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Romania ranks first in the European Union for the production of sunflower seeds, third for the production of soybeans and seventh for the production of rapeseed. The paper aims to analyse the effects produced by the COVID-19 pandemic on the evolution of the oilseed sector in Romania. Thus, the following indicators were analysed: evolution of areas under oilseeds, total oilseed production and average yields, as well as the volatility of selling prices for oilseeds. The results of the study reveal that Romania has been the largest producer of sunflower seeds in the European Union. The average yields in sunflower, soybeans and rapeseed have shown great variations in the analysed period. According to Eurostat data, it can be noticed that although Romania is the third large producer of oilseeds in the EU, the average yields continue to be low compared to those from other large EU producers. Yields are also among the most volatile in the EU. The selling prices for soybeans showed a higher increase in the year 2020 than in 2019 in Romania, compared to the increase in the average selling prices of the EU-27 (+9.89%). The selling prices for rapeseed also had a higher increase in 2020 than in 2019 in Romania, compared to the increase in the average selling prices of the EU-27 (+2.31%).
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Climate change events and the COVID-19 pandemic have brought to focus the significance of cassava as a supplementary food crop worldwide. However, the high yield potential of the crop necessitates timely and adequate enrichment of the soil with nutrient inputs. Consortium biofertilizers offer a viable option for reducing intensive fertilizer use to sustain soil health and productivity in cassava. The efficacy of a liquid consortium biofertilizer, specifically a plant growth-promoting rhizobacteria (PGPR) Mix - I, in economizing nutrient use in cassava was evaluated in a 4 x 3 factorial randomized block design, replicated thrice. The treatments consisted of combinations of four levels of biofertilizers and three levels of nutrients. Biometric and yield observations were recorded, and soil properties were analyzed before and after the harvest of the crop. The results showed that the liquid biofertilizer consortium at a concentration of 5% + 75% of the recommended dose, with 37.5:37.5:75 kg NPK/ha as chemical fertilizers, recorded significantly superior tuber yield in cassava. Considering the economics, the application of the PGPR liquid formulation (5%) thrice (basal, 2 and 4 MAP) along with 37.5:37.5:75 kg NPK/ha, or at a concentration of 2% with 50:50:100 kg NPK/ha, realized higher benefit-cost ratios and can be recommended for use in cassava.
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This paper presents the evaluation results of the yield target setting precision of the revised MOET App (v.2.0), following the inclusion of the correction factors generated from rice biomass correlations between MOET and nutrient omission plot setups obtained from 2017 to 2018. The project started with trainings on MOET kit and MOET App use for the seed production personnel across PhilRice stations in Nueva Ecija, Negros, Bukidnon and Agusan in 2018 DS. Included in the trainings were the establishment of MOET kit tests and generation of variety- and site-specific recommendations via the MOET App for several nationally or regionally recommended varieties (NSIC Rc 122, 160, 216, 218, 222, 238, 286, 300, 358, 402, 436, 440, 442, 480, PSB Rc18 and PSB Rc82) that each PhilRice station intended to produce in the succeeding 4 cropping periods from 2019 to 2020. Relative yield advantages and economic benefits from using the MOET App fertilizer recommendations over PhilRice' current fertilizer management in seed production per station were monitored every cropping while the precision evaluation of yield target setting was done after the last cropping of 2020 WS. In 2019, relative yield advantages averaged 0.43t ha-1 in DS and 0.25t ha-1 in WS. In 2020 DS, an average relative yield advantage of 0.63t ha-1 was obtained across stations and 0.93t ha-1 in 2020 WS in Nueva Ecija only due to travel restrictions brought about by the COVID-19 pandemic. Economic benefits of using the MOET App showed an average of 0.50t ha-1 and 0.65t ha-1 yield increase over the seed production units' fertilizer management in DS and WS, respectively. While savings in fertilizer cost were better realized during the WS at an average of Php 4,126.34 ha-1 season-1 across stations. Results of the precision evaluation of the yield target showed marked improvements with a 95.24% probability of achieving 17% higher grain yields than the target set by MOET App v.2.0. However, the overall normalized Root Mean Square Error (nRMSE) of 38.14% exceeded the range for a fairly acceptable fit with the model due to large gaps between target and actual yields obtained from DS field trials.
