vehicle collision data, because it is the underpinning of mitigation projects that protect both drivers and wildlife. Gathering data can be challenging because wildlife-vehicle collisions occur over broad areas, during all seasons of the year, and in large numbers. Collecting data of this magnitude requires an efficient data collection system. Presently there is no widely adopted system that is both efficient and accurate. METHODOLOGY/PRINCIPAL FINDINGS: Our objective was to develop and test an integrated smartphone-based system for reporting wildlife-vehicle collision data. The WVC Reporter system we developed consisted of a mobile web application for data collection, a database for centralized storage of data, and a desktop web application for viewing data. The smartphones that we tested for use with the application produced accurate locations (median error = 4.6-5.2 m), and reduced location error 99% versus reporting only the highway/marker. Additionally, mean times for data entry using the mobile web application (22.0-26.5 s) were substantially shorter than using the pen/paper method (52 s). We also found the pen/paper method had a data entry error rate of 10% and those errors were virtually eliminated using the mobile web application. During the first year of use, 6,822 animal carcasses were reported using WVC Reporter. The desktop web application improved access to WVC data and allowed users to easily visualize wildlife-vehicle collision patterns at multiple scales. CONCLUSIONS/SIGNIFICANCE: The WVC Reporter integrated several modern technologies into a seamless method for collecting, managing, and using WVC data. As a result, the system increased efficiency in reporting, improved accuracy, and enhanced visualization of data. The development costs for the system were minor relative to the potential benefits of having spatially accurate and temporally current wildlife-vehicle collision data. Language: en

A review with meta-analysis of outflow and nitrate loss reduction in controlled drainage (CD) vs conventional, free drainage (FD) was carried out in the study. Since the results of experimental field studies usually cover short periods of data collection, hence in this paper, meta-analyses were based on model studies that usually cover a longer time range. The databases Web of Science and Scopus were searched for eligible English articles, published until December 2020, that describe the quantity and quality of drainage water. The meta-analysis of outflow and nitrate loss reduction in CD vs FD using the mean difference (MD) with a confidence interval (CI) of 95%. The influence of each study was measured through heterogeneity, sensitivity analyses and publication bias using STATISTICA (version 13.3) for all analyses. Of the 107 works identified, 18 were finally included in the analysis based on established criteria required for an appropriate meta-analysis. In general the results indicate a reduction in average drainage outflow of 30.5% (MD = -71.26 mm; 95% CI, -103.49 –-39.04; p = 0.000) in arable land with CD in comparison to FD practice. In the case of nitrate load the reduction was 33.61% and in the drainage water there was lower content in CD practice by an average of 8.36 kg NO3 ha-1year-1 (95% CI, -9.93 –-6.79; p = 0.000). Subgroup analysis of two meta-analyses indicates that the results concerning these associations may vary with the calculated weight for each article, in which the number of years of study had the most significant impact.

As an important measure to enhance the allocation of land resources and achieve moderate scale operation in China, land transfer has an irreplaceable role in giving full play to the social and economic value of land. This paper uses data from the China Family Panel Studies in 2018 and applies OLS, PSM and mediator effects to study the impact of land transfer on household income. The results of the study show that: firstly, participation in land transfer can significantly increase the income level of farming households, but the impact of different land transfer acts on household income varies. Secondly, the age and physical condition of the household head, the number of agricultural and non-agricultural members in the household and the poverty status of the household all have a negative effect on household income. On the other hand, the education level of the household head, the household size and the presence of village officials in the household, agricultural subsidies, land titling and land size all have a positive effect on household income. Thirdly, the impact on household income for households that did not participate in land transfer is greater than for those that did. The results of the mediator effect test show that land transfer has a significant effect on household farm income, and that farm income has a full mediator effect, but all have a positive significant effect on household income.

Large input and high loss of chemical fertilizer are the major causes of agricultural non-point source pollution in China. Employing fertilizer loss and micro-health data, this paper analyzes the effects of chemical fertilizer loss on the health of rural elderly and the medical cost in China. Results of the difference-in-differences (DID) method indicate that one kg/ha increase in fertilizer loss alters a key medical disability index (Activities of Daily Living) by 0.0147 (0.2 percent changes) and the number of diseases by 0.0057 for rural residents of 65 and older. This is equivalent to CNY 316 million (USD 45 million) at national medical cost. Furthermore, the age of onset is younger in regions with higher fertilizer loss. One kg/ha increase of fertilizer loss advances the age of onset by 0.267 year, which will cause long-term effect on public health. Our results are robust to a variety of robustness checks.

