Food Shortages Research Articles

Reviewing the impact of climate change on global food security: Challenges and solutions

This review examines the intricate relationship between climate change and global food security, elucidating the challenges posed by climate variability and exploring potential solutions to mitigate its adverse effects. Climate change presents formidable obstacles to food security worldwide, disrupting agricultural productivity, exacerbating food shortages, and deepening malnutrition. Shifts in temperature and precipitation patterns, coupled with the increasing frequency of extreme weather events, threaten crop yields, livestock health, and food distribution networks, particularly in vulnerable regions. The review identifies key challenges confronting global food security in the context of climate change, including diminished agricultural productivity, heightened food price volatility, and heightened risks of food insecurity and malnutrition. It underscores the disproportionate impact of climate change on marginalized communities, smallholder farmers, and low-income populations, who bear the brunt of environmental degradation and lack the resources to adapt. In response to these challenges, the review explores a range of solutions and strategies aimed at enhancing food security resilience in a changing climate. It discusses the importance of climate-smart agricultural practices, such as agroforestry, crop diversification, and soil conservation, in bolstering the resilience of agricultural systems and improving resource efficiency. Additionally, the review highlights the significance of enhancing access to climate information, investing in sustainable infrastructure, and promoting gender equity in agriculture to foster inclusive and adaptive food systems. Furthermore, the review underscores the critical role of policy interventions, international collaboration, and community engagement in addressing climate-related food security challenges and advancing sustainable development goals. By integrating climate adaptation and mitigation measures into agricultural policies, promoting research and innovation, and fostering multi-stakeholder partnerships, it is possible to build more resilient and equitable food systems that can withstand the impacts of climate change and ensure food security for all. In conclusion, the review emphasizes the urgency of concerted action to address the complex interplay between climate change and global food security. Through collective efforts and targeted interventions, it is feasible to mitigate the adverse effects of climate change on food systems and pave the way for a more sustainable and food-secure future. Keywords: Impact, Climate Change, Global, Food Security, Challenges.

Potato Consumption Forecasting Based on a Hybrid Stacked Deep Learning Model

AbstractPotato consumption forecasting is crucial for several stakeholders in the food market. Due to the market flexibility, the farmers can manipulate the volumes planted for a given type of produce to reduce costs and improve revenue. Consequently, it means that establishing optimal inventories or inventory levels is possible and critical in that sense for the sellers to avoid either inadequate inventory or excessive inventories that may lead to wastage. In addition, governments can predict future food deficits and put measures in place to guarantee that they have a steady supply of food some of the time, especially in regions that involve the use of potatoes. Increased potato-eating anticipation has advantages for the sellers and buyers of the potatoes. The experiments of this study employed various machine learning and deep learning (DL) models that comprise stacked long short-term memory (Stacked LSTM), convolutional neural network (CNN), random forest (RF), support vector regressor (SVR), K-nearest neighbour regressor (KNN), bagging regressor (BR), and dummy regressor (DR). During the study, it was discovered that the Stacked LSTM model had superior performance compared to the other models. The Stacked LSTM model achieved a mean squared error (MSE) of 0.0081, a mean absolute error (MAE) of 0.0801, a median absolute error (MedAE) of 0.0755, and a coefficient of determination (R2) value of 98.90%. These results demonstrate that our algorithms can reliably forecast global potato consumption until the year 2030.

An ensemble deep learning models approach using image analysis for cotton crop classification in AI-enabled smart agriculture

