Crop Production Data Research Articles

Impact of Arable Land Abandonment on Crop Production Losses in Ukraine During the Armed Conflict

The outbreak of Russia-Ukraine conflict casted an impact on the global food market, which was believed to be attributed to that Ukraine has suffered significant production losses due to cropland abandonment. Nevertheless, recent outbreaks of farmer protests against Ukraine’s grain exports demonstrated that the production losses might not be as severe as previous estimates. By utilizing the adaptive threshold segmentation method to extract abandoned cropland from the Sentinel-2 high-resolution imagery and calibrating the spatial production allocation model’s gridded crop production data from Ukraine’s statistical data, this study explicitly evaluated Ukraine’s crop-specific production losses and the spatial heterogeneity. The results demonstrated that the estimated area of abandoned cropland in Ukraine ranges from 2.34 to 2.40 million hectares, constituting 7.14% to 7.30% of the total cropland. In Ukrainian-controlled zones, this area spans 1.44 to 1.48 million hectares, whereas in Russian-occupied areas, it varies from 0.90 to 0.92 million hectares. Additionally, the total production losses for wheat, maize, barley, and sunflower amount to 1.92, 1.67, 0.70, and 0.99 million tons, respectively, with corresponding loss ratios of 9.10%, 7.48%, 9.54%, and 8.67%. Furthermore, production losses of wheat, barley, and sunflower emerged in both the eastern and southern states adjacent to the conflict frontlines, while maize losses were concentrated in the western states. The findings imply that Ukraine ought to streamline the food transportation channels and maintain stable agricultural activities in regions with high crop production.

Availability and requirement of feed and fodder in different districts of Karnataka

Agriculture and livestock sectors are crucial for economic and social equity in rural areas. Livestock sector growth and fodder availability are directly related. Enhancing profitability of livestock husbandry can only be possible by ensuring adequate fodder to the livestock. A study was therefore conducted to know the feed and fodder availability and requirement at various districts of Karnataka. Secondary data of land use classification, crop production (2015 to 2019) and livestock census were used to derive dry matter (DM) availability and requirement for each district. Primary data was collected to understand the village level situation. Results indicated that state has an average of only 68.61±54.41% dry matter availability. Out of 30 districts, six districts belonged to surplus (>100%) and 12 districts belonged to severely deficient DM category with the DM availability of less than 40%. Crop residues contributed highest (69.01%) to the total DM. Contribution of total greens from all sources was found to be more in severely deficient districts. Bagalkot district had highest and Bengaluru urban had lowest DM availability. These findings are pivotal for developing fodder plan for Karnataka.

Comparison of Yield and Cost Data of Cotton Crop Production During 2019 and 2020 in Baluchistan

The study was carried out through a primary as well as secondary data collection from several stakeholders to examine the average position of cotton production, average per acre cost of production, physical and income productivity, economic profit, input output ratio, problems and constraints, faced by cotton farmers and to recommend policy measures for maintainable cotton production and marketing in study area. Statistics examines were performed by retaining the descriptive figures as well as standard economic methods. A mixture of qualitative and measurable methodical procedures such as cost of production, market limits, regression analysis, cross tabulation analysis were carried out. The study was carry out in Lasbella, Sibi, Noshki, Turbat, Dera Bugti and Khuzdar districts in Balochistan. The data were gathered from 77 farmers of cotton growers and collected material was related to cotton production in Kharif 2019 and 2020. Majority of cotton growers were small land holders and age was 48.33 years. The average seed rate was 10.50kgs/acre and purchasing price was Rs.344.33/kg during 2019 & 2020 correspondingly. The budget of production was Rs.91762.50 and total revenue was Rs. 192297.5 per acre in 2020 respectively. The average profit/net income of cotton growers received was Rs. 100535 and Rs.95225.77 per acre in 2020 and 2019 respectively.

