National Agricultural Research Articles

THE INFLUENCE OF GENOTYPE, SOIL TILLAGE AND FERTILISATION ON CARBON SEQUESTRATION IN MAIZE

The increase in the concentration of greenhouse gases in the Earth’s atmosphere, especially that of CO2, is a major concern because it is the main source leading to global warming, and its impact on climate change is still widely studied. The intensity and frequency of drought and flooding increase due to the change in climate, which has a negative impact on crop productivity and food security. The aim of this paper was to demonstrate the role of corn in carbon sequestration based on plant biomass and soil organic carbon accumulation. We presented the main factors that contribute to carbon sequestration and concrete examples regarding the capacity of corn hybrids created at National Agricultural Research and Development Institute (NARDI) Fundulea, as well as aspects regarding the importance of soil tillage and fertilisation. In contrast to genotypes in which this ratio was lower, maize genotypes that demonstrated a rise in the root:stem ratio under drought stress conditions produced more biomass, suggesting that the roots of these genotypes can grow at water potentials where stem growth is inhibited, which are attributes that also prove their good potential for carbon sequestration under climate change conditions. The organic carbon content in the superficial soil layer decreased with the intensification of the degree of soil mobilisation (9.95% when working the soil with the chisel, 17.91% for ploughing), but fertilisation had a beneficial effect. The biomass was higher than that of the unfertilised soil. This means that a higher carbon input has a positive influence on the carbon stock in the soil.

Measuring biodiversity and the loss of indigenous landscapes in coastal Louisiana using airborne imagery and satellite data

ABSTRACT The Adams Bay site is a Native American monumental centre located in the Mississippi River Delta (MRD), a dynamic, geomorphic environment comprised of marshes, bayous, and rivers. The site itself was constructed approximately 600 to 800 years ago by Indigenous communities who are the ancestors of modern-day coastal communities. Earthen mounds at Adams Bay have disappeared over the past 70 years, and the last remaining mound at the site has almost completely eroded away over the past 10 years. This is an environment that is rapidly subsiding, eroding, and becoming inundated due to sea-level rise, and within this environment are hundreds of earthen and shell mounds. This study uses Sentinel-2 and National Agriculture Imagery Program data to document decadal changes to the landscape at Adams Bay and posits that mound-building had net positive impacts on biodiversity and vegetation in this marshy, deltaic environment. Sites like Adams Bay provide remarkable ecosystem services, enhancing the resilience of coastal ecosystems, and they must be studied and/or preserved before being lost to climatic and environmental forces. Finally, these sites are still incredibly significant to modern Indigenous communities who live in the coastal zone today, and additional resources need to be dedicated towards their conservation.

Genetic trends for yield and key agronomic traits in pre-commercial and commercial maize varieties between 2008 and 2020 in Uganda.

Estimating genetic gains is vital to optimize breeding programs for increased efficiency. Genetic gains should translate into productivity gains if returns to investments in breeding and impact are to be realized. The objective of this study was to estimate genetic gain for grain yield and key agronomic traits in pre-commercial and commercial maize varieties from public and private breeding programs tested in (i) national performance trials (NPT), (ii) era trial and, (iii) compare the trends with the national average. The study used (i) historical NPT data on 419 improved maize varieties evaluated in 23 trials at 6-8 locations each between 2008 and 2020, and (ii) data from an era trial of 54 maize hybrids released between 1999 and 2020. The NPT data was first analyzed using a mixed model and resulting estimate for each entry was regressed onto its first year of testing. Analysis was done over all entries, only entries from National Agricultural Research Organization (NARO), International Maize and Wheat Improvement Center (CIMMYT), or private seed companies. Estimated genetic gain was 2.25% or 81 kg ha-1 year-1 from the NPT analysis. A comparison of genetic trends by source indicated that CIMMYT entries had a gain of 1.98% year-1 or 106 kg ha-1 year-1. In contrast, NARO and private sector maize entries recorded genetic gains of 1.30% year-1 (59 kg ha-1 year-1) and 1.71% year-1 (79 kg ha-1 year-1), respectively. Varieties from NARO and private sector showed comparable mean yields of 4.56 t ha-1 and 4.62 t ha-1, respectively, while hybrids from CIMMYT had a mean of 5.37 t ha-1. Era analysis indicated significant genetic gain of 1.69% year-1 or 55 kg ha-1 year-1, while a significant national productivity gain of 1.48% year-1 (37 kg ha-1 year-1) was obtained. The study, thus, demonstrated the importance of public-private partnerships in development and delivery of new genetics to farmers in Uganda.

