Agricultural Season Research Articles

Integrating temporal-aggregated satellite image with multi-sensor image fusion for seasonal land-cover mapping of Shilansha watershed, rift valley basin of Ethiopia

Accurate land-cover mapping in regions with frequent cloud-cover and rapidly changing agricultural land cover by crop growth cycles cannot be guaranteed by use of single sensor images, or an image from a single-acquisition-date. This study addressed these challenges by applying temporal-aggregation of single sensor image features that is integrated with multi-sensor image fusion. Results of land-cover classification target fallow, growing, and harvest/post-harvest agricultural seasons. Satellite based features used were frequency bands of Sentinel-1 (S1) and Sentinel-2 (S2), including vegetation indices (VIs) and biophysical variables (BPVs). Temporal aggregation improved classification accuracy. The single-acquisition-date S2 image, overall accuracy (OA) ranged from 0.81 to 0.85, increased to 0.86 to 0.87 after temporal-aggregation. Meanwhile, for single-acquisitions of S1, OA ranged from 0.44 to 0.79 increased to 0.6 to 0.86 across respective seasons. Fusing temporally aggregated S1 and S2 image features including VIs and BPVs increased OA up to 0.90. Selecting 11, 8, and 10 out of 18 optimum numbers of features for fallow, growing, and harvest/post-harvest seasons respectively improved OA by 3%, 2%, and 1.86%. PCA fusion of the temporally aggregated best performing feature set enhanced harvest/post-harvest season, fallow, and growing seasons with OA of 0.98, 0.96 and 0.94 respectively. Accuracy was enhanced when selecting different best performing feature set for the three seasons. The study enhanced knowledge of advanced remote sensing for agricultural land cover mapping, with practical implications of land monitoring and management.

Meaningful climate change communication: an analysis of women dry season farmers in Kuliyaa community of Ghana

ABSTRACT Access to climate change information can play a critical role in helping rural women adapt to climate change. Our research investigates the communication channels used for climate education among female dry-season farmers in the Kuliyaa community of northern Ghana. Particularly, we address access to climate change information among smallholder female farmers. We adopted a community-based participatory approach to guide the study. To achieve our research objectives of investigating climate change communication channels among smallholder female farmers, specific methods of in-depth interviews and focus group discussions were used to gather knowledge from smallholder female farmers. The research findings provide a well-rounded exploration of the unique climate change communication challenges female farmers face and the innovative approaches they have adopted to share climate change information. Specifically, the findings show that women have adopted innovative oral communication channels to disseminate and transfer climate knowledge among themselves. We also found that there is limited access to radio in the Kuliyaa community making them resort to group meetings to share knowledge and ideas empowering them economically in other livelihoods. The study discovered the community utilises gender inclusivity in decision-making. We recommend that the government and other relevant organisations to develop and implement a strategic policy on climate information dissemination with a focus on supporting farmers in rural communities of Ghana to mitigate climate change effects. Technologies can also be developed to aid in disseminating relevant information to farmers in rural areas as the available oral communication is less effective in disseminating useful information on climate change.

An adaptive neuro-fuzzy inference system-based irrigation sprinkler system for dry season farming

In recent years, the management of irrigation systems has emerged as one of the most pressing concerns in the agricultural industry, especially in areas that experience dry seasons. In this research, an adaptive neuro-fuzzy inference system (ANFIS)-based irrigation system that uses a hot and cold sprinkler mechanism is presented. The goal of the system is to reduce the amount of water needed for farming and increase crop output during dry seasons. Adaptive control of water release is achieved via the use of MATLAB and the ANFIS model. This is done in response to changes in soil moisture, ambient temperature, and crop water demand. According to the findings, the suggested system performs noticeably better than conventional irrigation methods in terms of both the amount of water used and the number of crops produced.

Understanding non-permanent mobility: Factors influencing resident movement in Racang Welak Village, Welak Subdistrict, West Manggarai Regency

