Agricultural Land Research Articles

High-Resolution Mapping of Topsoil Sand Content in Planosol Regions Using Temporal and Spectral Feature Optimization

Soil sand content is an important characterization index of soil texture, which directly affects soil water regulation, nutrient cycling, and crop growth potential. Therefore, its high-precision spatial distribution information is of great importance for agricultural resource management and land use. In this study, a remote sensing prediction method based on the combination of time-phase optimization and spectral feature preference is innovatively proposed for improving the mapping accuracy of the sand content in the till layer of a planosol area. The study first analyzed the prediction performance of single-time-phase images, screened the optimal time-phase (May), and constructed a single-time-phase model, which achieved significant prediction accuracy, with a coefficient of determination (R2) of 0.70 and a root mean square error (RMSE) of 1.26%. Subsequently, the model was further optimized by combining multiple time phases, and the prediction accuracy was improved to R2 = 0.77 and the RMSE decreased to 1.10%. At the feature level, the recursive feature elimination (RF-RFE) method was utilized to preferentially select 19 key spectral variables from the initial feature set, among which the short-wave infrared bands (b11, b12) and the visible bands (b2, b3, b4) contributed most significantly to the prediction. Finally, the prediction accuracy was further improved to R2 = 0.79 and RMSE = 1.05% by multi-temporal-multi-feature fusion modeling. The spatial distribution map of sand content generated by the optimized model shows that areas with high sand content are primarily located in the northern and central regions of Shuguang Farm. This study not only provides a new technical path for accurate mapping of soil texture in the planosol area, but also provides a reference for the improvement of remote sensing monitoring methods in other typical soil areas. The research results can provide a reference for mapping high-resolution soil sand maps over a wider area in the future.

ДИНАМИКА РАЗВИТИЯ ОТРАСЛИ СКОТОВОДСТВА В РЕСПУБЛИКЕ ХАКАСИЯ

The purpose of research is to study the dynamics of development and the current state of the cattle breeding industry in the Republic of Khakassia to provide the population with milk and meat of their own production. The results of monitoring the number of cattle, gross production of meat and milk, average milk yield per cow per year, meat and milk production per capita in the region are presented. Research was carried out in 2000–2021, the data studied is presented by categories of farms of various forms of ownership. It is noted that cattle breeding is one of the leading livestock sectors in the region. Over the past twenty years, the total number of cattle has increased by 37.1 thousand heads (27.6 %), including cows by 9.7 thousand (15.5 %), gross beef production by 0.8 thousand tons (8.4 %), milk by 6.4 thousand tons (5.2 %). Agricultural organizations currently account for only 11.7 % of beef and 19.7% of milk from their gross production. The average milk yield per cow increased by 1.8 times and amounted to 3637 kg of milk per year, including in agricultural organizations it increased by 3.3 times and amounted to 4431 kg. Milk production per capita in Khakassia in 2021 amounted to 246.3 kg, beef – 19.4 kg, the region's supply of own-produced milk was 75.8 %, beef – 97.0 %. The region has the necessary resources for the development of the industry: the presence of agricultural land of 1911.9 thousand hectares, including 826.4 thousand hectares of pastures, types of beef cattle have been created (Sonsky, Andrianovsky) adapted to local feeding and climatic conditions. An increase in milk and meat production must be achieved through an increase in the number of cattle in agricultural organizations and peasant (farm) farms, improvement of existing breeds and types, strengthening the food supply and a scientific approach to feeding and keeping animals.

Health and environmental risk due to acid mine drainage generating tailings in Zimapán, Mexico

Abstract In the mining district of Zimapán, located in the State of Hidalgo, Mexico, high concentrations of potentially toxic elements such as arsenic (As), lead (Pb), and cadmium (Cd), and Acid Mine Drainage (AMD) have been detected in tailing’s dams. This AMD, along with the population growth in the region, has reduced the distance between mining waste sites and urban areas, increasing the risk of exposure to these contaminants for living organisms. The objective of this study was to evaluate AMD generation and the risk to human health and the ecosystem due to potential exposure to elements present in the AMD, using the Spatial Analysis and Decision Assistance (SADA) software in three mining areas of Zimapán. Soil sample analyses revealed that the total concentrations of Pb, Cd, and As exceeded the maximum limits allowed by Mexican standard NOM-141-SEMARNAT-2003 for residential and agricultural land use. Additionally, the SADA model results demonstrated a potential risk to human health and mammals and birds due to their interaction with concentrations of 12,198 mg/kg of As and 4,618 mg/kg of Pb, respectively. The SADA model played a crucial role in enabling the quantification of the potential risk to the exposed population, thereby becoming an essential tool for the environmental management of this and other mining districts.

