Agricultural Resources Research Articles

Spatio-temporal characteristics of rainfall and drought conditions are using the different drought indices with geospatial approaches in Karnataka state

Karnataka state drought conditions are assessed via drought indices. Over the past several decades, several indices of drought (DI) have been developed and presented, although some of them are region-specific and have problems regarding their applicability to other climatic circumstances. Additionally, choosing the best DI time step to illustrate the drought condition is difficult because of the DIs' various time steps. The study compares the Standardized Precipitation Index (SPI), Statistical Z-Score, China Z-Index (CZI), Rainfall Anomaly Index (RAI), and Rainfall Departure (RD) to determine which one is most appropriate for the districts of the Karnataka state that are prone to both dry and rainy conditions. This study has pointed out that the best drought indices are SPI and RD, and the least accountable drought indice is China Z index. Droughts were most common in 22 districts in 2009, which represent around 70.97% of the state's landmass. In comparison with the rest of the districts, the Ramanagara district noticed the worst drought conditions in 2003, with rainfall reaching 92.47 mm and SPI -3.68, RAI-6.04, MCZI -2.39, and Z score −2.62. Overall, the results of the study will aid in the organization and improvement of drought, flood, agriculture, and water resource management approaches in the state.

Metabolic and histopathological impact of local resource food consumption on blood markers in rats previously subjected to moderate acute malnutrition

Malnutrition is caused by dietary and nutritional imbalances that can have an impact on blood parameters and vital organs. The use of local agricultural resources for adapted diets appears to be an effective solution to post-weaning infant malnutrition. The aim of this study was to evaluate the effectiveness of four newborn diets made from local agricultural resources in improving biochemical, hematological, and histological parameters in rats that had previously experienced mild acute malnutrition. A total of 42 juvenile male rats, with an average age of 80 ±5 days and an average weight of 103.46 ± 5.10 g, were divided into six groups. Each group consisted of seven rats, with two control groups (LTC and LSA) and four experimental groups (LAR1A, LAR1B, LAR2A, and LAR2B). The experiment had three distinct phases: an initial adaptation period lasting 5 days, followed by a phase of inducing malnutrition lasting 19 days, and finally a phase of nutritional rehabilitation lasting 14 days. At the conclusion of the malnutrition induction and nutritional rehabilitation phases, blood samples were collected and used to evaluate biochemical and haematological markers. Kidneys and liver were removed for histological analysis.The findings revealed that the period of inducing malnutrition had a detrimental impact on several parameters, such as urea, triglyceride, total protein, C-reactive protein, albumin, ALAT, ASAT, WBC, hemoglobin, hematocrit, and MCV. Nevertheless, the ingestion of LAR diet derived from indigenous ingredients successfully returned all of these blood markers to the required levels for rats. Furthermore, histological examinations demonstrated that there were no kidney or liver abnormalities at the end of the trial.The LAR diets have rehabilitative effects on the biochemical and haematological parameters of rats. This suggests that these diets can be used therapeutically to treat moderate acute malnutrition and meet the nutritional needs of children aged 6 to 36 months.

Fuzzy Comprehensive Evaluation-Based Development System for Eco-Agricultural Tourism Resources

This manuscript outlines a systematic evaluation of agricultural eco-tourism resources, focusing on the Taihang Mountain Grand Canyon scenic area. Employing fuzzy mathematics principles, we construct a comprehensive evaluation model to assess various dimensions of agro-ecotourism potential. The framework includes hierarchical levels (A, B1-B3, C1-C8) covering ecological resource value, environment condition, and tourism development. Using the fuzzy comprehensive evaluation method, we determine indicator weights via expert assessments and statistical analyses. Notably, ecological resource value and environment quality emerge as pivotal criteria. The resulting comprehensive score of 82.875 suggests Grade IV suitability for eco-tourism development. Our findings support strategic planning and sustainable management, emphasizing the importance of ecological preservation amidst China's urbanization. Graphical representations and detailed steps provided enhance practicality for sustainable tourism researchers and practitioners.