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The agricultural sector must receive serious attention today since it faces many challenges such as the small size of land ownership and the low interest of the younger generation for doing this business. Various efforts have been made, including the agricultural technology park program and other programs for increasing production and farmer welfare. All those agricultural programs need to be supported by technology and model to get properly development. This study aims to increase the productivity and income of farmers in the agricultural development area. The research activities include potentials and problems of farm identification by a Forum Group Discussion and research implementation using a factorial randomized completely block design with four new high yield varieties and one existing variety. The results showed that farmers were very enthusiastic and responsive to the use of new high yield varieties which combined with Jajar Legowo Super technology. The highest yields in the first and second planting season were consistently reached by Inpari 30 variety. It was carried out both in Batui and South Batui District and there was an increase in production around 1.7-2 t/ha. Crop yields and farmers' incomes have increased. The guidance and assistance for farmer groups has not shown best results, however, collaboration between the breeder group and the off taker (PT Pertani) has been formed, while the development of premium rice has not been optimally implemented due to the COVID-19 pandemic.
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Rapid population growth, natural and man-made factors (COVID-19 and the lack of a social safety net) have led to an increase in the demand for food, which calls for significant improvements to the food system worldwide to supply food more efficiently with the same or fewer resources. Potatoes have great potential to contribute to food security and incomes for rural smallholder farmers, as well as provide nutritious, affordable food for urban consumers. The availability of disease-free and certified seed potatoes of better-performing varieties remains limited. The use of tissue culture to provide a disease-free seed potato is therefore crucial to ensuring food security. A key goal of this paper is to summarize the work done on various aspects of seed potato multiplication, and how it can improve the food security of smallholder farmers. The systematic review method was applied to summarize how tissue culture application can produce excess disease-free seed potatoes to improve food availability for marginal farmers. The most effective way for farmers in developing countries or areas prone to natural or man-made disasters to increase their incomes and improve nutrition is to use high-quality certified seeds. Tissue cultures are used worldwide to produce pre-basic, virus-free seed potatoes. Early Generation Seed (micro-tubers, cuttings and mini-tuber), multiplication of mother plants and production of apical rooted cutting for seed production for field planting are popular. The activities of diseases-free seed production start at the laboratory and end at the field with seed production for planting. In general, three major steps were used in seed potato multiplication: (1) Tissue culture (to produce disease-free tissue culture plantlets);(2) Production of cuttings (involves two important stages: (i) multiplication of mother plants and (ii) production of apical rooted cutting for planting) for further multiplication and (3) production of seeds for field planting.
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Aeroponics is a particular soilless or hydroponic cultivation technique used in greenhouses and in indoor farms. The technical characteristics of aeroponic systems and their advantages, which has recently aroused new interest from the commercial sector, are summarized here.
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The COVID-19 influenced global pandemic severely affected the market of small industries and had a deep impact on the agri economic of the farmer community across the globe. The main objective of this article is to emphasize on the influence of global pandemic with agriculture and food sector. The lockdown made ambivalent in agriculture, the point of concern is that, at the first phase of lockdown in India, Rabi crops are at harvest stage, due to the lockdown the breakdown of supply chain has been interrupted and left a noticeable impact on the marketability of agriculture crops even though it has registered moderate growth in terms of yield. At present globally mankind is experiencing the waves of pandemic and it caused significant loss to the yield of crops. If the situation continuous, the world is going to experience the hunger deaths. To overcome the issue discussed, agriculture sector needs to adapt new technologies, right from the cultivation, harvest and supply chain with marketing to bring the new normal life back to mankind. This is the right time to have transition from conventional agri practices to the technology invented smart agriculture. Indian agriculture sector should adapt and the former community need to be educated in applying ICT based smart agriculture practices such as utilization of automated machinery, AI (artificial intelligence) enabled cultivation methods, Internet of Things (IoT) and Wireless Sensor Networks based monitoring and maintenance of the agriculture practice. The application ICTs methods in agriculture practices facilitate to choose good quality seeds, optimum quantity of manures required for the enhanced crop yield and direct monetary of the agriculture firm in order to show resilience to the global pandemic impact on agriculture sector. In the present review authors emphasised on various smart agriculture methods and their importance in promoting the agriculture practice as profitable venture and also how this ICT methods helps the sector to overcome the impact of global pandemic and to bring back the new normal life. © 2023,International Journal of Advanced Computer Science and Applications. All Rights Reserved.