Transforming US agriculture for carbon removal with enhanced weathering.

Enhanced weathering (EW) with agriculture uses crushed silicate rocks to drive carbon dioxide removal (CDR)1,2. If widely adopted on farmlands, it could help achieve net-zero emissions by 20502-4. Here we show, with a detailed US state-specific carbon cycle analysis constrained by resource provision, that EW deployed on agricultural land could sequester 0.16-0.30 GtCO2 yr-1 by 2050, rising to 0.25-0.49 GtCO2 yr-1 by 2070. Geochemical assessment of rivers and oceans suggests effective transport of dissolved products from EW from soils, offering CDR on intergenerational timescales. Our analysis further indicates that EW may temporarily help lower ground-level ozone and concentrations of secondary aerosols in agricultural regions. Geospatially mapped CDR costs show heterogeneity across the USA, reflecting a combination of cropland distance from basalt source regions, timing of EW deployment and evolving CDR rates. CDR costs are highest in the first two decades before declining to about US$100-150 tCO2-1 by 2050, including for states that contribute most to total national CDR. Although EW cannot be a substitute for emission reductions, our assessment strengthens the case for EW as an overlooked practical innovation for helping the USA meet net-zero 2050 goals5,6. Public awareness of EW and equity impacts of EW deployment across the USA require further exploration7,8 and we note that mobilizing an EW industry at the necessary scale could take decades.

Indigenous knowledge to deter elephants damaging crop lands

Elephant and man conflict is becoming more and more common problem in Sri Lanka. As there is no solution, poor farmers face severe crops losses due to elephant attacks. Electric fences were also not effective due to rise in electricity cost and elephants get used to these methods and there are no effective methods so far. According to several ancient literature man elephant conflict was controlled by traditional and indigenous methods. Therefore, extensive literature surveys on research articles, ancient authentic texts, ancient books and news articles were conducted. Furthermore, focus group discussions with farmers were carried to extract information on the most successful methods to deter elephants from crops lands. Several successful methods were extracted and presented here in this paper to disseminate this valuable indigenous knowledge into the present generation. Methods identified were Beehive fences in the border of the farmland and when elephant touches the wires the disturbed swarm of bees attaches the elephant get into the crop’s fields. Buffers of cultivation of Chili, which is an irritant, causing elephants to cough, sneeze and eventually turn away from the crop field. Vegetable buffer zones with unpalatable crops such as sisal (Agave sisalana), chili (Capsicum frutescens) tea (Camellia sinensis), ginger (Zingiber officinale), mustard (Brassica nigra) or oilseed (Brassica napus) is another method. These unpalatable crops may not necessarily deter the elephants, but these crops will not be raided and therefore the farmers’ livelihood is ensured. When elephants crush the mustard plants, they feel the strong smell which the elephants do not like, and they turn back and go away. In addition, these crops will provide additional income to the farmers. Acoustic deterrents were used widely which are noises used to deter elephants, either by the shock value of an unexpected loud noise, or by specific noises that are known to scare elephants. Acoustic deterrents are disturbance shooting, elephant communication and Tigers on tape are few of them. Chemical deterrents such as chilli powers and chilli pasted robes are also used effectively. Physical barriers such as trenches, bamboo spike, sharp stones are also used to deter elephants. As the conclusion the above mentioned traditional and indigenous methods could be practiced with less cost and it will also be possible to gain additional income other than the main crop.