Evaluating the Impact of Fair Price Shops on Food Security: A Comprehensive Study within the Aspirational District Programme in Hazaribagh, Jharkhand

Abstract The Aspirational District Programme, initiated by Prime Minister Narendra Modi in January 2018, aims to promote equitable development across 115 identified districts in India, including 19 in Jharkhand, with Hazaribagh situated in the North Chotanagpur division. This program operates under 49 indicators spread across five key sectors: Health and Nutrition, Education, Agriculture and Water Resources, Financial Inclusion and Skill Development, and Basic Infrastructure. A critical aspect of this initiative is the Health and Nutrition sector, which emphasizes the provision of nutritious food to ensure that no one faces hunger. Food security is vital in assessing whether individuals have consistent access to food, particularly through the Public Distribution System (PDS). This system includes numerous Fair Price Shops, or ration shops, tasked with delivering essential goods to individuals categorized as Below Poverty Line (BPL), Priority House Holds (PHH), and those under the Antyodaya Anna Yojana (AAY) in Jharkhand, aimed at supporting the most impoverished families with subsidized rates set by the central government. My research focuses on several Fair Price Shops in Hazaribagh district, employing survey methods to gather primary data. The objective is to gain insights into the actual conditions of these ration shops and to evaluate the extent of benefits received by the local population.

Bibliometric Analysis of Root Research under Drip Irrigation Based on Web of Science

The study delves into the prevailing focal points and developmental trends within the international sphere of crop root research under drip irrigation. It leverages the Web of Science core database and employs VOSviewer for a systematic review of the literature spanning 2001 to 2022. The analysis encompasses publication counts, publishing journals, contributing authors, research institutions, and keywords. Findings indicate that research on root systems under drip irrigation has become a notable area of interest in the field of irrigation, attracting global scholarly attention. There is a marked upward trend in publication output, with institutions in China and the United States taking on central roles. Journals like Agricultural Water Management and Acta Horticulturae are key publication venues, with Vadose Zone Journal being notable for high-impact articles. The research primarily involves agronomy, water resources, and horticulture, focusing on yield enhancement through drip irrigation, root distribution under various techniques, crop quality in response to partial root-zone drying, and irrigation scheduling model development. Scholars like Jiri Simunek and Yaohu Kang have made substantial contributions. The field’s established framework calls for continued international collaboration to drive further innovation. The identified trends and parameters can be a valuable reference for researchers, policymakers, and practitioners, guiding efforts to optimize agricultural productivity and resource use.

Moringa Leaf Cookies: A Nutritious Snack to Prevent Stunting in Sawocangkring Village

Stunting is a global health issue that significantly impacts the growth and development of children, particularly in regions facing nutritional deficiencies. In Sawocangkring Village, there is a pressing need for innovative nutritional interventions. This study aims to utilize moringa leaves in the production of cookies as a nutritious snack solution to combat stunting. The community service program was designed with distinct stages, including preparation, implementation, and evaluation, employing observation techniques to assess community engagement. The activity centered on developing moringa leaf cookies while monitoring the community's acceptance of the product. The findings indicate that these cookies not only enhance the nutritional value of snacks but are also positively received by the local population. The novelty of this initiative lies in integrating moringa leaves into a familiar food product, thereby promoting both health benefits and local agricultural resources. The implications of this program suggest that the sustainable production of moringa leaf cookies could serve as a viable livelihood strategy for the community, while also contributing to the broader effort of reducing stunting through improved nutrition. Highlights: Moringa leaf cookies enhance nutritional value, addressing stunting in children. The community service program involved preparation, implementation, and evaluation stages, fostering local engagement. Positive community acceptance suggests potential for sustainable production as a livelihood strategy. Keywords: Stunting, moringa leaves, cookies, nutrition, community service.

Integrating solar-induced chlorophyll fluorescence with traditional remote sensing and environmental variables for enhanced rice yield prediction in Nepal using machine learning