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This paper characterises South African sugarcane production for the 2021/22 milling season, from an agricultural perspective, to enable the industry to evaluate recent production strategies, and to identify priorities for improved efficiency. The industry's cane and sugar production during the 2021/22 season was 17.2 and 1.84 million tons, respectively. These figures show a marked drop of 5.6% for cane and 8.7% for sugar, when compared to the production figures for the 2020/21 season. The estimated industry average cane yield and quality also decreased slightly, compared to the previous season, but the main reason the drop in cane and sugar production was the limited milling capacity at several mills in KwaZulu-Natal. The civil unrest in July 2021 exacerbated the situation, causing disruptions to harvest and mill operations, as well as the subsequent closure of mills in parts of KwaZulu-Natal. The area harvested decreased considerably from an estimated 254 028 ha in 2020/21 to 241 030 ha in 2021/22 while estimated carry-over cane area increased from 24 029 ha to 32 476 ha over the same period. Rainfall was generally well above the long-term mean and well-distributed in most areas, while irrigation water supply also improved remarkably, compared to 2020 supply. Low temperatures and reduced sunshine duration caused yield reduction in the northern irrigated areas, but most rainfed areas experienced yield improvements when compared to 2020/21, because of the good rainfall. The Midlands region experienced severe frost damage during the winter of 2021, which had a negative impact on cane yield and quality. The Sugar Industry Value Chain Master Plan continued to help stabilise local sugar demand as well as reduce imports and exports at low world market prices, which all contributed to a 6% increase in the Recoverable Value (RV) price. This improved profitability for both largeand small-scale growers. COVID-19 had no noteworthy impact on sugarcane production.
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In the Republic of Kazakhstan melons and gourds are produced mainly in the traditional way, that is, by using chemical fertilizers and pesticides. The production of environmentally friendly melons is at the initial stage of its development. There is no organic melon growing at all. Considering the huge export potential of melons among other crops cultivated in the country (the total supply of melons and melons on the domestic market is 472%), the great economic and social significance of the transition of the melon industry to organic production is growing. In the future, Kazakhstan may be in the center of attention of the world community as a manufacturer and supplier of environmentally friendly (organic) melons, and environmentally friendly, natural melons may well become a brand of our sovereign state. To do this, it is necessary to make fundamental changes in the melon industry of the country. In general, the transition of agricultural production to an organic direction will contribute to the consumption of the safest and most useful products by the local population. Here, one should also take into account the decrease in the immunity of the human body due to various diseases, including those associated with the coronavirus pandemic. It should also be taken into account that only a limited number of pesticides used against harmful objects in agriculture act as intended, and most of the toxic substances spread into the environment. The use of disinfectants without scientific support has a negative impact on flora and fauna, being deposited in the soil and irrigation system of fields for a long time, thereby causing enormous damage to the environment. Given the above facts, our scientific research was aimed at the selection of pesticides and biological preparations with high biological and economic efficiency, low rates and frequency of treatments, as well as varieties with high resistance to fungal diseases of melons (watermelon, melon). Research work was carried out on the experimental plots of the Regional Branch "Kainar" of the LLP "Kazakh Research Institute of Horticulture" in the period 2020-2021. The studies used classical methods generally accepted in melon growing. The results obtained are new and relevant, and in the future, will contribute to the transition from traditional melon growing to biological.
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Rice production and research have met unprecedented challenges in recent years. Yield and total production have plateaued for many years in some major producing rice-producing countries while the demand from populations in poverty is ever increasing. For example, more than 100 million additional people became extremely poor, mostly from Asia and sub-Saharan Africa in 2020 alone. Rice is not only the calorie source for half of the global population but also the key staple food for the world's poorest and undernourished people living in Asia and Africa. In this review, we have analysed the trends in rice research in the past three decades, particularly on the mega-projects that attempted to revolutionize rice yield, sustainability and quality of both Asian (Oryza sativa) and African (O. glaberrima) rice, with their impact on rice cultivation. We have also analysed the trends in population growth, rice cultivation, production, price and consumption along with their projections for 2030 and beyond. Furthermore, we have analysed recent trends in variety release using Bangladesh as an example. Finally, we have identified the future challenges and priorities of rice research.
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The market for biostimulants is rapidly growing and many companies are expanding their portfolio with the introduction of these products, which are increasingly used to improve the management of crop systems and increase their sustainability. In fact, biostimulants, if properly used, can increase crop yields and quality, reducing fertilizer inputs and increasing plant tolerance against abiotic stresses.