Background: The factors of mobility in this study refer to the push and pull factors influencing the non-permanent mobility of the residents of Racang Welak Village, Welak Subdistrict, West Manggarai Regency. Most of the residents in Racang Welak Village are seasonal farmers. Non-permanent mobility is influenced by good accessibility and sufficient access to technology. The area of Racang Welak Village cannot fully meet the needs of the local community, leading them to seek employment outside their area despite the strategic potential of Racang Welak to boost their economy. Method: The objectives of this study are to identify the factors that cause the residents of Racang Welak Village, Welak Subdistrict, West Manggarai Regency, to engage in non-permanent mobility. This research is a descriptive qualitative study. Data collection methods include observation, interviews, and documentation. The sample consists of residents of Racang Welak Village who participate in non-permanent mobility. Result: The results of this study show that the fertile soil conditions in Racang Welak Village allow for the cultivation of various types of crops, resulting in many residents working as seasonal farmers. Seasonal farmers whose needs are not met locally often seek information about job opportunities elsewhere. With information received from family members in the destination area, the residents of Racang Welak Village decide to work in other regions without the initial intention to settle there. Conclusion: The push factors for non-permanent mobility among Racang Welak residents include unmet needs in their home area. Despite having to bear transportation costs, they still choose to engage in non-permanent mobility. The pull factors include a pleasant environment, good social interactions, and job opportunities obtained through relatives in the destination area. Additionally, the work locations are strategic and offer jobs that match their professional skills, resulting in higher incomes. Novelty/Originality of this study: This research aims to identify the push and pull factors of non-permanent mobility and how the inability to meet local needs drives residents to seek employment outside the region. These findings apply to designing local economic development policies that can reduce dependence on non-permanent mobility by increasing job opportunities and accessibility in the region of origin.

Calculating Costs and Marketing Margins for Summer Vegetable Crops Under the Protected Agriculture System in Baghdad Governorate for the Agricultural Season 2022/2023

Calculating Costs and Marketing Margins for Summer Vegetable Crops Under the Protected Agriculture System in Baghdad Governorate for the Agricultural Season 2022/2023

Organophosphate insecticide exposure and respiratory symptoms among school children in Northern Thailand: Interaction by biomass burning, dampness and season

The aim was to study associations between dialkylphosphates (DAPs), organophosphate (OP) metabolites in urine, biomarkers of OP insecticide exposure, and respiratory symptoms among children in upper northern Thailand. We recruited junior high school children in randomly selected schools in four cities (N = 337), with repeated data collection in wet and dry seasons. Urine was collected and analyzed for six OP metabolites, with creatinine adjustment. Total DAP was expressed as sum of DAPs. Data on respiratory symptoms was collected by a standardized questionnaire. Associations were analyzed by multiple logistic regression. Totally 11.3 % lived in farm families. Total DAPs concentration was higher in dry season (p = 0.002) but did not differ between farm and non-farm children. Total DAPs in wet season was associated with current wheeze (p = 0.019), current asthma attacks (p = 0.012) and attacks of breathlessness in last 12 months (p = 0.021). Total DAPs in dry season was associated with current wheeze (p = 0.042), and associations between DAPs and respiratory symptoms were stronger for dimethylphosphate metabolites (DMPs) than for diethylphosphate metabolites (DEPs). DMPs are produced by certain OP pesticides. Biomass burning inside or outside the home, and dampness or mold at home, enhanced the association between total DAPs and attacks of breathlessness.In conclusion, OP pesticide exposure, measured as urinary DAPs, was higher in dry season and similar in farm and non-farm children. OPs exposure, especially to DMP related pesticides, can increase asthmatic symptoms, especially in wet season. Combined exposure to OP and smoke from biomass burning, or dampness and mold, can further increase the prevalence of attacks of breathlessness. There is a need to reduce OP insecticide and biomass smoke exposure among Thai children. Since different pesticides can be used in different seasons, studies on respiratory health effects of OPs pesticide exposure should be done in different seasons.

Effect of Fertilizer With Potassium Humate and the Method of Addition to the Growth and Yield of Red Cabbage

Background: The application of potassium humate has been recognized for its potential to enhance plant growth and yield due to its nutrient enrichment properties. Specific Background: Despite extensive research on various fertilizers, the specific effects of potassium humate on red cabbage (Ruby King cultivar) growth and yield, especially concerning the method of application, remain underexplored. Knowledge Gap: Limited studies have addressed the comparative impact of foliar spraying versus soil addition of potassium humate on cabbage vegetative growth and yield characteristics. Aims: This study aimed to evaluate the effects of different concentrations of potassium humate (0, 50, 100, 150 g.l-1) and application methods (foliar spraying and soil addition) on the growth and yield of red cabbage. Results: A randomized complete block design (RCBD) with three replications was implemented during the 2022-2023 agricultural season. Significant improvements in vegetative growth and yield were observed with the highest concentration (150 g.l-1) of foliar spraying. Key vegetative and yield parameters, such as plant height, stem length, number of leaves, leaf chlorophyll content, average head weight, and total yield, were positively influenced. Novelty: This study uniquely highlights the superior efficacy of foliar spraying with potassium humate at 150 g.l-1 over soil addition, providing insights into optimizing fertilization strategies for red cabbage. Implications: The findings advocate for the use of potassium humate, particularly via foliar spraying, as a beneficial organic fertilizer to enhance red cabbage growth and yield. This practice could lead to improved agricultural productivity and better tolerance of plants to environmental stresses, supporting sustainable agriculture initiatives. Highlights: Superior Growth: Foliar spraying with 150 g.l-1 potassium humate boosts growth. Yield Increase: Highest humate concentration yields maximum red cabbage. Effective Strategy: Foliar spraying outperforms soil addition for fertilization. Keywords: Potassium humate, foliar spraying, red cabbage, vegetative growth, yield enhancement