Implications of US agricultural data practices for sustainable food systems research.

Using the tenets of data feminism, we analyse the National Agricultural Statistics Service Quick Stats database - the primary repository of United States agricultural data. We identify unstated assumptions built into the database's scaffolding through data collection, aggregation and dissemination practices, revealing how they facilitate granular analyses of agricultural topics historically judged as national priorities while leaving unilluminated many others of vital importance for contemporary sustainability needs. We argue that this entrenches an inequitable and unsustainable food systems status quo, and we offer recommendations for data providers and users based on principles of reflexivity, context and pluralism.

The sensitivity of food security to agricultural input subsidies in Uganda

The agricultural sector plays a crucial role in addressing food insecurity and malnutrition in developing countries, and smallholder farmers are significant contributors to food production. In Uganda, the National Agricultural Advisory Services (NAADS) program was initiated in 2001 to provide extension services and agricultural input subsidies to farmers. However, the program has faced criticism for its high levels of corruption, militarization, and political influence, as well as for its failure to reach its intended beneficiaries, and smallholder farmers. This paper aims to examine the contribution of smallholder farmers to food security and its sensitivity to agricultural input subsidies in Uganda, with a focus on the NAADS program. Additionally, it covers the evolution of agricultural input subsidy policy in Uganda from 1987 to the present and analyses the findings on the impact of these subsidies on smallholder farmer productivity and food security. The findings conclude that the NAADS program contributes less to the target beneficiaries, and its priorities do not align with the set goals. The study further suggests several recommendations for improving the program and addressing the issues facing smallholder farmers in Uganda.

Leveraging Important Covariate Groups for Corn Yield Prediction

Accurate yield information empowers farmers to adapt, their governments to adopt timely agricultural and food policy interventions, and the markets they supply to prepare for production shifts. Unfortunately, the most representative yield data in the US, provided by the US Department of Agriculture, National Agricultural Statistics Service (USDA-NASS) Surveys, are spatiotemporally patchy and inconsistent. This paper builds a more complete data product by examining the spatiotemporal efficacy of random forests (RF) in predicting county-level yields of corn—the most widely cultivated crop in the US. To meet our objective, we compare RF cross-validated prediction accuracy using several combinations of explanatory variables. We also utilize variable importance measures and partial dependence plots to compare and contextualize how key variables interact with corn yield. Results suggest that RF predicts US corn yields well using a relatively small subset of climate variables along with year and geographical location (RMSE = 17.1 bushels/acre (1.2 tons/hectare)). Of note is the insensitivity of RF prediction accuracy when removing variables traditionally thought to be predictive of yield or variables flagged as important by RF variable importance measures. Understanding what variables are needed to accurately predict corn yields provides a template for applying machine learning approaches to estimate county-level yields for other US crops.

Strategies for Sustainable Management of Agricultural Waste Vinyl in South Korea

Vinyl, such as those in the form of mulching and vinyl houses, is used to improve agricultural productivity. It is generated as an agriculture waste vinyl (AWV) after use. The collected AWV is transported to a recycling facility and shredded, washed, and compressed to be recycled. Recycled materials can contribute to the circular economy of agriculture as they are used again as an agricultural plastic product. However, in Korea, there are concerns about the illegal disposal (landfill, incineration) of AWV. So, a new management model is needed in which stakeholders voluntarily establish an AWV management system. In this study, a sustainable management strategy was proposed. This strategy is reinforcing the responsibility of the producers of AWV and forms a value chain in the proper discharge after consumption by applying the deposit system proposed to recover AWV. Local governments and the National Agricultural Cooperative Federation (NH) proposed education to curb the illegal disposal of AWV, and for managing areas where a collection system has not yet been established, biodegradable mulching vinyl (BMV) was proposed to minimize the environmental pollution caused by AWV. It was calculated that the EPR contribution was 0.16 USD/kg, and the introduction of BMV was 0.42 USD/kg in Korea. This study will provide a new alternative in countries struggling with AWV management.