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The main problem of this research is decreasing of agricultural labor wages during the study period 2007-2020 which is reaching about 11.05 thousand pounds in 2020 compared to the agricultural wages of workers in 2007, which contributes about 17.87 thousand pounds, while the worker's wages are increased in The construction sector (as an alternative sector of the agricultural sector) during the study period, so the migration of workers from the agricultural sector to the construction sector is increased, and according to previous, the crop intensification rate is decreased during the study period (especially in the second period) due to decreasing the unit of farm area due to Encroachment on agricultural lands and increasing the inflation rate, and agricultural investments are decreasing in the agricultural sector, and consequently the percentage of agricultural GDP to total GDP is decreasing from 14.10% in 2007 to 12.10% in 2020. So this study aims to study the most important economic variables affecting on the size of agricultural labor during the study period (2000-2020).by dividing the study to two periods 2007-2013, and 2014-2020, and compare with them by (T test) and estimating growth rate, using multiple regression models to identify the most important variables which was affecting on the size of agricultural labor. Simple regression models were also used to estimate the powers function and write it in its linear form [double logarithmic], after testing data stability by the unit root test using the Augmented Dickey-Fuller test (ADF), and processing them before estimating And the graphical signature of the correlation coefficients of these variables to determine whether they are inactive [correlogram] to know if the model was suffering self- correlation problem or not before obtained the results. It was shown from results that: (1) The economic and social changes which were followed by the political events which were happened in the first period of the revolutions (January 2011, June 2013) were never in the interest of agricultural labor, so government should reconsider the set of procedures and policies that would restructure agricultural activity to ensure Stability in the situation of agricultural labor, especially seasonal labor, and benefiting from skilled labor from it, which led to have decreasing agricultural labor wages.(2) It was also found that the average percentage of total contribution Agricultural wages in relation to the total variable production costs of the most important strategic crops under study account for a large proportion of the total variable costs by up to 50%. Because of increasing inflation rate, which was affecting on high prices of agricultural commodity, production inputs. and the policy of floating the Egyptian pound that is not commensurate with the prices of agricultural crops, also the economic impact of Covid 19 on the most important of strategy crops to variable costs during the first period average 2007-2013. This led to rising labor migration from the agricultural sector to other sectors. (3) By studying the most important factors affecting on size of agricultural labor, it was found that there is a positive and significant relationship between the size of agricultural labor (in million workers) and total agricultural investments (million pounds). Which means that the increase in the agricultural of labor productivity leads to decreasing the numbers of labor, because of the decision of the investor or producer to dispense with the extra labor because the existing labor maintains the same amount of output. (4) The increase in the state's tendency to export and economic efficiency over the marginal propensity to import in the second period 2014-2020 and the decrease in the state's desire to import, in contrast to the first period, which is characterized by a high marginal propensity to export and import.
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Intercropping is considered to be a fundamental tool for ensuring agricultural sustainability and productivity, a matter of major importance in the specific context of the last decades and, mainly, the last two years. Within European agriculture, conventional advantages of intercropping system following laborious experiments were disregarded by farmers because of the justified goal of maximizig profits using affordable pesticides on the market. This determines farmers to focus on increasing the size of their farms, replacing manual labor with a mechanized one, resulting a technological specialization of a few crops at the expense of biodiversity. However, nowadays, following the Covid-19 pandemic and the entire chain of effects it generated, agriculture was directly affected due to the limitation of worldwide transport amplitude and the scarcity of products and raw materials that arose, the price for some of them becoming trully prohibitive (to be seen the case of chemical fertilizers at the end of year 2021). The present paper aims to highligh some paramount matters of using intercropping systems in vegetable crop practice, regarding the perspective of soil, environment, ecosystem biodiversity and economical sustainability.
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For sustainable food production. In agriculture, crop yields are increasingly affected by warmer temperatures, and pest infestations caused by climate change have increased agricultural losses. Increasing local production is important to reduce our dependence on imported food and provide a buffer in case of supply disruptions such as those caused by the COVID-19 pandemic. To increase food security, it is important to optimize agricultural yields, despite the high costs associated with factors such as supplemental feeding, pest control measures, or operating costs. We present a Machine Vision method (MV) with Adversarial Autoencoder (AAE) as an approach to crop yield optimization. Predicted leaf area is projected from initial germination to early vegetative stages. Generative machine learning models are analyzed to determine a suitable architecture for crop yield prediction. Images of romaine lettuce grown over time under different conditions (e.g., light intensity) are used as the data set. Preliminary results show that the model created is able to predict an image with sufficient accuracy based on a single condition. With our method, corrective actions can be taken early, and yields recover from initial below-average values. Further work can be done to extend the model to other conditions such as moisture, strength of available sunlight, or soil nutrient content.