Rice is a vital cereal crop providing essential food for Nepal. To mitigate climate risks and ensure food security, especially with climate change and increasing extreme weather events, it is imperative and a prerequisite to have timely and reliable rice yield prediction. While traditional vegetation indices (VIs) and environmental variables are commonly used in rice yield prediction, the potential of solar-induced chlorophyll fluorescence (SIF), despite its greater sensitivity, has been explored in limited studies. Furthermore, integrating SIF with other remote sensing and environmental data for regional crop yield modeling still needs to be explored. This study aims to address these gaps by incorporating SIF to enhance rice yield prediction in Nepal, offering a novel approach to improving model accuracy. This study uses multi-source data and machine learning algorithms to study 22 major rice-growing districts in the Terai region of Nepal. Random forest (RF), support vector machine (SVR), gradient boosting regressor (GBR), and least absolute shrinkage and selection operator (LASSO) algorithms were employed to predict crop yield using various combinations of input features. Machine learning models were trained and tested over four different time windows within the growing period of rice, using 15 years of rice yield data from 2003 to 2017. Our analysis reveals that GBR out-performed other machine learning algorithms when using input features from July to September, achieving root mean square error (RMSE) and the ratio of RMSE (RRMSE) to observed mean values of 250 kg/ha and 8.6%, respectively. The findings also reveal that incorporating SIF alongside traditional remote sensing and environmental variables significantly enhances the model's prediction accuracy. These findings are valuable for ensuring food security, optimizing agricultural resource management, and supporting decision-making for farmers, policymakers, and supply chain stakeholders.

Field-scale variability and dynamics of soil moisture in Southwestern Nigeria

This research leverages field-based sensors and Geographic Information Systems (GIS) to elucidate soil moisture dynamics across diverse land uses in Southwestern Nigeria, including Cocoa, Cassava, Oil Palm, and Riparian ecosystems. The study synthesizes soil moisture data and geospatial coordinates from strategically selected land covers with satellite-derived soil moisture records from NASA's Prediction of Worldwide Energy Resources (POWER) and the US Geological Survey. Through a robust analytical framework combining cross-correlation functions, wavelet analysis, and inverse distance weighting interpolation, we revealed distinct soil moisture patterns ranging from 0 to 47.9% in arable farms, 0 to 46.8% in built-up areas, 0 to 49.9% in cocoa farms, 0.2 to 49.7% in oil palm farms, and 5.6 to 94.1% in riparian vegetation. The coefficient of determination values between 0.7 and 0.97 (p ≤ 0.05) underscore the significant influence of periodic land use on soil moisture during the study period. A comparative analysis of ground-based and satellite data revealed a potential overestimation of minimum soil moisture values by 66% and an underestimation of maximum values by 4%. This investigation provides critical insights into the interplay between hydrological variables and agro-meteorological factors, informing the management and assessment of agricultural resources.

Portfolio Agriculture: A Model for Resilient Regional Agricultural Planning

Food security is threatened by climate change worldwide; consequently, agriculture and farming livelihoods must adapt to new and unpredictable conditions. These conditions vary along spatial scales, and since agricultural yields are sensitive to microclimate conditions, a locally tailored data-driven approach may be helpful. Furthermore, limited agricultural resources like water and labor increasingly constrain food production. This research proposes a regional portfolio model for identifying crop choices and regional portfolio compositions that align with known and forecasted microclimate variation in temperature and humidity. The model will enable farmers to assess tradeoffs between the financial returns and agricultural production risks. The goal of this work is to provide new insights into agricultural planning in the face of climate risk and limited access to water and labor resources. Three steps are taken. Firstly, regional agricultural land is divided into farming subunits, with each representing a terroir characterized by temperature and humidity. Then a simulated yield coefficient is used to assess the effect of microclimate variables on the yield of the different crops in the portfolio of each subunit. Secondly, farming resource allocation, represented by water and labor, across crops and farming subunits is optimized to maximize the yield and associated financial return from farming across the agricultural region. Finally, a resilient agricultural planning model is developed based on the assumed data for regional microclimate and agricultural resources. The results of this research can be used by regional farmers as a reference for selecting crop portfolios and resource allocations to maximize overall profit.

Efficient conversion of hemicellulose into high-value product and electric power by enzyme-engineered bacterial consortia

As an abundant agricultural and forestry biomass resource, hemicelluloses are hard to be effectively degraded and utilized by microorganisms due to the constraints of membrane and metabolic regulations. Herein, we report a synthetic extracellular metabolic pathway with hemicellulose-degrading-enzymes controllably displayed on Escherichia coli surface as engineered bacterial consortia members for efficient utilization of xylan, the most abundant component in hemicellulose. Further, we develop a hemicellulose/O2 microbial fuel cell (MFC) configuring of enzyme-engineered bacterial consortia based bioanode and bacterial-displayed laccase based biocathode. The optimized MFC exhibited an open-circuit voltage of 0.71 V and a maximum power density (Pmax) of 174.33 ± 4.56 µW cm−2. Meanwhile, 46.6% (w/w) α-ketoglutarate was produced in this hemicellulose fed-MFC. Besides, the MFC retained over 95% of the Pmax during 6 days’ operation. Therefore, this work establishes an effective and sustainable one-pot process for catalyzing renewable biomass into high-value products and electricity in an environmentally-friendly way.