This paper aims to examine the key determinants and efficiency of China’s agricultural exports with its 114 importing countries by applying the Stochastic Frontier Analysis (SFA) on an augmented gravity model for the period of 2000–2019. The Poisson Pseudo Maximum Likelihood (PPML) and the fixed effect models were also estimated simultaneously to confirm the robustness of our findings. The results reveal that China’s economic size (GDP) and its importing countries, the Belt and Road Initiative (BRI), common border, and the Chinese language positively determine China’s agricultural export flows. The results, on the other hand, also reveal that China’s agricultural export is adversely influenced by the income (per capita GDP) of China and its trade partners, currency depreciation, distance, and landlocked. On an average account, China has untapped the potential of 51% in its agriculture export with the countries used in this study. We provide policy suggestions as part of our study.

The COVID-19 pandemic has impacted almost all the sectors including agriculture in the country. The present paper investigates the impact of COVID-19 induced lockdown on both wholesale and retail prices of major pulses in India. The daily wholesale and retail price data on five major pulses namely Lentil, Moong, Arhar, Urad and Gram are collected for five major markets in India namely Delhi, Mumbai, Kolkata, Chennai and Hyderabad during the period January, 2019 to September, 2020 from Ministry of Consumer Affairs, Food & Public Distribution, Government of India. The Government of India declared nationwide lockdown since March, 24, to May, 31, 2020 in different phases in order to restrict the spread of the infection due to COVID-19. To see the impact of lockdown on price and price volatility, time series model namely Autoregressive integrated moving average (ARIMA) model with error following Generalized autoregressive conditional heteroscedastic (GARCH) model incorporating exogenous variable as lockdown dummy in both mean as well variance equations. It is observed that in almost all the markets, lockdown has significant impact on price of the pulses whereas in few cases, it has significant impact on price volatility.

Annual monitoring of the spatial distribution of cultivated land is important for maintaining the ecological environment, achieving a status quo of land resource management, and guaranteeing agricultural production. With the gradual development of remote sensing technology, it has become a common practice to obtain cultivated land boundary information on a large scale with the help of satellite Earth observation images. Traditional land use classification methods are affected by multiple types of land cover, which leads to a decrease in the accuracy of cultivated land mapping. In contrast, although the current advanced methods (such as deep learning) can obtain more accurate cultivated land mapping results than traditional methods, such methods often require the use of a massive amount of training samples, large computing power, and highly complex model tuning processes, increasing the cost of mapping and requiring the involvement of more professionals. This has hindered the promotion of related methods in mapping institutions. This paper proposes a method based on time series vector features (MTVF), which uses vector thinking to establish the features. The advantage of this method is that the introduction of vector features enlarges the differences between the different land cover types, which overcomes the loss of mapping accuracy caused by the influences of the spectra of different ground objects and ensures the calculation efficiency. Moreover, the MTVF uses a traditional method (random forest) as the classification core, which makes the MTVF less demanding than advanced methods in terms of the number of training samples. Sentinel-2 satellite images were used to carry out cultivated land mapping for 2020 in northern Henan Province, China. The results show that the MTVF has the potential to accurately identify cultivated land. Furthermore, the overall accuracy, producer accuracy, and user accuracy of the overall study area and four sub-study areas were all greater than 90%. In addition, the cultivated land mapping accuracy of the MTVF is significantly better than that of the maximum likelihood, support vector machine, and artificial neural network methods.