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Introduction: Most areas under spring sugar beet cultivation face severe water restrictions and increasing the area under cultivation of this crop in most of these areas is contrary to the principle of conservation of water and soil resources. The use of new areas for winter sugar beet cultivation should be the area under cultivation of this crop in hot and dry areas. Therefore, winter sowing (pending) of sugar beet with emphasis on the limitations of the country's water resources has been proposed as a solution. Materials and Methods: In this study, the quantitative and qualitative yield of 16 sugar beet genotypes in winter planting were studied as a randomized complete block design with four replications in the Torbat-e-Jam region in the two cropping years (2020-2021 and 2021-2022). The studied genotypes included F-20739, F-20837, F-21083, SBSI-5, SBSI-15, SVZA 2019-JD389, SVZA 2019-JD0402, SVZA 2019-JD0400, SVZA 2019-JD0401, FDIR 19 B 3021, FDIR 19 B 4028, F-20591, SBSI-6, SBSI-16, SBSI-7 and SBSI-17 are the breeding populations obtained from the gene bank of the Sugar Beet Seed Breeding Research Institute. In this research, traits such as root yield, sugar content, sugar yield, white sugar yield, Na, K, N, alkalinity, molasses sugar, white sugar content, and extraction coefficient of sugar were measured. Data were analyzed using SAS 9.1 software. The analysis of variance on test data and comparison to the middle of the Duncan test was performed at the 5% level. Factor analysis was calculated to identify the main factors using MINITAB software. Cluster analysis of the studied genotypes was obtained after standardizing the data by the Ward method and using Euclidean distance criterion with the help of SPSS software. Results and Discussion: The results of the combined analysis of variance showed that there was a significant difference between different genotypes of sugar beet at the level of 1% probability for all studied traits except for nitrogen content. The mean comparison showed that the SBSI-15 genotype had the highest root yield (60.66 ton.ha). It should be noted that this genotype in terms of yield index traits did not show significantly different from genotypes F-20739, SBSI-15, SVZA 2019-JD389, SVZA 2019-JD0402, SVZA 2019-JD0400, SVZA 2019-JD0401, and FDIR 19 B 4028. Also, the F-20739 genotype had the highest amounts of sugar content (19.5%), white sugar content (16.3%) and extraction coefficient of sugar (83.2%) and the lowest amount of potassium (4.24 meq .100 g-1 of root weight) and Molasses sugar (2.7%). In addition, the highest sugar yield (10.69 t/ha) and white sugar yield (8.68 t/ha) were in FDIR 19 B 3021 genotype. Investigating the correlation of traits showed the highest positive and significant correlation was between sugar yield and white sugar yield (0.99**) and the highest negative and significant correlation was between extraction coefficient of sugar and molasses sugar (-0.95**). Principal factor analysis based on the mean of the traits identified three factors that accounted for a total of 91% of the variability between the data. SBSI-15, SVZA 2019-JD0398, SVZA 2019-JD0402, SVZA 2019-JD0400, SVZA 2019-JD0401, FDIR 19 B 3021, and FDIR 19 B 4028 genotypes are distinguished different from other genotypes and they were as superior genotypes in terms of yield index traits. The dendrogram generated from the cluster analysis for white sugar yield classified genotypes into three main groups.
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The COVID-19 outbreak has seriously affected the global food security at a time when it was significantly compromised by the effects of climate change and armed conflicts. The impact of the pandemic and quarantine restrictions imposed in response to the deadly virus brought humanity face-to-face with a new threat – that of food insecurity – which contributed to a high social demand for state-of-the-art methods of improving the cereal production efficiency. The aim of the study is to develop and implement a methodological approach to enhancing the cereal production efficiency. The methodology of the study relies on time series that made it possible to determine the main trends in regional cereal production and make projections. Application of the suggested approach in the Kostanay region revealed that this region was among the key cereal producers in the country. In 2019, the region was affected by extreme weather, which caused a sharp decline in cereal production. The present study, however, projects large opportunities for cereal production growth in the region and a significant increase in cereal production in the future. In addition, the paper suggests the following action plan to improve efficiency of the cereal production sector in the Kostanay region: streamlining of state support arrangements for cereal producers;development of affordable crop insurance products;systemic steps to increase cereal yields;development of logistic infrastructure;comprehensive monitoring of cereal production to develop a system of rapid response to changes in the external environment © 2022,Journal of Ecological Engineering.All Rights Reserved
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Speed read More than 800 research projects will be affected by deep cuts to UK aid budget Thousands of scientists call on British government to revoke the plans Leading researchers say cuts undermine trusted partnerships Dramatic cuts to UK foreign aid budgets have left the future of hundreds of research projects in developing countries hanging in the balance and trusted partnerships severely undermined, say leading scientists. “The real concern has to be for our partners, who trusted in this process and the early career researchers who will lose their jobs, and the wasted progress on important development issues,” Jenni Barclay, professor of volcanology, University of East Anglia Nick Talbot, executive director of the Sainsbury Laboratory, said it was a “massive breach of trust” to cut ongoing projects of real impact for developing countries. Talbot, a world-renowned expert in molecular plant pathology, leads a project on rice blast, a disease that can devastate rice yields, particularly in Sub-Saharan Africa where disease-resistant varieties are lacking and control strategies limited.