CAMELS-IND: hydrometeorological time series and catchment attributes for 228 catchments in Peninsular India

Abstract. We introduce CAMELS-IND (Catchment Attributes and MEteorology for Large-sample Studies – India), a dataset containing hydrometeorological time series and catchment attributes for 472 catchments in Peninsular India, of which 228 catchments have observed streamflow data available for over 30 % of the period between 1980 to 2020. Peninsular India covers 15 interstate river basins defined by the Central Water Commission (CWC), where river flow and water level datasets are available for several gauge stations through the open-source India Water Resources Information System (India-WRIS). However, many of these gauge stations lack reliable metadata, and data are not in an analysis-ready format for large-sample hydrological studies. Therefore, we utilized 472 gauge stations and their catchment boundaries, characterized as stations with reliable metadata, from the Geospatial dataset for hydrologic analyses in India (GHI) (Goteti, 2023). For each of these catchments, CAMELS-IND provides a catchment mean time series of meteorological forcings for 41 years (1980–2020) and 211 catchment attributes representing hydroclimatic and land cover characteristics extracted from multiple data sources (including ground-based observations, remote sensing-based products, and reanalyses datasets). CAMELS-IND follows the same standards of the previously developed CAMELS datasets for the USA, Chile, Brazil, Great Britain, Australia, Switzerland, and Germany to facilitate comparisons with catchments of those countries and inclusion in global hydrological studies. Notably, CAMELS-IND includes available observed streamflow and catchment mean time series of 19 meteorological forcings, including precipitation, maximum, minimum, average temperature, long-wave and short-wave radiation flux, U and V components of wind, relative humidity, evaporation rates from canopy and soil surface, actual and potential evapotranspiration, and soil moisture of four layers (covering depth up to 3 m below ground) for detailed hydrometeorological studies. We also derived catchment attributes representing human influences, including the number of dams and their utilization, total volume contents of dams in catchments, population density, and increases in urban and agricultural land covers to facilitate studies to understand human influences on catchment hydrology. Furthermore, the dataset includes predicted streamflow time series from a regionally trained long short-term memory (LSTM)-based hydrological model for all 472 catchments which can fill gaps in observed streamflow data or serve as a benchmark for testing and developing new hydrological models. We envision that CAMELS-IND will provide a strong foundation for a community-led effort toward gaining new hydrological insights from hydrologically distinct Indian catchments and solving pertinent issues related to water management, quantification and risk assessment of hydrologic extremes, unraveling regional-scale hydrologic functioning, and climate change impact assessment of catchments across India. The CAMELS-IND dataset is available at https://doi.org/10.5281/zenodo.14005378 (Mangukiya et al., 2024).

Synthesis on the Impact of Land Cover Conversion towards Water Quantity and Quality

This research intends to establish a policy on watershed management based on the land use recommendation and an analysis of land cover conversion to per-urban location towards water quality and discharge which many sub-watersheds in Indonesia are in critical condition due to the frequent event of flooding, drought, and landslide. It is further worsened by the changes of land cover in the watershed that causes to increase in surface runoff which also affects the water quality in the watershed. Watershed condition can be restored by management if the correct implementation and regulation is effective. Out of 458 watersheds in Indonesia, 60 of them were very critical, 222 were critical, and the remaining 176 were in endangered condition. One of the critical watersheds is Ciliwung watershed. Furthermore, public participation is a key in managing watershed. The methodology consists of collecting the primary data as a benchmark for simulation by using SWAT; the regression model is used for covering the water quality while the water discharge analysis is performed through hydrological simulation. Then socio-economic survey is conducted to evaluate public willingness and capacity to participate in the watershed management. The result of simulation shows that sediment and nitrate is positively affected by water discharge while phosphate is negatively affected by it. The conversion of forest into agriculture significantly increases the nitrate and sediment production in while phosphate is not really affected. Meanwhile, in the watershed overall, surface runoff, nitrate, and phosphate are increasing drastically. The result of survey shows that most people that are living in the watershed do not have the funding or yard to participate in the watershed management. This result is a recommendation which reduces the agriculture land use by 10% and allocating it for water management.