BackgroundAgriculture is one of the most crucial assets of any country, as it brings prosperity by alleviating poverty, food shortages, unemployment, and economic instability. The entire process of agriculture comprises many sectors, such as crop cultivation, water irrigation, the supply chain, and many more. During the cultivation process, the plant is exposed to many challenges, among which pesticide attacks and disease in the plant are the main threats. Diseases affect yield production, which affects the country’s economy. Over the past decade, there have been significant advancements in agriculture; nevertheless, a substantial portion of crop yields continues to be compromised by diseases and pests. Early detection and prevention are crucial for successful crop management.MethodsTo address this, we propose a framework that utilizes state-of-the-art computer vision (CV) and artificial intelligence (AI) techniques, specifically deep learning (DL), for detecting healthy and unhealthy cotton plants. Our approach combines DL with feature extraction methods such as continuous wavelet transform (CWT) and fast Fourier transform (FFT). The detection process involved employing pre-trained models such as AlexNet, GoogLeNet, InceptionV3, and VGG-19. Implemented models performance was analysed based on metrics such as accuracy, precision, recall, F1-Score, and Confusion matrices. Moreover, the proposed framework employed ensemble learning framework which uses averaging method to fuse the classification score of individual DL model, thereby improving the overall classification accuracy.ResultsDuring the training process, the framework achieved better performance when features extracted from CWT were used as inputs to the DL model compared to features extracted from FFT. Among the learning models, GoogleNet obtained a remarkable accuracy of 93.4% and a notable F1-score of 0.953 when trained on features extracted by CWT in comparison to FFT-extracted features. It was closely followed by AlexNet and InceptionV3 with an accuracy of 93.4% and 91.8% respectively. To further improve the classification accuracy, ensemble learning framework achieved 98.4% on the features extracted from CWT as compared to feature extracted from FFT.ConclusionThe results show that the features extracted as scalograms more accurately detect each plant condition using DL models, facilitating the early detection of diseases in cotton plants. This early detection leads to better yield and profit which positively affects the economy.

Evaluation of Food Security in North China Based on Food Production Level.

This paper focuses on county-level grain production and food security in North China; selects 17 indicators from both climatic conditions and human activities; applies yield fluctuation coefficients, spatial econometric modelling, the random forest method, and factor analysis to study the characteristics of grain production in North China and the influencing factors; and evaluates the situation of food security in North China based on grain production capacity. The following results were obtained: (1) The spatial and temporal changes in grain production located in North China from 2000 to 2020 are obvious. The grain output in North China from 2000 to 2020 maintains fluctuating growth at a rate of 0.38 × 1011 kg/10a. The east and south are the key areas for grain production in North China. Grain output was relatively stable except for 2003. with the cold spots of grain production being mainly in the northwestern area and the hot spots in the central and southern areas. (2) The changes in grain production in North China from 2000 to 2020 were less affected by climate and mainly influenced by human activity indicators. (3) As time progresses, the area of food shortage zones decreases in size, becoming evenly distributed and dispersed from the initial concentration in northern Hebei and most of Shanxi; the change in the supply-demand equilibrium zones is not obvious; and the area of surplus grain zones increases markedly in size, with a tendency to expand from the south and centre of the study area to the west and north. The grain production capacity of counties in the northwest and north is generally low, and even counties located in surplus grain areas have potential food security risks. However, in the east and south, due to their high grain production capacity, the per capita grain supply situation may be alleviated even in counties located in grain shortage areas. This study can deepen the understanding of the characteristics of food production in North China and enrich the research on food security. Analyses of factors influencing food production will improve a deeper understanding of food security. Food security evaluation based on food production capacity will contribute to a more precise and comprehensive understanding of the food security pattern in North China.

Sustainable Livestock Farming with Oil Seed Crops and Their By-Products

The increasing human population and food shortage are fueling the demand for alternative feed resources for animals not meant for human consumption. Oil seeds and their derivatives are suitable options to meet the escalating global demand for animal feed proteins; camelina is one of them. Camelina sativa (CS), an ancient oilseed crop belonging to the Brassicaceae family, is known for its resistance to drought and cold, as well as its various uses for meal, oil, and other products. However, it also has some anti-nutritional factors (ANF) that can limit its use as animal feed. These ANFs can be reduced by various methods, such as enzyme addition, heat treatment, fermentation, or genetic engineering. CS and its by-products can affect animal metabolism, especially lipid metabolism and hormone levels, and can also improve the fat profile of meat and milk products, making them more suitable for human consumption and health. CS and its by-products achieved weight gain and protected dietary PUFAs, but decreased bio-hydrogenation intermediates. Small ruminants fed CS-supplemented diets produced meat with a suitable fat profile for human consumption. Feeding with CS seeds and derivatives decreased milk fat concentration, yield, and fat-corrected milk. Camelina forage, however, increased the milk fat percentage. The effects of CS and its by-products on milk fatty acid composition were contradictory. CS meals may improve the composition of milk products, making them healthier for humans. Researchers need to determine how CS meals can be used in dairy ewe and goat diets at different life stages.