Assessing the Current Status of Vietnam's Coffee Exports in the Period 2014-2023 in the Global Coffee Value Chain

Vietnam has favorable geographical location and weather to grow and develop robusta coffee varieties. Vietnam's production area is more than 95% of robusta coffee output out of a total planting area of 600,000 hectares. In 2022, coffee productivity will reach about 28.2 tons/1 hectare, reaching the highest level since 2005, according to Department of Crop Production data. The robusta coffee variety in Vietnam is also considered the best coffee variety in the world. Therefore, according to statistics from the Vietnam Commodity Exchange, in 2023, Vietnam will be the country with the world's highest robusta coffee export value, accounting for 36% of the total global coffee export value, followed second by Brazil with 28%. In 2021, Vietnam ranks 5th globally, with coffee exports reaching 2.35 billion USD. In 2022, Vietnam exported 1.68 million tons of coffee, but the turnover reached only about 3.9 billion USD. Of these, 82% of Vietnam's coffee is exported raw (mainly Robusta), valued at 2.9 billion USD. In contrast, the export turnover of Arabica coffee is only 260 million USD for decaffeinated coffee. 76.9 million USD and roasted, ground-illat coffee worth 598 million USD. Colombia and Switzerland have a small amount of coffee exported, but the value is high thanks to the quality and coffee brands that the country has built. Vietnam's coffee exports set a new record with a turnover of 4.24 billion USD in 2023. Just past the beginning of the new year, Robusta coffee prices continue to record many new peaks. With this advantage, the coffee industry has a solid foundation for its export goal in 2024.

Rate of desertification, climate change and coping strategies: Insights from smallholder farmers in Ghana's Upper East Region

Climate change and desertification are global issues that are affecting agricultural activities in Sub-Saharan Africa. These phenomena have made it challenging for smallholder farmers to cope with the emerging global food crises. This article examines the evidence of desertification and climate change and how smallholder farmers in the Upper East Region of Ghana are responding to these threats. Primary data was analysed through interviews and focus group discussions. We used Landsat satellite-based annual mean Normalized Difference Vegetation Index, climate, crop production data, and reports from the Ministry of Food and Agriculture and other NGOs as secondary sources. We interviewed eighty respondents using case history and snowball sampling. The mean annual NDVI declined from 0.5 in 1998 to −0.10 in 2022. NDVI values suggest a decline in green vegetation health to a negative value, suggesting a non-vegetative surface. This means that the process of desertification has progressed to severe levels, resulting in little to no vegetation cover on the land surface. Similarly, rainfall data suggests a sharp decline in annual rainfall while farmers change the types of crops and the timing of planting. Farmers discussed the impact of climate change and desertification on their livelihoods. They have implemented approaches like using synthetic fertilisers, planting drought-resistant crops, practising dry-season farming, irrigating their crops, and building social support networks. Food insecurity and land degradation are major issues due to continuous cropping and population growth. Smallholder farmers suggest providing them with affordable, drought-resistant seedlings with shorter gestation periods to increase food production and avoid insecurity.

Larger nations benefit more than smaller nations from the stabilizing effects of crop diversity.

Crop diversification is increasingly recognized as a strategy to stabilize national food production, yet the benefits of this approach may vary across nations due to the scale dependence of crop diversity and stability. Here we use crop production data from 131 nations from 1961 to 2020 to explore the spatial scale dependence of the crop diversity-stability relationship. Drawing on ecological theory and complementary analytical approaches, we find that as the total national harvested area increases, yield stability increases. Crop diversity stabilizes national yield stability, as does an increase in the number of farms, but these stabilizing effects are weaker in smaller countries. Our findings suggest that enhancing crop diversity at the national level may not provide a de facto universal strategy for increasing yield stability across all countries-with implications for national strategies promoting crop diversification to protect against food system shocks.

Large-scale spatially explicit analysis of carbon capture at cellulosic biorefineries

The large-scale production of cellulosic biofuels would involve spatially distributed systems including biomass fields, logistics networks and biorefineries. Better understanding of the interactions between landscape-related decisions and the design of biorefineries with carbon capture and storage (CCS) in a supply chain context is needed to enable efficient systems. Here we analyse the cost and greenhouse gas mitigation potential for cellulosic biofuel supply chains in the US Midwest using realistic spatially explicit land availability and crop productivity data and consider fuel conversion technologies with detailed CCS design for their associated CO2 streams. Optimization methods identify trade-offs and design strategies leading to systems with attractive environmental and economic performance. Strategic and operational decisions depend on underlying spatial features and are sensitive to biofuel demand and CCS incentives. US CCS incentives neglect to motivate greenhouse gas mitigation from all supply chain emission sources, which leverage spatial interactions between CCS, electricity prices and the biomass landscape.