Engaging Sustainable Reforestation and Forest Protection in the Wallacea Line, Indonesia

The Wallacea region of Indonesia has high biodiversity and highly unique and endangered species. Its terrestrial ecosystems have unique flora and fauna found nowhere else. Nevertheless, the strategy for protecting and conserving the Wallacea ecosystem is like that in other parts of Indonesia, since it refers to the national forest and environmental regulations. The uniqueness of the Wallacea ecosystem does not reflect the extraordinary efforts of protecting and conserving the region’s pristine ecosystem. The continuing decline of the forestland and expansions of agricultural lands have indicated the need for a more fundamental and integrative approach to conserving and protecting the Wallacea ecosystem, particularly forestlands. We use the actor-centered power (ACP) approach or ideas and use the Wallacea Line to highlight how this idea is contested and confronted with the dynamics of complex societies and ecosystems. The ACP approach is the most widely used one in the implementation of the community forest (CF) program in Indonesia. The CF program is one of Indonesia’s community-based forest management schemes that empowers local communities to manage state forests sustainably. We chose two national parks established in the Wallacea region, Mutis on Timor Island and Matalawa on Sumba Island, to elaborate further on the development, conservation, and changes that occurred within that landscape. The ACP approach, in line with the spirit of the decentralization era, has mixed consequences for forest management and the biodiversity of the Wallacea region. Regarding the specific characteristics of the Wallacea region and lessons learned from the ACP approach implementation in the CF program, we then propose a sustainable model of reforestation and forest protection that applies the principle of “unity in diversity,” where all actors involved have space for the growth of creativity and positive contributions to sustainable forest protection.

Vine Pruning Residues and Wine Fermentation By-Products: A Non-Exploited Source of Sustainable Agriculture, Albania Case

Albania, situated in southeastern Europe, enjoys a Mediterranean climate that is well-suited for grape cultivation. The vineyard area totals 7.202 million hectares. Since the 1990s, the country has experienced a resurgence in its rich winemaking traditions, which have gained considerable attention over the last decade. Alongside its significant wine production, large amounts of vine pruning waste and fermentation by-products are generated, estimated at over 50,000 t of prunings and 35,900 t of grape pomace annually. This waste is often burned, and the ash is used as fertilizer, releasing considerable CO2 emissions, and contributing to greenhouse gas levels. However, recycling these prunings into fertilizer by chipping and grinding them in the vineyard presents a sustainable choice, providing key minerals, nitrogen, phosphorus, and various micronutrients, thereby reducing the dependence on synthetic fertilizers in farming. Characterized by small plantations, the vine pruning issue needs site-specific, economically feasible solutions for the farmer. Additionally, there is unexplored potential for applying wine fermentation pressing residues as fertilizer for agricultural land or vineyards. The Albanian wine sector has significant untapped opportunities, such as employing vine pruning ash as a mineral fertilizer to help achieve sustainability goals.

Environmental degradation and food security in Somalia

Somalia grapples with significant land degradation due to soil erosion, deforestation, and overgrazing. These environmental stressors diminish agricultural productivity, further exacerbating food insecurity among the population. This study examines the impact of environmental degradation on food security in Somalia. The autoregressive distributed lag (ARDL) model was utilized with annual time-series data from 1990 to 2019. The empirical results show significant negative impacts of environmental degradation and gross domestic product (GDP) on food security, persisting in the short and long terms. However, population growth was found to have an insignificant effect on food security. Notably, while agricultural land expansion exhibits a negative effect in the short term, it emerges as a positive contributor to food security in the long term, highlighting its pivotal role in bolstering production capacity. The study suggests policy reform to prioritise initiatives for sustainable land management, focusing on reforestation, soil conservation, and watershed management. These practices are critical for mitigating environmental degradation, preserving natural resources, and enhancing the resilience of agricultural systems to climate change.

The Changes in Grassland Animal Husbandry and Herdsmen’s Life in the Qinghai Pastoral Area of China Based on the Perspective of Changes in the Grassland Property Rights System

Based on the historical background of the changes made to the grassland property rights system, the first part of this study restores the changes in property rights systems in six major autonomous counties of grassland animal husbandry production in Qinghai region, while the second part qualitatively analyzes the changes in grassland animal husbandry operations and herdsmen’s life under the changes in property rights. The results show that, with the reform of the property rights system, the range of livestock grazing has changed from large-scale nomadic grazing to regional rotational grazing. The herds are mainly yaks and Tibetan sheep, accounting for more than 90%, with the proportion of Tibetan sheep being higher than that of yaks. The numbers of total livestock and those on the market first rose and then declined, showing a dynamic balance in recent 10 years, while the number of breeding female animals has increased year by year. Artificial grass planting has gradually become popularized in pastoral areas. The time span of livestock supplementary feeding has increased and is more scientific, and the output value of animal husbandry has increased year by year, showing a strong peak associated with intensification. The proportion of the population engaged in animal husbandry has decreased gradually with increasing population in the region. The income sources of herdsmen have become more and more diversified and are increasing year by year, and the Engel coefficient presents a downward trend. The human environment in pastoral areas has improved. Based on the above analysis, suggestions for the sustainable and high-quality production of animal husbandry under the current grassland property rights system are put forward, as well as for the construction of green organic agricultural and livestock product export land in Qinghai Province.