Local knowledge of Mecula Haroano Laa as social cohesion of agricultural communities in Buton utara district

Mecula Haroano Laa is a local wisdom that includes beliefs, norms, and practices passed down from generation to generation in the context of agricultural resource preservation and community cultural identity formation. The author is interested in investigating the practices of the Mecula Haroano Laa tradition, which is unique to North Buton Regency and has unique specifications and characteristics. This research uses a qualitative approach. The data collection techniques used in this study are in-depth interviews and participatory observations. The results of this study demonstrate that Mecula Haroano Laa in North Buton society is more than just an agricultural custom; it is also an attempt to strengthen social solidarity among community members. This practice reflects the spirit of solidarity, gotong royong together, and respect for the environment. The North Buton community is actively involved in implementing Mecula Haroano Laa as a form of participation in developing sustainable agriculture. This research contributes to understanding the importance of local wisdom in building social cohesion in communities. Research implications include sustainable planning and efforts to empower communities in developing farms in North Buton Regency. Natural resource management policies may incorporate. Mecula Haroano Laa’s effective and sustainable resource management techniques to promote wise use, environmental conservation, economic resilience, and dependency reduction.

Optimizing agricultural water resources: a study on cotton cultivation using non-conventional water sources in Khuzestan, Iran

Optimizing agricultural water resources: a study on cotton cultivation using non-conventional water sources in Khuzestan, Iran

Salinity challenges and adaptive strategies in salinization-affected coastal Bangladesh: Implications for agricultural sustainability and water resource management

Abstract Salinization has become a rising global concern due to its notable effects on agriculture and freshwater resources. Coastal region of Bangladesh has been struggling with elevated levels of soil and water salinity, exacerbated by storm surges and rising sea levels. We assessed nutrient and salinity contents in agricultural and homestead lands, and the level of salinity in pond and canal water in six sub-districts in coastal Bangladesh. Finally, using household (HH) survey, focus group discussion (FGD) and key informant interview (KII), we explored the adaptive practices and challenges of salinity issues in agriculture and drinking water management. Soil nitrogen, phosphorus, and potassium contents exhibited significant variations across the sub-districts, which reflect the diversity of agricultural practices and soil management strategies. However, there was no notable difference in soil salinity across the sub-districts, which underscores the commonality of soil salinity as a pressing concern. Shyamnagar (13.99 dS m−1) recorded the highest level of pond water salinity, followed by Assasuni (13.96 dS m−1), Dacope (13.91 dS m−1), Koyra (13.58 dS m−1), Morrelganj (13.33 dS m−1), and Mongla (13.19 dS m−1) sub-districts, which highlights that water salinity decreased from exposed coast to the landward areas. Respondents in HH surveys, FGDs and KIIs identified salinity as a major challenge in agriculture and drinking water. Furthermore, climate-related stresses were recognized as significant challenges impacting crop productivity. The research highlights the feasibility of rainwater harvesting, with 89%–100% of HHs harvest rainwater in HH tanks, as an effective adaptive practice for managing drinking water. The study emphasizes the positive impact of vermicompost in reducing soil salinity levels, which is demonstrated by the 43%–88% of HHs using this practice, indicating its potential as a nature-based solution to address soil salinization. The findings underscore the need for resilient agricultural systems and sustainable water management approaches to tackle these challenges.

IDENTIFIKASI KELEMBAGAAN PERTANIAN DAN PERANANNYA PADA SUBSISTEM PRODUKSI TANAMAN PADI SAWAH DI DESA BUKIT PARIAMAN KECAMATAN TENGGARONG SEBERANG

Agricultural Institutions are a driving factor in achieving agricultural resource management that encourages the achievement of farmer welfare. The existence of important physical and management aspects is studied, especially in rice producing centers, in relation to their contribution to the food supply. The objective of this research to identify existing agricultural institutions in Bukit Pariaman Village, to identify the role of farming institutions in the rice farming production subsystem, and analyze farmers' access to existing agricultural institutions in Bukit Pariaman Village. The research was conducted in Bukit Pariaman Village, Tenggarong Seberang District, Kutai Kartanegara Regency in May-July 2024. The sampling method was purposive sampling. Data analysis used descriptive analysis and perception analysis of access to agricultural institutions. The research results showed that agricultural institutions in Bukit Pariaman Village are adequate and well accessible. The role in the production subsystem was demonstrated by the achievement of an annual rice production surplus of 88.81%.