A Review on Biotechnological Innovations in Developing Stress-Tolerant Crops for Adverse Environmental Conditions

The development of stress-tolerant crops through advanced biotechnological approaches is critical for enhancing global food security and sustainability in the face of climate change and increasing environmental stresses. Emerging tools such as CRISPR/Cas9 gene editing and synthetic biology are revolutionizing genetic engineering by enabling precise, targeted modifications of plant genomes to improve drought, salinity, heat, and cold tolerance. Integrative approaches that combine genomics, transcriptomics, proteomics, and metabolomics provide a comprehensive understanding of plant stress responses, facilitating the identification of key regulatory genes and metabolic pathways. High-throughput phenotyping and RNA interference (RNAi) technologies further enhance trait identification and manipulation, accelerating the development of robust stress-tolerant varieties. The deployment of these crops has demonstrated significant yield improvements and stability in adverse conditions, reducing the risk of crop failures and food shortages. Drought-tolerant maize and rice varieties have increased yields by 20-30% under water-scarce conditions, while salt-tolerant rice and wheat varieties have enabled cultivation in saline soils. Heat-tolerant crops maintain productivity in high-temperature regions, and cold-tolerant varieties extend growing seasons in temperate areas. These advancements not only enhance crop productivity but also promote sustainable agricultural practices by reducing the need for chemical inputs and supporting the resilience of food systems. Moreover, the socio-economic benefits include improved livelihoods for smallholder farmers through increased incomes and economic stability. Continued interdisciplinary research and collaboration are essential to fully realize the potential of these technologies in addressing global agricultural challenges and ensuring a stable food supply for future generations.

P-726 Age of natural menopause and its associated factors among ethnic Han and Tibetan Chinese women: findings from a China Multi-Ethnic Cohort (CMEC) study

Abstract Study question Is there a disparity in the age of natural menopause (ANM) between ethnic Han and Tibetan Chinese women? Summary answer The present study has discovered a significant difference in the ANM between ethnic Han and Tibetan Chinese women. What is known already The ANM indicates the termination of ovarian function and the reproductive lifespan of the ovary. Factors influencing ANM include genetic, ovarian diseases or surgery, environment, and unhealthy lifestyles. Some studies reported that ANM was different among different ethnics, such as lower in African, Latin American, Asian, whereas higher in Europe, Australia and America. Ethnic Tibetan Chinese mainly resides in an environment with high altitude, low oxygen level, and intense ultraviolet radiation. They also have unique dietary and lifestyle habits, which might result in different ANM compared to ethnic Han Chinese. However, there are few studies on ANM between the two. Study design, size, duration We performed a cross-section study involving 11174 ethnic Han and 1049 ethnic Tibetan Chinese postmenopausal women from Chengdu city and Aba Prefecture in Sichuan province. The participants were recruited by the China Multi-Ethnic Cohort (CMEC) study from May 2018 to September 2019. Participants/materials, setting, methods Information of the postmenopausal women was derived from CMEC baseline questionnaire. Ethnicity was used as the primary exposure variable. Regression models incorporating linear, quadratic and quadratic with interaction terms on age were used to assess the association of ANM with the ethnicity. Main results and the role of chance The mean ANM of ethnic Han Chinese women was later than that of ethnic Tibetan Chinese women (48.50 ± 4.20 years vs. 47.80 ± 4.92 years, P < 0.05). Multivariate linear regression analysis showed a significant disparity in the ANM between the two groups, and sexual life, higher education, no smoking, never experienced severe food shortage, later age of menarche and more times of pregnancy were associated with later ANM (P < 0.05). Furthermore, the quadratic and interaction models demonstrated a significant non-linear association between the ANM and the age at the time of survey. In both groups, the ANM showed a trend of first rising and then declining with the increase of the age at the time of survey Notably, among women younger than 68, the ANM of ethnic Han Chinese was significantly later than that of ethnic Tibetan Chinese. Limitations, reasons for caution The information regarding menopausal women, including ANM and potential influencing factors were obtained from self-reports. Additionally, the duration of exposure to these potential influencing factors remained uncertain. Wider implications of the findings This is the first study with a large sample size comparing ANM between ethnic Han and Tibetan Chinese women. Notably, the age at the time of survey and ethnicity have independently contributed to variation in ANM, and significant interaction effects on ANM are found between age of survey and ethnicity. Trial registration number not applicable