Is the boom in staple crop production attributed to expanded cropland or improved yield? A comparative analysis between China and India

The characteristics of cropland development and the dynamics of food production in China and India, the world's largest agricultural and most populous countries, are of great importance to global food security. However, there is a notable lack of a thorough comparison between China and India in this regard. Here, we systematically compare the differences between China and India using cropping intensity and crop production data, including cropland area, harvested area, total staple crop (i.e., cereal crops, tuber crops and pulse crops) production and yield capacity. The results are mainly as follows: (1) Both China and India experienced an increasing trend in cropland area and harvested area from 2001 to 2021, especially notable in India. In China, the cropland area and harvested area increased by 11.76 % and 14.36 %, respectively, while in India, they witnessed a more substantial increase of 31.10 % and 49.32 %, respectively. (2) The cropping intensity underwent significant transformations, primarily shifting between non-cropland, single-cropping, and double-cropping. Northwestern China exhibited a clear trend of non-cropland converting to single-cropping, whereas northeastern China showed a distinct pattern of single-cropping changing to non-cropland. The interconversion between single-cropping and double-cropping was also frequently observed in the main food-producing regions. In India, the cropland expansion and the adoption of double-cropping are highly pronounced, extending widely across most of the country. (3) From 2001 to 2021, the total staple crop production in China and India increased by 34.12 % and 55.81 %, respectively. Despite the rapid growth in India's total staple crop production, it still amounts to only about half of China's. The major crops production also showed different trends, China's cereal crops production increased significantly, while tuber and pulse crops production declined, and India's production of cereal, tuber, and pulse crops has all increased (4) China's yield capacity has increased by 17.28 %, while India's has only grown by 4.35 %. Despite the rapid increase in India's total staple crop production, the yield gap with China has widened. The boost in China's total staple crop production mainly resulted from improved yield capacity, whereas India relied more on the cropland area expansion, especially the increase in harvested area. Our comprehensive comparison of China and India in cropland development and staple crop production contributes to a deep understanding of the differences in agricultural production between the two countries, and provides lessons for global food security and sustainable agricultural development.

Soil quality evaluation for irrigated agroecological zones of Punjab, Pakistan: The Luenberger indicator approach

AbstractThis article describes the construction of the Luenberger soil quality indicator (SQI) using data on crop yield, non‐soil inputs, and soil profile from three irrigated agroecological zones of Punjab, Pakistan, namely, rice–wheat, maize–wheat–mix, and cotton–mix zones. Plot level data are used to construct a soil quality indicator by estimating directional distance functions within a data envelopment analysis (DEA) framework. We find that the SQI and crop yield relationships exhibit diminishing returns to improving soil quality levels. Using the constructed SQI values, we estimate linear regression models to generate weights that could be used directly to aggregate individual soil attributes into soil quality indicators without the necessity of fitting a frontier to the crop production data. For wheat and rice production, we find that SQI is most sensitive to changes in soil electrical conductivity (EC) and potassium (K). The SQI has direct relevance for site‐specific decision‐making problems where policymakers need to price land resources and conservation services to achieve agricultural and environmental goals.

Manure nutrient cycling in US animal agriculture basins-North Carolina case study.

Nutrient cycling in crop-animal production is impacted by changes in both systems, with imbalance hotspots in concentrated animal production regions severely impacting water quality. This study assesses manure-crop nutrient balances in five river basins in North Carolina and demonstrates a new approach for partial nutrient balances along hydrological boundaries. County-level crop production data were combined with crop-type spatial distribution data to derive spatially referenced nutrient uptake and removal. Similarly, spatially referred animal production inventory data were used to derive excreted and recovered manure nutrients. Partial nutrient balances were developed for both N and P in basins and hydrologic units. Excreted manure N and P were 139% and 159% of respective plant N and P removal at harvest across the five basins. Finer geographical scales revealed hotspots for manure surplus, particularly within the Cape Fear basin (up to 96% N and 97% P). Despite N hotspots, plant-available manure N met only 38% of crop N demand due to significant losses during storage. Plant-available manure P exceeded crop P removal by 54% over the entire area. Cape Fear showed the greatest P excess, 76% greater than crop removal. This study contributes to nutrient cycling improvements by connecting crop-animal nutrient budgets to hydrologic resources. Furthermore, we show the value of finer spatial scales to identify hotspots that play a significant role in nutrient losses. We conclude that nutrient-surplus basins require, in addition to manure nutrient conservation, a basin-wide redistribution and export strategies to address nutrient excesses and water quality impacts.