Micro Fluidics for Food, Agriculture and Biosystems Industries

Microfluidics is the technological know-how and computing in small blocks or controlling Systems Technology fluids (10−nine to 10−18L) using channels measuring tens to hundreds of micrometers. Microfluidics in the early 1980s appeared and used in technology development. One of the fashionable, micro methods following capabilities: small volumes United Nations Food and Agriculture Organization CSA techniques include planting drought-tolerant seeds, using drip irrigation, and using shade trees in integrated agriculture. Integrated biological procedures their price-powerful conversion into excessive-price bio molecules is vital to attaining the technical, monetary and environmental feasibility of bio resource era development. New techniques for the manufacturing containing periodic habitats of bio molecules need food and pharmaceutical industries Agri-Food Supply Chain This research aims to explore block chain era with a focal point on meals and agriculture research. Therefore, a bibliometric approach changed into followed to become aware of key developments and topics in this domain by studying substantive articles, authors, countries and keywords. This study attempts to expand a graphical map of bibliographic facts in food and agriculture

Does agricultural water-saving policy improve food security? Evidence from the Yellow River Basin in China

Abstract For our empirical research, the 2012 implementation of China's National Agricultural Water-Saving Outline serves as a quasi-experiment. In addition, one of the main regions in China for grain production is the Yellow River Basin. Based on this, we utilize a Difference-in-Difference (DID) empirical technique to assess the impact of the agricultural water-saving policy on food security using data from prefectures in China's Yellow River Basin from 2000 to 2020. According to the estimated results, grain production has greatly increased as a result of the agricultural water-saving policy. This conclusion still holds when other water-related policies are considered. The agricultural water-saving policy may enhance other input factors in grain production by assuring water demand, which is one possible mechanism of the influence. The empirical results show that the policy indeed increases the water productivity in agricultural production, which will ensure the effective water utilization in agricultural production, and the grain sown area, which is the most important production factor in agriculture. In heterogeneity analysis, the impact of the policy on food security is the largest in the lower reach, followed by the middle reach and the smallest in the upper reach in the Yellow River Basin.

Impacts of irrigation tank restoration on water bodies and croplands in Telangana State of India using Landsat time series data and machine learning algorithms

In 2014, the State of Telangana in southern India began repairing and restoring more than 46,000 irrigation water tanks (artificial reservoirs) under the Mission Kakatiya project with an investment in excess of USD 2 billion. In this study, we attempted to map the temporal changes that have occurred in cropland areas and water bodies as a result of the project, using remote sensing imagery and applying land use/land cover (LULC) mapping algorithms. We used 16-day time series data from Landsat 8 to study the spatial distribution of changes in water bodies and cropland areas over the 2013–18 period. Ground survey information was used to assess the pixel-based accuracy of the Landsat-derived data. The areas served by these tanks were identified on the basis of training data and Random Forest algorithms using Google Earth Engine. Our spatial analysis revealed a substantial increase in cropped area under irrigation and expansion of water bodies over the study period. We observed a 20% increase in total tank area in 2017–18 and total cropland and irrigated area expansion of the order of 0.6 M ha and 0.2 M ha, respectively. A comparison of ground survey data and four LULC classes derived from Landsat temporal imagery showed an overall accuracy of 87%, significantly correlated with national agriculture statistics. Periodic monitoring based on remote sensing has proved to be an effective method of capturing LULC changes resulting from the Mission Kakatiya interventions. Higher-resolution satellite data can further improve the accuracy of estimates.