Impact of Environmental Factors of Stream Ecosystems on Aquatic Invertebrate Communities

Understanding the responses of stream ecosystems to environmental disturbances is essential for maintaining and restoring healthy ecosystems. In this study, we analyzed the associations between benthic macroinvertebrate communities and environmental factors using machine learning approaches to identify key stressors potentially influencing stream ecosystem health. Various machine learning models were evaluated, with random forest (RF) and gradient boosting machine (GBM) identified as the optimal models for predicting tolerant species (TS) and Ephemeroptera, Plecoptera, and Trichoptera (EPT) species densities. SHAP analysis revealed that watershed variables, such as elevation, flow velocity, and slope, significantly influenced EPT and TS populations. EPT population density increased with elevation and flow velocity but decreased significantly with higher levels of biochemical oxygen demand (BOD), total nitrogen (TN), and agricultural land-use proportions, with negative effects becoming evident beyond threshold levels. Conversely, TS population density showed a positive response to elevated BOD, TN, and agricultural land-use proportions, stabilizing at the threshold levels of BOD and TN, but continuing to increase with greater agricultural land use. Through machine learning, this study provides critical insights into how environmental variables are associated with the distribution of benthic macroinvertebrate communities. By identifying threshold levels of key stressors, this approach offers actionable guidance for managing agricultural runoff, enhancing riparian buffers, and implementing sustainable land-use practices. These findings contribute to the development of integrated watershed management strategies that promote the long-term sustainability of stream ecosystems.

Shorter growing seasons may moderate climate change effects on crop water demands

Abstract Rising evaporative demand (ETo) with a warming climate contributes to diminished water availability in water-stressed agricultural regions globally. While increased ETo typically necessitates increased irrigation, we explore how crop phenological response can moderate this challenge. Focusing on five key agricultural crops in California’s San Joaquin Valley, we employ coupled water balance and phenology models to project crop water demands as a function of increased ETo and changing phenology. All crops exhibited accelerated growth from a shortened growing season with warming. The shortened crop maturation period partially to fully offset increased crop water demands due to rising ETo, with the largest phenological influence for annual crops such as tomato and corn. By contrast, models that do not account for phenological changes showed increased irrigation demands of approximately 3.5-4.5% per °C of global warming primarily due to increased ETo. Integration with dynamic phenological models for the five key crops across the extent of agricultural land in the San Joaquin Valley showed a 1.6% decrease in irrigation needs under a 2°C warming scenario. While phenological change alongside plant physiological responses to increased atmospheric CO2 may help buffer the impact of climate change on crop irrigation demand, decreased crop yields with a shorter growing season and continued reliance of groundwater reserves for agricultural water use and reduced spring snowpack will threaten coupled agricultural and water security in the region.

Динамика земельного фонда Российской Федерации и Краснодарского края по категориям земель, составу и площади сельскохозяйственных угодий

The presented study is aimed at quantifying the dynamic characteristics of the land fund of the Russian Federation and the Krasnodar Territory in the period from 2018 to 2023. The work analyzes statistical data characterizing the distribution of land by category, changes in the composition and area of agricultural land. The methodological approach used makes it possible to identify spatial and temporal trends and differentiate them at the level of the territorial units under consideration. An analysis of official data from the State (national) Land Status and Use report revealed key trends in land transformation by category and agricultural land. At the federal level, there is a steady tendency to reduce agricultural land in parallel with an increase in the areas of specially protected natural territories and forest resources. This situation requires careful analysis from the point of view of ensuring the country's food security. In the Krasnodar Territory, known as a region with intensive agricultural production, an in-depth analysis of the dynamics of land categories revealed the main trends, taking into account possible causal factors affecting changes in the structure of land use. The results obtained made it possible to evaluate the effectiveness of existing land use strategies and identify potential ways to increase the area of agricultural land. Based on the analysis, specific recommendations are formulated to optimize spatial development both for the whole country and for the Krasnodar Territory, identifying the goal as sustainable and efficient use of land resources. Further research should focus on clarifying the contribution of individual factors and developing adaptive land-use strategies taking into account changing climatic conditions.