Although many endo-ß-1,4-glucanases have been isolated in invertebrates, their cellulolytic systems are not fully understood. In particular, gastropod feeding on seaweed is considered an excellent model system for production of bioethanol and renewable bioenergy from third-generation feedstocks (microalgae and seaweeds). In this study, enzymes involved in the conversion of cellulose and other polysaccharides to glucose in digestive fluids of the sea hare (Aplysia kurodai) were screened and characterized to determine how the sea hare obtains glucose from sea lettuce (Ulva pertusa). Four endo-ß-1,4-glucanases (21K, 45K, 65K, and 95K cellulase) and 2 ß-glucosidases (110K and 210K) were purified to a homogeneous state, and the synergistic action of these enzymes during cellulose digestion was analyzed. All cellulases exhibited cellulase and lichenase activities and showed distinct cleavage specificities against cellooligosaccharides and filter paper. Filter paper was digested to cellobiose, cellotriose, and cellotetraose by 21K cellulase, whereas 45K and 65K enzymes hydrolyzed the filter paper to cellobiose and glucose. 210K ß-glucosidase showed unique substrate specificity against synthetic and natural substrates, and 4-methylumbelliferyl (4MU)-ß-glucoside, 4MU-ß-galactoside, cello-oligosaccharides, laminarin, and lichenan were suitable substrates. Furthermore, 210K ß-glucosidase possesses lactase activity. Although ß-glucosidase and cellulase are necessary for efficient hydrolysis of carboxymethylcellulose to glucose, laminarin is hydrolyzed to glucose only by 210K ß-glucosidase. Kinetic analysis of the inhibition of 210K ß-glucosidase by D-glucono-1,5-lactone suggested the presence of 2 active sites similar to those of mammalian lactase-phlorizin hydrolase. Saccharification of sea lettuce was considerably stimulated by the synergistic action of 45K cellulase and 210K ß-glucosidase. Our results indicate that 45K cellulase and 210K ß-glucosidase are the core components of the sea hare digestive system for efficient production of glucose from sea lettuce. These findings contribute important new insights into the development of biofuel processing biotechnologies from seaweed.

Identifying agricultural disaster risk regions before the occurrence of climate-related disasters is critical for early mitigation planning. This paper aims to identify these regions based on data from the Food and Agriculture Organization of the United Nations (FAO), the bilateral and multilateral trade network data of the World Integrated Trade Solution(WITS) and the agent-based economic model Acclimate. By applying a uniform forcing across agricultural sectors of some breadbasket regions (US, EU and China), when single and simultaneous extreme weather events occur, such as the 2018 European heatwave, production and consumption value losses and gains are calculated at regional and global levels. Comparing the FAO data sets, WITS, and Acclimate’s production value losses, the results show a strong dependence of agricultural production losses on a region’s output and connectivity level in the global supply and trade network. While India, Brazil, Russia, Canada, Australia, and Iran are highly vulnerable, the imposition of export restrictions to compensate for demand shortfalls makes Sub-Saharan Africa the most vulnerable region, as it is heavily dependent on agricultural imports. In addition, simultaneous extreme weather events can exacerbate the loss of value of agricultural production relative to single extreme weather events. Agricultural practices to increase production such as smart farming, increased investment in plantation agriculture, and diversification of trading partners can help mitigate future food security risks in Sub-Saharan Africa and other agricultural import-dependent regions.

Heavy metal contamination in soil is an important factor affecting the determination of safe redevelopment methods for industrial and mining land. In this paper, the soil environment of a typical mining city in northern China was taken as the research object, 148 surface soil samples were collected and the contents of heavy metals were measured. The health risk classification criteria for heavy metal contamination of soils and the method of priority assessment for redevelopment were used. The results showed that: the risk of potential utilization types of heavy metals in the abandoned industrial and mining land is different. When the utilization type is agricultural land, the soil environmental quality is good as a whole, and a small number of plots are polluted by cadmium (Cd)and mercury (Hg); When the land use type is construction land, the risk of heavy metal pollution comes from chromium (Cr); The priority of development in this study area is as follows: agricultural land > construction land > ecological land.

This paper highlights the importance of recording at least a (1)H nuclear magnetic resonance (NMR) spectrum to verify identity of standards used in analyses of organic materials irrespective of source. We show the importance of this approach with an example of a quantitative high-performance liquid chromatography (HPLC) study undertaken with green tea extracts that required the use of several polyphenols as standards. In the course of the study one of these standards [(-)-epigallocatechin, EGC], although having the physical appearance and appropriate HPLC chromatographic behavior of EGC, proved by (1)H-NMR to be a completely different class of molecule. For us, this raised significant questions concerning validity of many published pieces of research that used quantitative HPLC methods without first performing rigorous validation of the employed standards prior to their use. This paper clearly illustrates the importance of validation of all standards used in analysis of organic materials by recording at least a (1)H-NMR spectrum of them prior to their use.