Are common bean traders efficient? An empirical evidence from Malawi

Efficient agricultural markets can be a bedrock for diverse economy-wide benefits ranging from improvements in resource use to price stabilisation. However, as is the case with most developing and agrarian countries, Malawi's agricultural markets are still developing. This is mainly the case in the country's legume markets, especially the bean marketing system. The current study assessed the market efficiency of common bean traders in Malawi using a multiple linear regression model. By focusing on the bean traders in the major markets in Malawi, the study departs from earlier research on bean marketing, which has placed greater emphasis on the farmer. The findings reveal that traders in bean markets mostly use informal sources of market information. Again, transaction costs such as transportation, storage, handling and distance to sources of bean reduce marketing efficiency. The scale of the operation portrayed a positive influence on marketing efficiency. Access to credit significantly increased marketing efficiency for both wholesalers and retailers. In addition, markets that are located in rural areas had a negative effect on marketing efficiency as compared to markets in urban areas, further agreeing with the focus of the National Agriculture Policy (NAP) to introduce structured markets in rural areas. The study recommends adjustments in policies in the NAP that would promote smooth access to reliable market information, especially in rural areas. The upgrading of the rural road system and warehousing facilities should be promoted in order to lower transaction costs. This will enable bean traders to expand their operations on a larger scale while also lowering expenses and increasing profits.

Improved Model Estimates of Tree Debris Following Ice Storms

Planning to prepare for storms should involve the estimation of tree debris. This paper tested an improvement of a rapid estimation model of tree debris following ice storms. An initial model found using 30-m resolution National Land Cover Database (NLCD) tree canopy cover (TCC) data did not significantly (P ≈ 0.20) improve estimation of tree debris within a community right-of-way (ROW) following an ice storm. We tested if finer resolution National Agriculture Imagery Program (NAIP) TCC imagery (2-m resolution or better) could more accurately predict tree debris after an ice storm. Tree canopy cover was estimated with NAIP across the entire community (TCCCITY) and also the area that only covered the ROW plus a 15.24-m (50-foot) buffer on each side (TCCROW). The TCCCITY (P = 0.08) estimate marginally improved tree debris prediction in the overall multiple regression model (R2 adj = 0.917; F = 133.8; df = 3,33), but this was not the case with the TCCROW (P = 0.66) estimate. The TCCCITY estimate was 34.7% (SEM = 2.0) and significantly (P < 0.001) 2 times greater than in the 16.2% (SEM = 2.2) TCC estimate from NLCD imagery. We found the TCCROW was 32.6% (SEM = 1.6) and significantly lower (P = 0.003) than in TCCCITY. Results from this study may improve the overall ability to predict tree debris following ice storms from the regional models currently used to a more local estimate for a city. Future investigations are needed to determine if this is the case.

An overview of National Agricultural Education Policy

An overview of National Agricultural Education Policy

Risk Perceptions in Agricultural Aviation

ABSTRACT Background Agricultural aircraft operations are an integral part of the agricultural sector. According to the National Agriculture Aviation Association (NAAA), aerial applications are conducted in all 50 states of the U.S. and account for 28% of all treated cropland. A typical application operation consists of an operator (Part 137 certificate holder, permission to apply chemicals to agricultural crops) and one or more pilots. This article explores the risk perceptions of operators (pilots with a Part 137 certificate) and non-operators (pilots without a Part 137 certificate) using data from two industry surveys. Methods In an effort to explain the differences between risk perceptions of operators and non-operators, a series of regression analyses were conducted controlling for age, work experience, prior encounters with hazards and history of reported injuries. In addition to exploring the aggregated perceptions across all hazards, perceptions of specific hazards were also examined. Results Data indicate that non-operators perceive hazards as significantly more dangerous than operators. Power lines are perceived as the most hazardous, followed by communication towers and meteorological towers. The regression results indicate that risk perception differences remain even after controlling for differences in age, work experiences, prior hazard encounters and injuries between the two groups. Conclusions Heterogeneity in risk perceptions within an organization can result in discrepancies over daily decision-making concerning operations. Further research is needed to identify the causal factors behind the observed differences.