ANALYSIS OF RICE CROP PRODUCTION CHANGES DUE TO LAND USE CHANGES IN BAGIK POLAK VILLAGE, LABUAPI SUBDISTRICT WEST LOMBOK REGENCY

Bagik Polak Village is located in Labuapi District, West Lombok Regency. Its area is 2.50 km2 with 7 sub-villages and a population of 4,232 people and a population density of 1,693 people/km2. Geographically, Bagik Polak is located at coordinates 8037'39" S 116007'57" E. Agricultural activities such as planting rice, corn, horticulture, and livestock, are mostly carried out by the community to meet the needs of life. However, in the last 10 years, there has been a change in the function of agricultural land to non-agricultural land. An increase in population causes this, the dynamics of development and industrial development, which require space, so it has implications for changes in land use. The purpose of this study is to analyze changes in rice crop production based on land use changes in Bagik Polak Village from 2012 to 2022. The method used in this study is the evaluative descriptive method. Data processing and analysis is carried out using ArcGis 10.8, while the stages include geometric correction, image interpretation, calculating the digitized area and field observation. The data used are Google Earth Pro satellite imagery data from 2012-2022 and rice crop production data from 2012-2022. The analysis results show that changes in the use of agricultural land into settlements and housing are the most significant changes. In 2012 the area of agricultural land was 189.51 Ha with rice production of 11.867813 quintals. However, in 2022, the area of agricultural land decreased to 168.32 Ha with rice production of 11.571725 quintals. The average rate of shrinkage of rice crop production is -0.854782108. The land conversion is the main factor causing the decline in rice crop production in Bagik Polak Village. A correlation was found between changes in agricultural land use and a decrease in rice production in Bagik Polak Village, where changes in land use were directly proportional to a decrease in rice production

Utilization of Machine Learning Algorithms for Precision Agriculture: Enhancing Crop Selection

Agriculture stands as a crucial economic driver, playing a pivotal role in fostering economic progress. Understanding the dynamics of the agricultural system is imperative for ensuring food security. Even as technological strides like vertical farming emerge, conventional farming practices and beliefs continue to hold sway. This study delves into fundamental aspects such as soil composition, pH levels, humidity, and rainfall, employing a range of machine learning models including kernel naive Bayes, Gaussian naive Bayes, linear support vector machine (SVM), quadratic discriminant analysis, and quadratic SVM. The primary objective is to provide insightful crop recommendations to farmers. Accurate crop forecasting is paramount for optimizing agricultural methodologies and maintaining a consistent food supply. By leveraging historical weather trends, soil quality, and crop production data, machine learning algorithms proficiently anticipate crop yields. The outcomes of this investigation have the potential to refine crop management practices and reinforce food security measures.

A Study on Analyses of the Production Data of Feed Crops and Vulnerability to Climate Impacts According to Climate Change in Republic of Korea

According to the climate change scenario, climate change in the Korean Peninsula is expected to worsen due to extreme temperatures, with effects such as rising average temperatures, heat waves, and droughts. In Republic of Korea, which relies on foreign countries for the supply of forage crops, a decrease in the productivity of forage crops is expected to cause increased damage to the domestic livestock industry. In this paper, to solve the issue of climate vulnerability for forage crops, we performed a study to predict the productivity of forage crops in relation to climate change. We surveyed and compiled not only forage crop production data from various regions, but also experimental cultivation production data over several years from reports of the Korea Institute of Animal Science and Technology. Then, we crawled related climate data from the Korea Meteorological Administration. Therefore, we were able to construct a basic database for forage crop production data and related climate data. Using the database, a production prediction model was implemented, applying a multivariate regression analysis and deep learning regression. The key factors were determined as a result of analyzing the changes in forage crop production due to climate change. Using the prediction model, it could be possible to forecast the shifting locations of suitable cultivation areas. As a result of our study, we were able to construct electromagnetic climate maps for forage crops in Republic of Korea. It can be used to present region-specific agricultural insights and guidelines for cultivation technology for forage crops against climate change.