Contribución de la ganadería mexicana a la seguridad alimentaria nacional, a tres sexenios del TLCAN

In recent decades Food Security (FS) has become a topic of global interest, with food shortages and deficient diets at home being a serious problem faced by humanity. The objective was to analyze the role of livestock in the FSof Mexico, period 1994-2012, toevaluate and contrast, livestock production and the availability of food for the national population. A descriptive and comparative multidimensional analysis was carried out with statistics from official sources, finding a significant increase in the volume of livestock production, a significant rise in prices and a sustained deficit trade balance. Therefore, livestock shows a significant contribution to the Mexican food security, supplying with national production the nutritional requirements established by the National Council for the Evaluation of Social Development Policy (CONEVAL) for a balanced and healthy diet.

Improving bee feed recipes to safeguard honeybee colonies during times of food scarcity.

In beekeeping, when natural nectar or pollen sources become limited, it is crucial to provide supplemental bee feed to maintain the viability of the bee colony. This study was conducted during the autumn food shortage season, during which bees were fed with different proportions of modified bee feed. We identified an optimal bee diet by evaluating honeybee longevity, food consumption, body weight, and gut microbe distribution, with natural pollen serving as a control diet. The results indicated that bees preferred a mixture of 65% defatted soy flour, 20% corn protein powder, 13% wheat germ flour, 2% yeast powder, and a 50% sucrose solution. This bee food recipe significantly increased the longevity, feed consumption, and body weight of bees. The group fed the natural pollen diet exhibited a greater abundance of essential intestinal bacteria. The bee diets used in this study contained higher protein levels and lower concentrations of unsaturated fatty acids and vitamins than did the diets stored within the colonies. Therefore, we propose that incorporating both bee feed and natural pollen in beekeeping practices will achieve more balanced nutritional intake.

Combined effects of herbicides and insecticides reduce biomass of sensitive aquatic invertebrates

The structure and biomass of aquatic invertebrate communities play a crucial role in the matter dynamics of streams. However, biomass is rarely quantified in ecological assessments of streams, and little is known about the environmental and anthropogenic factors that influence it. In this study, we aimed to identify environmental factors that are associated with invertebrate structure and biomass through a monitoring of 25 streams across Germany. We identified invertebrates, assigned them to taxonomic and trait-based groups, and quantified biomass using image-based analysis. We found that insecticide pressure generally reduced the abundance of insecticide-vulnerable populations (R2 = 0.43 applying SPEARpesticides indicator), but not invertebrate biomass. In contrast, herbicide pressure reduced the biomass of several biomass aggregations. Especially, insecticide-sensitive populations, that were directly (algae feeder, R2 = 0.39) or indirectly (predators, R2 = 0.29) dependent on algae, were affected. This indicated a combined effect of possible food shortage due to herbicides and direct insecticide pressure. Specifically, all streams with increased herbicide pressure showed a reduced overall biomass share of Trichoptera from 43 % to 3 % and those of Ephemeroptera from 20 % to 3 % compared to streams grouped by low herbicide pressure. In contrast, insecticide-insensitive Gastropoda increased from 10 % to 45 %, and non-vulnerable leaf-shredding Crustacea increased from 10 % to 22 %. In summary, our results indicate that at the community level, the direct effects of insecticides and the indirect, food-mediated effects of herbicides exert a combined effect on the biomass of sensitive insect groups, thus disrupting food chains at ecosystem level.

Prevalence of Rotifers in the Tigris River before and after the Al Kut Dam /Iraq

A study was conducted to analyze the makeup of the rotifera community in terms of both quantity and quality. The study took place over four seasons at two locations on the Tigris River, both before and after the construction of Al-Kut's Barrage. The study period spanned from January to December 2023, during which a total of 48 taxonomic units of rotifera were discovered. The overall population density of the Rotifera at the initial location prior to Al-Kut's Barrage varied between the peak value of 10509.9 individuals/m3 in the spring and the minimum value of 2621.1 individuals/m3 in the winter. The second location downstream of Al-Kut's Barrage had a peak density of 5198.8 persons per cubic meter during spring, while the lowest density of 1088.3 individuals per cubic meter was seen during winter. The study examined the indicators of relative abundance and the Shannon-Wienercoefficient of biological diversity. The values observed ranged from 2.198 to 6542 bits per individual. The index of species appearance homogeneity ranged from 0.67 to 0.85, and the index of species abundance ranged from 5.25 to 7.89. The decline in the population of Rotifera during winter is attributed to the adverse impact of cold temperatures, which hampers the restricted growth of the species. During the winter season, there is a reduction in illumination and phytoplankton, resulting in a fall in food availability. This shortage of food is responsible for the decline in Rotifera populations.