Comparison of high-resolution NAIP and unmanned aerial vehicle (UAV) imagery for natural vegetation communities classification using machine learning approaches

ABSTRACT To map and manage forest vegetation including wetland communities, remote sensing technology has been shown to be a valid and widely employed technology. In this paper, two ecologically different study areas were evaluated using free and widely available high-resolution multispectral National Agriculture Imagery Program (NAIP) and ultra-high-resolution multispectral unmanned aerial vehicle (UAV) imagery located in the Upper Great Lakes Laurentian Mixed Forest. Three different machine learning algorithms, random forest (RF), support vector machine (SVM), and averaged neural network (avNNet), were evaluated to classify complex natural habitat communities as defined by the Michigan Natural Features Inventory. Accurate training sets were developed using both spectral enhancement and transformation techniques, field collected data, soil data, texture, spectral indices, and expert knowledge. The utility of the various ancillary datasets significantly improved classification results. Using the RF classifier, overall accuracies (OA) between 83.8% and 87.7% with kappa (k) values between 0.79 and 0.85 for the NAIP imagery and between 87.3% and 93.7% OA with k values between 0.83 and 0.92 for the UAV dataset were achieved. Based on the results, we concluded RF to be a robust choice for classifying complex forest vegetation including surrounding wetland communities.

The Short-term Impact of Sustainable Agriculture Policy on Farmers’ Economic Welfare in China

Half of the Chinese population still consists of farmers. To increase their productivity, sustainable agriculture offers essential approaches while protecting the environment. Unlike the existing literature focusing on the long-term effects of sustainable agriculture on economic welfare, the current research examines how sustainable agriculture impacts the various aspects of farmers’ welfare in the short term. We used data from the China Health and Retirement Longitudinal Study (CHARLS) and the Chinese National Agricultural Sustainable Development Plan (2015-2030). To investigate the impact of sustainable agriculture policy on economic welfare, we also employed the Difference-in-Differences (DID) model which helped address the endogeneity problem. After the DID regression, we discovered that sustainable agriculture has a negative impact on farmers’ annual household incomes and overall health status. However, it increases the annual working time of farmers and their willingness to participate in agricultural work. To ensure the reproducibility and reliability of the result, we did the robustness test by merely keeping the key independent variables on each regression. We also employed two sets of placebo tests and an alternative DID approach for each key dependent variable. Since all the regressions are robust and all results are significant, the initial hypothesis of this paper was demonstrated. We also propose some policy suggestions based on these results.

A Study: - “Assessing Impact of Goods and Services Tax on Agriculture”

Agricultural sector has been the root of Indian economy and it contributes to around 18.8 percent in (2021-2022) GDP. About 52 percent of the total rural livelihood depends on this sector as their primary means of livelihood. The GST is being introduced with the unbiased objective of having a unified tax structure for goods and services, this is likely to facilitate and strengthen the Scheme on National Agricultural Market (NAM) aimed at an integrated system of market of agriculture produce at the national level, allowing free flow of agricultural commodities across states. The aim of the study is to identify the impact of GST on the Agriculture sector. The data were collected from 400 farmers of Rajasthan using non probability convenience sampling. The result argues that GST will have both significant positive and negative effect on Agriculture. Future this paper show a behavioral suggestions and bringing out the light on Impact of GST on Agriculture Sector. Key Words: Agriculture, GST, National Agriculture Market (e-NAM), Cost of Agriculture

Plant variety protection and secured financing in Nigeria: lessons from international standards