Modelling and Estimation of Average Annual Soil Loss in Ika South Local Government Area of Delta State, Nigeria

Soil-related phenomenon and the Sustainable Development Goals (SDGs) particularly SDG-15 are strictly tied. A healthy soil ecosystem encourages the existence of life on Earth and for agricultural purposes. One of the key factors that is contributing to unhealthy soil ecosystems is soil erosion. The research involves the assessment and modelling of soil erosion using the Revised Universal Soil Loss Equation (RUSLE II) with the sole aim of ascertaining the annual Soil loss within the study area, this will be a veritable tool in estimating soil loss in farming systems and in supporting the achievement of the SDGs. It provides a concrete estimation of the distribution of soil erosion at Ika South LGA, through the combination of the influencing factors such as rainfall aggressivity, soil erodibility, topography, vegetation cover, and soil conservation practices. The soil loss estimated at Ika South ranges from 0 to 49119.93 t/ha/year. Results have shown that 5% of the surface area displays a high rate of soil loss, and it represents zones with moderate to severe soil erosion. These areas are mainly situated in moderate to very high slope where the runoff is high. This loss is favoured by the other factors of erosion, which are also combined to accelerate erosion losses significantly (58% of the total area has a very high rainfall erosivity), moderately erodible soils (49% of the soils show a K factor between 0.128 and 0.27t ha H/ha MJ mm), 78% of the soil have nearly level to gently undulating plains, and 14% of the areas representing steep slopes. The results revealed that, there is a probability that the rate of erosion will increase in the future in this area which pose a great threat to the achievement of the SDG-15. Therefore, proper land-use planning should be adopted such as cropping pattern for agricultural land in local area. Accurate planning should be done as a means for restoring degraded vegetation.

Factors affecting the net ecosystem productivity of agroecosystems on mineral soils: a meta-analysis

ABSTRACT To optimize agricultural land management for soil carbon sequestration, it is necessary to identify whether agroecosystems are accumulating or gaining carbon. This can be done by determining an agroecosystem’s net ecosystem productivity (NEP). This study collated data from 40 papers, containing 242 annual measurements of NEP, to assess the impact of climate, soil type and management on the annual NEP of croplands and managed grasslands. Croplands lost significantly more carbon (110 g Cm−2) than managed grasslands (29.9 g Cm−2) and there was little statistical influence of climate, soil, or management practice on annual NEP. For agroecosystems to sequester carbon, there should be a shift in focus toward implementing management practices that increase carbon retention within agroecosystems.

Water Consumption, Quantity and Quality of Wastewater and Sewage Sludge from Polish Dairies

The peculiarity of the wastewater produced in Polish dairies stems from the frequency and specific technology of cottage cheese production. The aim of this study was to determine the water consumption and the quantity and quality of wastewater and sewage sludge discharged from Polish dairies based on the size of the plant and the production profile of the plant to characterize the wastewater treatment plants (WWTPs). Data were collected from eighteen dairies. Most of them have their own WWTP. Water consumption ranged from 1.5 litres (L) of water per litre of milk processed to 3.71 L/L. The specific volume of wastewater ranged from 1.18 to 5.78 L per L of milk processed. The raw wastewater concentrations were comparable to those of dairy wastewater in other European countries. Despite the disposal of domestic wastewater in WWTPs, the results of the sanitary examinations of the sludge showed it was suitable for agricultural purposes. Its heavy metal also made it applicable on agricultural land. The ratio of the sludge to raw milk processing was between 0.137 and 7.927 kg of sludge per 100 L of milk processed. The amount of sludge produced per pollutant (BOD) load removed ranged from 0.404 to 18.895 kg/kg BODremoved.