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Speed read Benefits of satellite tech for world’s poorest and the planet could be boundless – if data is open to all Demand for resources to build satellites could put vulnerable communities, indigenous land rights at risk Future challenges remain, such as need for infrastructure, uneven distribution between countries Satellite technologies are a new frontier in global development. Satellites are being used for everything from monitoring illegal fishing to tracking malaria, from supporting early warning systems in flood-prone nations to measuring crop yields and giving farmers advice on fertilisers. Nomadic communities in Africa are using space technology and mobile phone networks to go where the water is and avoid violent conflicts in the Sahel related to climate change and food insecurity.
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Timely, accurate, and repeatable crop mapping is vital for food security. Rice is one of the important food crops. Efficient and timely rice mapping would provide critical support for rice yield and production prediction as well as food security. The development of remote sensing (RS) satellite monitoring technology provides an opportunity for agricultural modernization applications and has become an important method to extract rice. This paper evaluated how a semantic segmentation model U-net that used time series Landsat images and Cropland Data Layer (CDL) performed when applied to extractions of paddy rice in Arkansas. Classifiers were trained based on time series images from 2017–2019, then were transferred to corresponding images in 2020 to obtain resultant maps. The extraction outputs were compared to those produced by Random Forest (RF). The results showed that U-net outperformed RF in most scenarios. The best scenario was when the time resolution of the data composite was fourteen day. The band combination including red band, near-infrared band, and Swir-1 band showed notably better performance than the six widely used bands for extracting rice. This study found a relatively high overall accuracy of 0.92 for extracting rice with training samples including five years from 2015 to 2019. Finally, we generated dynamic maps of rice in 2020. Rice could be identified in the heading stage (two months before maturing) with an overall accuracy of 0.86 on July 23. Accuracy gradually increased with the date of the mapping date. On September 17, overall accuracy was 0.92. There was a significant linear relationship (slope = 0.9, r2 = 0.75) between the mapped areas on July 23 and those from the statistical reports. Dynamic mapping is not only essential to assist farms and governments for growth monitoring and production assessment in the growing season, but also to support mitigation and disaster response strategies in the different growth stages of rice.
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As the world's population approaches eight billion people, there is an increasing demand for cereals, grains, vegetables, animal protein, as well as energy. At the same time, in the shadow of the COVID-19 pandemic, world hunger has increased. After remaining virtually unchanged for five years, the prevalence of malnutrition (PoU) increased from 8.4% to about 9.9% in just one year, further adding to the challenge of achieving the Zero Hunger target by 2030. Research Findings To sustainably increase agriculture productivity, the use of best plant nutrition practices is essential. The shortage of any one nutrient has the potential to limit the growth, productivity, and quality of crops, as stated in Justus von Liebig's "Law of the Minimum". In addition to nitrogen (N), phosphorus (P), and potassium (K), attention must be paid to other macronutrients including calcium (Ca), magnesium (Mg), and sulfur (S), and to the management of micronutrients as well. Balanced fertilization is essential to obtain the maximum potential for crop yield. Since 2015 a new natural mineral fertilizer, polyhalite, has stood out as an alternative fertilizer. Polyhalite provides four macronutrients in a single granule: K, Ca, Mg, and S. Polyhalite has several differential characteristics, such as a low salt content and prolonged availability of nutrients. Polyhalite has a lower carbon footprint than similar fertilizers and can be used in organic production systems. Reviewing the research into the use of polyhalite as a sustainable multi-nutrient fertilizer consistently reveals its potential to increase agricultural productivity, where it consistently and significantly improves the yield, health, and quality of a wide range of crops.