... On 22 May 2021, the World News Media widely reported on the passing, at the age of 91, of Professor Yuan Longping, a Chinese agronomist nicknamed the ‘Father of Hybrid Rice’ and reputed for reportedly saving the teeming Chinese population with his genetically modified hybrid species of high-yield, fast-growing, disease-resistant rice discovered in 1974.1 His species of rice was to become predominant in the USA, Africa and Asia, thereby saving practically the entire world from malnutrition, hunger and starvation.2 Encomiums and fond remembrance continued to trail the demise of this world-famous and important scientist.3 In the 1970s, Yuan’s hybrid strain of rice recorded an annual yield 20 per cent higher than existing variety which, in practical terms, meant that it could feed an extra 70 million people in China that year.4 In 2017, in conjunction with an agricultural school, he helped create a strain of low-cadmium Indica rice for areas suffering from heavy metal pollution, reducing the amount of cadmium in rice by more than 90 per cent.5 These examples illustrate the importance of genetically modified plant variety in contemporary agriculture and explain why governments and non-governmental institutions should encourage and protect safe inventions in agriculture to incentivize creativity and end global hunger and malnutrition, especially in times of food shortage, famine and global food insecurity. Apart from the 2004 World Food Prize, Yuan’s honours and awards also included the United Nations Food and Agriculture Organization (FAO) Medal of Honor for Food Security and the 2004 Wolf Prize in Agriculture, and he was also appointed as chief consultant to the United Nations FAO programme to increase grain production outside China which made the hybrid rice its first choice.6

CHANGES IN THE NUMBER AND STRUCTURE OF FARMS IN POLAND

The aim of the research was to assess the scale of changes in the number of and spatial variations in the agricultural structure of farms in Poland taking place at the beginning of the 21st century. The publication is a review and is based on the results of National Agricultural Censuses from the year 2002 and 2020 conducted by Statistics Poland as well as the reports on the activity of the Agency for Restructuring and Modernisation of Agriculture covering the period 2004-2020. Voivodeship was adopted as the basic study unit. The publication consists of two main parts. The first one is an analysis of the changes in the number of farms. The second one is assessment of the similarity of the agricultural structure of the farms located in individual voivodeships. The conducted analyses have confirmed that there was an increase in the percentage of farms characterised by a larger size in the period under study. An interesting observation is the fact that in most of the voivodeships under study the agricultural structure of farms was slowly but clearly becoming similar. The polarization of farms in terms of their size in the surveyed groups of provinces is also deepening.

A net-map analysis of stakeholder connections and influence in agriculture-for-nutrition policymaking in Ghana

Nutrition-sensitive agriculture approaches can improve farming household incomes, food security, and diet quality. Adopting nutrition-sensitive agriculture approaches means placing a nutrition lens on the policies, strategies, and investments in the food and agriculture sector without detracting from the sector's traditional goals of food supply. To understand the processes involved in developing agriculture-for-nutrition policies in Ghana, this paper examined the influence of stakeholders' interconnections using a visual participatory mapping technique, Virtual Net-Map. Three convening platforms were identified for stakeholder engagement: the Agriculture Sector Working Group, the National Agricultural Technical Committee, and the Public-Private Partnership Dialogue Platform. Sixty stakeholders with 188 connections were recognised for their involvement in agriculture-for-nutrition policymaking in Ghana. Fourteen stakeholders, twelve from government organizations and two from donor and development partner organizations, were identified as the most influential. International stakeholders (donors and development partners) were critical in funding agriculture-for-nutrition policymaking activities. While all stakeholders had a joint mandate to ensure policies were developed, the Ministry of Food and Agriculture led the policy development process in Ghana's food and agriculture sector. Moreover, government stakeholders notably received more support from other stakeholders for funding, advocacy, dissemination, and technical assistance than the support they offered. Generally, stakeholders were more engaged in technical assistance activities and least involved in disseminating agriculture-nutrition information in the agriculture-for-nutrition policymaking process. The information on stakeholders' interconnections and influence showed areas that had the most and least stakeholder engagements, which will enable potential stakeholders to identify niche(s) to support the nutrition agenda in Ghana's food and agriculture sector and help Ghana meet the Global Nutrition Targets and the Sustainable Development Goals for 2025 and 2030, respectively. In addition, the evidence presented on Ghana's agriculture-for-nutrition policymaking network can lead to better ways of centralizing nutrition in agricultural policies and designing initiatives that encompass most, if not all, relevant stakeholders. Key words: Agriculture, Nutrition, Policymaking, Net-Map, Influence, Connections, Ghana, Nutrition-sensitive agriculture