Integration of Deep Learning with Fox Optimization Algorithm for Early Detection and Classification of Tomato Leaf and Fruit Diseases

Tomato is a common vegetable crop extensively cultivated in the farming lands in India. The hot climate of India is perfect for its development, but particular weather conditions along with many other aspects affect the growing of tomato plants. Apart from these natural disasters and weather conditions, plant diseases consist a major issue in crop production. Precisely classifying leaf and fruit diseases in tomato plants is a vital step toward computerizing processes. Traditional disease detection models for tomato crops often fall short in predictability. To address this, Machine Learning (ML) and Deep Learning (DL) models have been developed, presenting advanced classification capabilities and the ability to manage the vast variability in agricultural data that conventional computer vision models struggle with. This work presents an Integration of DL with Fox Optimization Algorithm (FOA) for the Recognition and Classification of Tomato Leaf and Fruit Diseases (IDLFOA-DCTLFD). The major objective of the proposed IDLFOA-DCTLFD model is to enhance the detection and classification outcomes of tomato leaf and fruit diseases. At the initial stage, the Median Filter (MF) model is used for pre-processing and the Efficient Channel Attention-SqueezeNet (ECA-SqueezeNet) model is employed for feature extraction. For the hyperparameter tuning process, the proposed IDLFOA-DCTLFD technique implements the FOA. Finally, a Wasserstein Generative Adversarial Network (WGAN) is utilized for the detection of tomato leaf and fruit diseases. The IDLFOA-DCTLFD method is experimentally examined in a tomato leaf and fruit dataset. The experimental validation of the IDLFOA-DCTLFD methodology portrayed a superior accuracy value of 98.02%, surpassing the existing techniques.

Analysis of the Seasonal Change on the Sediment Transport in the Primary Channel of Saddang Irrigation Area

Irrigation channels are a vital component of an agricultural system, functioning to distribute water to agricultural land and support food security. The Saddang irrigation area, one of the main irrigation regions in Indonesia, plays a crucial role in enhancing agricultural productivity. However, the sediment accumulation in irrigation channels can significantly impact water distribution efficiency and environmental quality. The current research aims to analyze the influence of flow parameters during the rainy and dry seasons, examine the relationship between seasonal changes and sediment transport, and assess the impact of sediment discharge in the primary channel of the Saddang irrigation area. The tests conducted included sieve analysis, specific gravity, sediment concentration, and hydrometer analysis. Based on the research results, the average sediment discharge during the rainy season in the primary channel of the Saddang irrigation area is 2,702 tons/day, while during the dry season, the average sediment discharge is 100 tons/day. The ratio of the average sediment discharge between the rainy and dry seasons is 27:1. Additionally, linear equations were obtained to predict sediment discharge in the primary channel of the Saddang irrigation area. For the rainy season, the linear equation used is y = 857.67x - 1618.3, while for the dry season, it is y = 38.811x - 79.937. These equations have a validation rate of 98% between the linear equation and the actual calculation results, indicating high accuracy in modeling sediment discharge in the channel.

Influence of the Doyang Hydro Electric Project on land use land cover, land surface temperature and socio-economic conditions in Wokha district, Nagaland: India

ABSTRACT The Doyang Hydro Electric Project (DHEP) with a 75 MW power generation capacity was completed in 2000 on the Doyang river at Wokha district of Nagaland, India. This study analyses the changes in land use and land cover (LULC) and land surface temperature (LST) in the district from 1991 to 2021. Six LULC classes were analysed: forest land, water body, urban body, agricultural land, barren land, and shifting cultivation using supervised classification. The findings indicate significant LULC changes over the 30-year period. Urban areas expanded by 198.44%, from 10.42 km2 in 1991 to 31.15 km2 in 2021. Forest cover declined by 2.85%, while water bodies saw a dramatic increase of 133.3%. The regression analysis reveals a strong correlation between LULC changes and LST, with urban and barren lands contributing to higher temperatures, while forested areas, water bodies, agricultural lands, and shifting cultivation are associated with lower LST. A household survey conducted in three villages influenced by the DHEP revealed substantial socio-economic, agricultural, and environmental impacts. A paired sample t-test confirmed a significant decrease in agricultural activity, with a p-value of 0.000. These findings highlight the need for sustainable land management practices and consideration of socio-environmental impacts of large-scale infrastructure projects.