Genome sequencing of Coryphaenoides yaquinae reveals convergent and lineage‐specific molecular evolution in deep‐sea adaptation

AbstractAbyssal (3501–6500 m) and hadal (>6500 m) fauna evolve under harsh abiotic stresses, characterized by high hydrostatic pressure, darkness and food shortage, providing unique opportunities to investigate mechanisms underlying environmental adaptation. Genomes of several hadal species have recently been reported. However, the genetic adaptation of deep sea species across a broad spectrum of ocean depths has yet to be thoroughly investigated, due to the challenges imposed by collecting the deep sea species. To elucidate the correlation between genetic innovation and vertical distribution, we generated a chromosome‐level genome assembly of the macrourids Coryphaenoides yaquinae, which is widely distributed in the abyssal/hadal zone ranging from 3655 to 7259 m in depth. Genomic comparisons among shallow, abyssal and hadal‐living species identified idiosyncratic and convergent genetic alterations underlying the extraordinary adaptations of deep‐sea species including light perception, circadian regulation, hydrostatic pressure and hunger tolerance. The deep‐sea fishes (Coryphaenoides Sp. and Pseudoliparis swirei) venturing into various ocean depths independently have undergone convergent amino acid substitutions in multiple proteins such as rhodopsin 1, pancreatic and duodenal homeobox 1 and melanocortin 4 receptor which are known or verified in zebrafish to be related with vision adaptation and energy expenditure. Convergent evolution events were also identified in heat shock protein 90 beta family member 1 and valosin‐containing protein genes known to be related to hydrostatic pressure adaptation specifically in fishes found around the hadal range. The uncovering of the molecular convergence among the deep‐sea species shed new light on the common genetic innovations required for deep‐sea adaptation by the fishes.

ANALYZING THE CAUSES OF WATER SHORTAGE, LOW CROP YIELD, AND FOOD CRISIS IN PAKISTAN: A LONGITUDINAL ANALYSIS (1991-2019)

Pakistan has been facing problem of low crop yield, food shortage, and high prices of food items, and it has to import food items for billions of dollars every year to meet domestic needs. The literature shows a sufficient gap to investigate the causes of low crop yield. This motivates the authors to investigate the causes of water shortage, low crop yields, and high prices of agriculture inputs, using 28 years of data spanning from 1991 to 2019. The selected variables include crop yield as the dependent variable and water availability, precipitation, seed, fertilizer, and pesticides as independent variables. Various statistical techniques such as descriptive statistics, Correlation matrix, ADF test, ARDL Model, Bound test, and Error Correction model were employed to determine the relationship between variables. The findings reveal that all independent variables except precipitation have a positive association with crop yield. The comparison of the results of ARDL and ECM Models shows that the variables water, seed, fertilizer, and pesticides have a significant and positive relationship with crop yield in the short run rather than in the long run. In light of these findings, the study suggests that the Government of Pakistan should build water storage, ensure the availability of agriculture inputs at subsided prices, and introduce modern agriculture technologies to enhance crop yield to ensure food security and save billions of dollars being spent on the import of food items every year.

Analyzing the Russo-Ukrainian Conflict: Geopolitical Insecurities of Russia and Their Consequences in Eurasia

This research delves into the geographical and historical factors underpinning the Russia-Ukraine war, exploring Russia's expansive strategies and the role of geography in its foreign policy. It highlights the conflict's extensive implications across the Eurasian region, manifesting in crises like global food and energy shortages, and shifting geopolitical alliances. By examining Russia's defensive maneuvers against Western influences, the study offers insights into the complex dynamics of regional security, the motivations behind Russia's foreign policies, and the broader impacts of the war on global stability. Recommendations focus on diplomatic resolutions to mitigate the conflict's repercussions.