VALORIZATION OF BANANA FLOWER RESIDUES: POTENTIAL THERAPEUTIC AND ANTIOXIDANT APPLICATIONS

Various parts of the banana tree (Musa spp.), such as leaves, fruits, inflorescences, roots, peels and stems are used in traditional medicine, in several cultures around the world, for the treatment of diarrhea, ulcers, pain, inflammation, and diabetes mellitus. The inflorescence, in turn, stands out as a promising by-product of the banana agroindustry, since it is rich in micronutrients and bioactive compounds relevant to the human health, such as β-sitosterol, flavonoids, saponins, and phenolics like catechin and isoquercetin. Studies reveal that the consumption of banana inflorescences can provide various health benefits, including improved intestinal function, weight management and reduced risk of cardiovascular diseases. For this work, a bibliographic narrative review was carried out with a focus on the valorization of banana flower residues, exploring its therapeutic and antioxidant potential. The research was developed through the analysis of scientific articles and relevant studies, highlighting the bioactive properties of these by-products and their potential applications in the pharmaceutical and food industries. This review showed that banana inflorescences are rich in phenolic compounds, flavonoids and terpenoids, which have antioxidant, antidiabetic, anti-inflammatory and antimicrobial properties. Therefore, these by-products can be used by the pharmaceutical and food industries and can contribute to the circular economy and sustainable management of agricultural resources.

Exploring the Potential of Macroalgae for Sustainable Crop Production in Agriculture.

Marine macroalgae, which typically colonize coastal areas, are simple plant organisms. They live on rocks in coastal regions and are classified into red, brown, and green macroalgae. These algae are an important natural resource in agriculture due to their ability to enhance the structural, chemical, and biological properties of soil. Marine macroalgae can be used to produce various biocidal molecules that are effective in controlling plant pathogens. Much of the literature on marine macroalgae and their derivatives focuses primarily on the pharmaceutical field, while their use in agriculture is still considered secondary. However, various studies and experiments have demonstrated their potential to play a significant role in crop protection and enhancement. This review aims to highlight the various applications of macroalgae in plant production. It also emphasizes the biotechnological importance of marine macroalgae derivatives as biofertilizers, molecules for controlling insects and microorganisms, and as plant growth conditioners. Compounds from macroalgae, such as fatty acids, carotenoids, polyphenols, and carbohydrates, are being investigated for their fungicidal, antimicrobial, and antiviral effects against various plant pathogens. Beyond enhancing crop production, macroalgae can also be considered multifunctional bioinoculants suitable for use in organic farming.

Оценка обеспеченности человеческим капиталом аграрного сектора экономики

Abstract. The formation and use of human capital in the agricultural economy must meet modern economic requirements and the level of development of agricultural production. The assessment of the efficiency of the use of human resources and the quality of products plays a key role in adapting to changing market conditions. Therefore, it is important to constantly strengthen human resources to ensure a prompt response to market challenges. At the same time, agricultural production is currently undergoing changes in all key areas. This article analyzes the availability and efficiency of the use of agricultural enterprises' labor resources, based on statistical data for the Russian Federation. In this regard, the purpose of this scientific study is to analyze the availability of human capital in agriculture. The objectives of the study include carrying out a qualitative and quantitative assessment of labor resources. Methods. The methodological basis is based on the general scientific principles of a systematic approach. The analysis uses logical, factorial, comparative and strategic methods, as well as methods of qualitative research of the main trends in the presence and use of human capital in agriculture. Results. The analysis of the formation and use of human capital in agriculture in its quantitative and qualitative assessment in the Russian Federation is carried out: the dynamics of rural population density and the number of workers, the growth rate of wages of agricultural workers, the grouping of those employed in agriculture by level of education, gender and age is given. Scientific novelty. As a result of the research, new theoretical and practical conclusions were obtained, including: 1) identification and classification of socio-economic conditions that promote or, conversely, hinder the effective use and preservation of human capital in the agricultural sector; 2) comprehensive schemes for the formation of human capital in the agricultural sector are proposed, taking into account internal and external factors; 3) the need for the formation of a comfortable socio-economic environment in rural areas is justified; 4) confirmed the need to provide special support measures to attract highly qualified specialists to rural areas.