Crops Productivity in a Changing Climate: Adaptation Strategies for Farmers Resilience in Pakistan

Climate change poses a significant threat to agricultural productivity, especially in regions with vulnerable economies such as Pakistan. This research article aims to explore the multifaceted impacts of climate change on crop yields within the country. By analysing historical climate and crop productivity data of 1977-2016 through the ARDL technique, the study identifies trends and patterns that suggest a strong correlation between climate change and fluctuations in crop productivity. Our findings highlight the need for climate-resilient crop development, improved agricultural technology, and the necessity for adaptive agricultural practices and robust policy interventions to reduce the adverse effects of a changing climate on crop productivity Furthermore, the potential of emerging technologies and farming techniques to enhance resilience in crops production, ensuring a crops supply for Pakistan's growing population.

Trends and impacts of climate change on crop production in Burkina Faso

Abstract Understanding past climate trends and their impacts in the Sahel region is fundamental for climate change (CC) adaptation and mitigation. This study analyses climate trends from 1961 to 2020 in three climatic zones in Burkina Faso and the impacts of CC on five major crops production. Long time series of daily rainfall and temperature data from National Meteorology Agency for the period 1961 to 2020 has been compiled. Crop production data (1984–2020) were retrieved from the agriculture department. Climate temporal variations in each climatic zone were analyzed using extreme climate indices and principal component analysis. Linear regression was used to assess climate impacts on crop production. The results showed a high rainfall variability and changes in temperature extremes in the three zones. The climate window, 1991–2020, was hotter than 1961–1990, while the last decade (2011–2020) was the wettest. Most climate indices (67%) showed significant correlations with crop yields. Dry spells, cool days, cold nights, average daily wet days and rainfall intensity showed positive and negative effects on maize, cowpea, millet and sorghum yields. This study highlights the importance of climate-smart policy promoting drought-resistant and short-duration varieties in addressing the adverse effects of CC on crop production.

Oracles Integration in Blockchain-Based Platform for Smart Crop Production Data Exchange

Blockchain oracles are an intermediary designed to connect external non-deterministic information and real-world data to the blockchain digital infrastructure. The variety of proposed solutions and purposes are of great variety and suggest that it is necessary to take into account different features of the process and specifically define the required functionalities. The purpose of this paper is to present the integration of oracles into an EOSIO blockchain-based platform for smart crop production data exchange by smart contracts. The functions of two oracles are presented. Their integration is described at the design level and at the implementation of the smart contracts. The design level is illustrated by workflow diagrams of internal processes between oracle applications and the blockchain smart contract and by external processes in the oracles’ smart contracts. The implementation level is illustrated by oracle application configuration files and elements of C++ smart contracts, such as constant and variable declarations, multi-index tables, internal contract functions, and actions called by other contracts and external programs. As results of the oracles’ operation, a report on the detected emergency failures and an estimate of the cost of ram resource are presented.

IOT-BASED professional crop recommendation system using a weight-based long-term memory approach

For the vast majority of Indians, agriculture is their main source of income, and it plays a vital role in the country's economy. The most prevalent issue Indian farmers have is that they do not choose their crops based on the requirements of the soil, which has a significant negative impact on their productivity. Precision agriculture can help solve this problem. This method considers three parameters: soil characteristics, soil types, and crop yield data collection. A suitable crop to cultivate is suggested to the farmer based on these parameters. However, India must develop and civilizes the agro industry's technological engagement and usability. Due to the inability to select acceptable features, the existing system's accuracy is low, and it takes longer to process the given climate dataset. This paper proposes a method based on IDCSO (Improved Distribution-based Chicken Swarm Optimization) with WLSTM (Weight-based Long Short-Term Memory) for crop predictions and recommendations in order to address the aforementioned issues with the help of the Internet of Things (IoT). The primary phases are pre-processing, attribute selection using the IDCSO algorithm, and crop prediction using the WLSTM method. First, climate data are collected, then crop production data. For this study, the climate data includes a number of variables responsible for the rainfall at a given location and the agricultural yield in that region. Then, pre-processing is performed to enhance the quality of the input. To provide precise prediction results with shorter execution times, the IDCSO algorithm is utilized to choose the most helpful features. The most pertinent features from the provided dataset are chosen using the optimal fitness values. The required crop predictions are then performed using the WLSTM approach. Farmers can get instant crop recommendations by entering their preferred climate and crop attributes. The experimental findings show that in terms of precision, recall, and execution time, the suggested IDCSO-WLSTM technique performs better than its forerunner.