Food Insecurity and Coping Mechanism During COVID-19 Pandemic: Evidence from Indonesia

This study provides empirical evidence with respect to identifying whether the coping mechanism adopted by households in Indonesia significantly influences food security during the COVID-19 pandemic. The data used was from the fourth round of high-frequency monitoring data of COVID-19 impact on households from the World Bank (www.microdata.worldbank.org), which was collected between November 3rd – 15th, 2020 through the phone-based survey. By employing the logit regression model and controlling for demography characteristics such as gender, age, and education level, this study confirms that reducing non-food consumption has been effectively lowering the probability of food insecurity in all forms of indicators, including “were hungry” (3.3 percentage points), “went without eating” (2.0 percentage points), “unable to eat nutritious food” (6.6 percentage points), “food shortage” (9.6 percentage points), and “eat less” (5.6 percentage points). Additionally, households who relied on saving had a lower probability of 13.7 percentage points of being unable to eat nutritious food, while households who received assistance from the government had a lower chance of 2.4 percentage points of experiencing hunger during the pandemic. This study emphasizes that temporary strategies or short-term coping mechanisms such as relying on support from relatives, taking loans, and engaging in additional income-generating activities, as well as reducing food consumption may not contribute effectively to food security, instead, these types of coping mechanisms may exacerbate food insecurity. The findings of this study offer several implications in regard to enhancing the capacity of households to cope with the difficulties during crises as well as policy implications to design effective interventions in dealing with future shocks.

Artificial Intelligence on Food Vulnerability: Future Implications within a Framework of Opportunities and Challenges

This study explores the field of artificial intelligence (AI) through the lens of Stephen Hawking, who warned of its potential dangers. It aims to provide a comprehensive understanding of AI and its implications for food security using a qualitative approach and offering a contemporary perspective on the topic. The study explores the challenges and opportunities presented by AI in various fields with an emphasis on the global food reality. It also highlights the critical importance of striking a harmonious balance between technological progress and the preservation of local wisdom, cultural diversity, and environmental sustainability. In conclusion, the analysis argues that AI is a transformative force with the potential to address global food shortages and facilitate sustainable food production. However, it is not without significant risks that require rigorous scrutiny and ethical oversight.

A novel heuristic algorithm for disruption mitigation in a global food supply chain

The Global Food Supply Chain (GFSC) often encounters challenges in maintaining the continuous flow of essential food products such as rice and wheat. In this paper, we consider possible disruptions in supply and transportation in GFSC. Disruptions may cause severe food shortages in some parts of the world. Moreover, a disruption is not necessarily a single independent event, as multiple disruptions may occur sequentially or simultaneously. After any interruption, it is essential to reoptimize the remaining flow activities in a short period under the changed conditions. Although both the initial flow plan and post-disruption plan can be generated by formulating them as Mixed Integer Linear Programming (MILP) models, such a mitigation plan is challenging because of time constraints and when multiple disruptions are considered. To address this issue, we proposed a novel heuristic algorithm that revises the ideal plan in the event of a disruption. The developed heuristic can deal with different types of disruptions, as well as a series of disruptions. The performance of the heuristic was judged by solving 300 problem instances and comparing the results with those obtained from the exact method. To demonstrate the applicability of the proposed algorithm in practice, we have solved three real-world disruption Scenarios. The analysis of results uncovered crucial managerial insights, recommending strategies for disruption mitigation, and proved to be an effective method for post-disruption planning.

ROS-Induced Autophagy of Skeletal Muscle Confers Resistance of Rice Flower Carp (Cyprinus carpio) to Short-Term Fasting.

Starvation is one of the main stresses for fish due to food shortage, the evasion of predators, and intraspecific competition. This research evaluated the impact of brief fasting periods on reactive oxygen species (ROS) levels, antioxidant response, mRNA expression of antioxidants, autophagy-related signaling genes, and autophagosome development in the muscle tissue of rice flower carp. Following a three-day fasting period, the levels of ROS and MDA rose. Additionally, after 3 d of fasting, there was a notable upregulation of NRF2 and significant increases in the levels of GSH and the activities of enzymes such as SOD, CAT, GST, GR, and GPX, while the expression of the autophagy marker gene LC3B did not change (p < 0.05). After 7 d of fasting, the content of the ROS, the activity of SOD and GR, and the GSH content reached the maximum (p < 0.05). Concurrently, there was a significant rise in the quantity of autophagosomes. An RT-qPCR analysis revealed that seven d of starvation significantly elevated the mRNA expression of genes associated with the initiation and expansion of autophagosome membranes, vesicle recycling, and cargo recruitment, including ULK1, BECLIN1, LC3B, ATG3, ATG4B, ATG4C, ATG5, ATG9, and P62. After feeding resumed for 3 d, the mRNA level of BECLIN1, ATG3, ATG4B, ATG4C, ATG5, LC3B, and P62 still remained at a high level. The LC3II protein reached its highest level. All autophagy-related gene expression decreased in the 7-day resumed feeding group. Our data implied that short-term fasting can cause oxidative stress and disrupt the antioxidant system first and then induce autophagy in the muscles of rice flower carp. These findings shed light on how fasting affects muscle homeostasis in fish. ROS-induced autophagy of the skeletal muscle may confer the resistance of rice flower carp to short-term fasting.