NSEMBLE FINE TUNED MULTI LAYER PERCEPTRON FOR PREDICTIVE ANALYSIS OF WEATHER PATTERNS AND RAINFALL FORECASTING FROM SATELLITE DATA

The accurate prediction of weather patterns and rainfall forecasting is critical for various sectors, including agriculture, disaster management, and water resource planning. Traditional models often struggle to capture the complex interactions between atmospheric variables, particularly when integrating diverse types of satellite data (binary, categorical, and numerical). To address this challenge, an ensemble fine-tuned multi-layer perceptron (MLP) model is developed, combining the strengths of multiple machine learning techniques for more robust predictions. The primary problem is the difficulty in handling mixed data types while maintaining high prediction accuracy. Satellite data, including binary indicators (e.g., cloud presence), categorical features (e.g., cloud types), and numerical variables (e.g., temperature, humidity, and wind speed), provide rich information but require specialized processing for effective forecasting. The proposed method involves fine-tuning an ensemble of MLP models with backpropagation, dropout regularization, and batch normalization to reduce overfitting and enhance generalization. The ensemble integrates predictions from individual MLP models, each trained on different subsets of features (binary, categorical, numerical). This technique allows the model to leverage complementary strengths and produce more accurate rainfall forecasts. Satellite data is preprocessed and normalized before training, and categorical variables are one-hot encoded to ensure compatibility with the MLP architecture. Results from testing on historical satellite weather datasets demonstrate significant improvements in forecast accuracy. The ensemble MLP achieved an accuracy of 91.3%, with a precision of 90.7%, recall of 89.5%, and an F1-score of 90.1%. The model performed exceptionally well in identifying critical rainfall events, reducing false positives by 12% compared to traditional models.

Implicit EXP-RBF techniques for modeling unsaturated flow through soils with water uptake by plant roots

Modeling unsaturated flow through soils with water uptake by plan root has many applications in agriculture and water resources management. In this study, our aim is to develop efficient numerical techniques for solving the Richards equation with a sink term due to plant root water uptake. The Feddes model is used for water absorption by plant roots, and the van-Genuchten model is employed for capillary pressure. We introduce a numerical approach that combines the localized exponential radial basis function (EXP-RBF) method for space and the second-order backward differentiation formula (BDF2) for temporal discretization. The localized RBF methods eliminate the need for mesh generation and avoid ill-conditioning problems. This approach yields a sparse matrix for the global system, optimizing memory usage and computational time. The proposed implicit EXP-RBF techniques have advantages in terms of accuracy and computational efficiency thanks to the use of BDF2 and the localized RBF method. Modified Picards iteration method for the mixed form of the Richards equation is employed to linearize the system. Various numerical experiments are conducted to validate the proposed numerical model of infiltration with plant root water absorption. The obtained results conclusively demonstrate the effectiveness of the proposed numerical model in accurately predicting soil moisture dynamics under water uptake by plant roots. The proposed numerical techniques can be incorporated in the numerical models where unsaturated flows and water uptake by plant roots are involved such as in hydrology, agriculture, and water management.

Woody Grains In Chinese History: The Basis For New Agricultural Policies

Historically, China was not only a large agricultural country, but also a strong agricultural power. Because there were countless types of grains produced in China, it had never been a problem to feed tens of millions of people. After consulting Chinese literature records, we are always surprised to find that, in addition to the wellknown gramineous food crops, there are also many food crops produced from tall arbor or shrub. Such special food crops can be generally referred to as “tree- grains”. In this way, during the long history, the Chinese ancestors could not only have no worry about food, but also ensure an adequate supply of fuel and diversify clothing materials. Because of precisely out of a deep recognition and understanding of the superiority of Chinese traditional culture, the current Chinese government is able to put forward the decision-making on the modern agricultural transformation of establishing large-scale agriculture, large-scale food, and large-scale resources