ШЛЯХИ ПІДВИЩЕННЯ ЕКОНОМІЧНОЇ ЕФЕКТИВНОСТІ ІНТЕНСИФІКАЦІЇ ВИРОБНИЦТВА ПРОДУКЦІЇ РОСЛИННИЦТВА ПОВОЄННОГО ЧАСУ

The purpose of the research is to conduct a detailed scientific and practical substantiation of the ways to increase the economic efficiency of the intensification of the production of plant products in the post-war period. The research used general scientific (generalization, comparison, induction and deduction) and empirical-theoretical methods (analysis, synthesis). The use of system-structural and statistical analysis made it possible to distinguish the main statistical data of crop production. It was established that almost a quarter of the industry was lost in agriculture, and direct losses as a result of the 9-month war reached 6.6 billion US dollars, and indirect losses - 34.5 billion US dollars. It was established that at the end of 2021, there was an increase in production in agriculture (the index of agricultural products increased by 14.4% compared to "minus" 10.1% in 2020) due to significant growth in crop production. It was found that in order to intensify the production of plant products, it is necessary to increase the production of agricultural crops due to the use of more arable land or to increase production on existing arable land by increasing the yield or intensity of crops by improving management methods and genetics. It has been established that the priority tasks in the agricultural sector are to bring the track width and rail cars of Ukraine into compliance with EU standards; increasing the capacity of grain bunkers in Ukraine according to the EU standard; providing Ukrainian farmers with seed, fertilizers, fuel, generators and agricultural machinery; formation of safe working conditions (demining of cultivated areas); maximum sowing of agricultural crops in safe regions of the country; the use of innovative technologies in the production and storage of agricultural crops. The results of the research can be used in the process of studying the scientific field "Agrarian Sciences". The results can be aimed at increasing the economic efficiency of the intensification of the production of crop production in the post-war period.

Bioenergy potential of agricultural crop residues and municipal solid waste in Cameroon

<abstract> <p>Biomass has emerged as an important and promising energy source, particularly in developing countries, owing to continuous research for sustainable energy sources that do not interfere with food, water or land needs. This study introduces the surplus availability factor (SAF), minimum, average and maximum biogas production technique in the assessment of crop production data in 2020 to provide a more precise and current estimate of Cameroon's crop residue and municipal solid waste (MSW) bioenergy potential. Crop residues contributed roughly 96% while MSW contributed the remaining 4% of the total bioenergy potential of 606 PJ per year. The bioenergy potential was calculated using crop production statistics derived from the FAOSTAT database of the Food and Agriculture Organization, while the residue-to-product ratio (RPR) and surplus availability factors (SAF) were found from related studies. The study concludes that crop residues and MSW have significant energy potential capable of meeting the country's electricity, transport fuel and biogas demand while simultaneously mitigating climate change through the capture of about 1.6 billion kg of CO<sub>2</sub> through biogas recovery. It also highlights the lack of accurate and up-to-date data on the country's biomass potential and recommends ground data collection and geospatial mapping of areas with enormous potential for these resources to guide policymakers and investment plans.</p> </abstract>

A GIS-based interactive map enabling data-driven decision-making in Nigeria's food supply chain

The accessibility of open-source data on fresh food supply chains provides key stakeholders from the public and private sectors with insights for better decision-making to drive food loss reduction. Nigeria has a fair amount of open-source agricultural and climate-related data. However, most of these datasets are not readily accessible. This paper presents a detailed method used to develop an interactive web Geographic Information System (GIS) tool that collates and visualizes available open-source datasets on Nigeria's Agricultural Sector with particular focus on the fresh produce supply chains. The following steps were used to create such an interactive map.•Open-source data were acquired in various forms, including tabular, vector, and rasters, processed and uploaded as layers on the interactive web map.•Most of the data needed some processing on open-source geographic information system applications and web-based computing platforms to transform them into sources of actionable insights•These final processed layers were then uploaded to a consolidated interactive web map built on the Google Earth Engine platform.The gathered open-source data includes crop production data, market prices, weather, road network, market locations, mobile coverage, water access, water scarcity, and food insecurity. The method described here also allows the reproduction of such maps for other countries.