Research Progress and Production Status of Edible Insects as Food in China.

Based on the background of the exacerbating food shortage in the world, it is particularly important to diversify food resources in every possible direction. Among the choices available, edible insects have become an important alternative source of animal food with their high nutritional and functional (pharmacological) values, partially replacing normally consumed animal and livestock protein food sources. The utilization of edible insects has been an ancient custom since the dawn of civilization, attributed to their rich nutrition, alternate protein source, medicinal values, and presence of diverse secondary metabolites and alkaloids. This review provides an introduction to three key aspects of edible insects as food: freshness, long-term preservation, and medicinal value. It also provides details on the food source and products of edible insect species, their detailed nutritional composition and medicinal values, and their potential in producing alternative protein sources. Additionally, the review also encompasses rearing and producing technologies, resource utilization, and industrial development in China. Simultaneously, the problems and challenges faced in the artificial rearing and production development of edible insects, the production advantages over traditional livestock, and the farming evaluation and prospects of edible insects, as well as the lack of specific legislation on edible insects in China, are discussed. This review will be helpful in scientific knowledge propagation regarding edible insects for the public, guiding consumers to establish a diverse perception of sustainable agriculture and food sources in the world that has, as yet, been thwarted by food insecurity. Moreover, though edible insects could potentially serve as part of a commercial and industrial agri-enterprise that could generate a huge income, artificial rearing technology and edible insect product manufacturing and processing have not received sufficient attention from the government on a policy level, thereby leaving an open space for extensive research on edible insects as an alternate food source as well as an examination of the industrial prospects of edible insect products.

ჰიდრომელიორაციის ინსტიტუციური მოწყობის საერთაშორისო მოდელები და საქართველო

At the current stage of development, special attention should be focused on maximum realization of the country's food potential. It is important for Georgia to overcome food shortage, to provide the population with affordable, diverse, harmless, high-quality and sufficient food. Industrialization of agriculture and its transformation into a high-tech industry stand as guarantee that the country will meet its food requirements. In addition, it is important to take into account that not only expansion of agricultural land is limited, but on the contrary, it is even decreasing due to escalation of urbanization process. The solution lies in the high-performance use of agricultural lands and increasing of per hectare yield. There is only one way to achieve this goal – land use efficiency. In order to make full use of land and secure high yields of agricultural crops, additional human labor and agro-cultural measures are often required to give a specific soil the properties that other soils possess under the best natural conditions. Such lands require significant improvement (melioration). The proposed paper provides an analysis of the current state of agricultural hydromelioration in Georgia. Economic innovative proposals for the use of agromelioration have been developed on the basis of generalization of international best practices. This research dwells upon the experience of foreign countries from the point of view of institutional arrangement. We tried to select the countries based on the principle that the best practices of all continents should be represented. From Latin American countries, we studied the institutional arrangement of Mexico in the field of irrigation, from the European countries – the experience of Portugal, Croatia, Bosnia-Herzegovina, Montenegro, Serbia, Romania and Ukraine; on the Eurasian continent target country was Russia, in the Caucasus - Armenia, in Asia Minor - Turkey, in the Middle East - Israel, in Asia - China, South Korea and Japan, on the Australian continent – Australia proper. Such variegated selection showed us the specifics of institutional structures in different countries, despite their varying development histories and paths taken in the field of irrigation and drainage. From the point of view of institutional arrangement, several distinct classification markers have been identified, highlighting similarities between specific countries and allowing to group them according to these markers. In particular, we can group countries according to the type of institutional arrangement in terms of management - centralized or decentralized.