Spatial Durbin Model with Expansion Using Casetti’s Approach: A Case Study for Rainfall Prediction in Java Island, Indonesia

Research on rainfall is critically important due to its significant impact on climate change and natural disasters in Indonesia. Various factors influence rainfall variability. Consequently, when examining spatial aspects, it is likely that spatial dependency exists not only in the response variable but also in the exogenous variables. Hence, a model that accounts for spatial dependencies between these variables is required. The integration of the Spatial Durbin Model (SDM) with Casetti’s expansion approach can be utilized to predict spatial patterns of rainfall influenced by exogenous variables. By incorporating spatial effects and relevant independent variables, this model can provide more precise estimates of rainfall distribution across different regions. This modeling technique is particularly effective for accurate rainfall prediction, considering exogenous factors such as air temperature, humidity, solar irradiation, and surface pressure. The SDM with Casetti’s expansion approach was employed to predict rainfall patterns in the Java Island region, utilizing data from the National Aeronautics and Space Administration’s Prediction of Worldwide Energy Resources (NASA POWER) big data website. The application of this model in the context of rainfall prediction highlights its importance in enhancing the understanding of weather dynamics and aiding disaster risk mitigation in Java Island, a highly populated region characterized by a Monsoon rainfall pattern. The rainfall prediction follows a Knowledge Discovery in Databases (KDD) methodology. The results of this study are expected to be valuable to relevant agencies, such as the Meteorology, Climatology, and Geophysics Agency (BMKG), and agribusiness companies, improving agricultural planning and planting seasons. Additionally, the general public can benefit from more accurate climate information, particularly regarding rainfall. The computational framework is developed within an RShiny web application, and the performance of the proposed technique is measured by the Mean Absolute Percentage Error (MAPE), achieving a very accurate prediction rate of 2.78%.

Adaptive extreme learning machine using soft computing fuzzy propositions—Validating operating state of solar energy system

In this paper soft computing fuzzy proposition/rule based adaptive extreme learning is proposed. This article illustrates the impact of agricultural solar panel (AgSP) and its operating condition/state during the farming seasons and hence safety of energy system sustained. Extreme learning machine (ExLM) used as learning machine (LM) for artificial intelligence (AI) training to predict the operating state of applied AgSP green energy unit. soft computing Fuzzy rules are framed for every instant of leaning machine to identifying the lower mismatch conditions and avoid the false prediction. Higher and lower limits of adaptive resonance theory (ART) support LM (ART-LM) is properly used by providing unusual dust formation (UnDFR) data and usual/normal dust formation (UsDFR) data for AI training. Outcome of AI neural net is determined by resonant neuron net (RSNN). Predicted variable from ART-LM is calculated with higher and lower limits of dataset captured from applied energy common node (CN). Many test conditions of dust formation on solar photovoltaic (PV) has been validated to predict the state of applied energy system. For any UnDFR confirmation, entire AgSP based distributed generator (DG) unit will isolate from common node/utility grid. Proposed ART-LM based AI algorithm has been validated even for charging state events of electrical vehicle (EV) during the abnormal conditions.

Influencing mechanism of farming clams on the CO2 flux from aquaculture ponds: Insights from ecosystem carbon metabolism

Aquaculture ponds have garnered increasing attention for their potential roles in the global carbon cycle within the context of global warming. As a significant co-culture species in mariculture ponds, clams exert a notable impact on CO2 flux across the water-air interface. However, the mechanism underlying this influence is as yet unclear. This study measured the CO2 flux as well as the ecosystem carbon metabolism and environmental physiochemical parameters from four marine polyculture ponds, i.e., the pond containing swimming crabs and kuruma shrimp was referred to as CS, and the other three ponds containing three varying densities of razor clams additionally based on CS were noted as CSB1, CSB2, and CSB3 in order of increasing clam density. All the bi-species and tri-species polyculture ponds acted as atmospheric CO2 sinks during the farming season, with the peak in CSB1 and the lowest in CSB3. Net ecosystem production was a dominant regulator of CO2 uptake, and sediment respiration significantly increased CO2 production and then affected the CO2 flux, contributing 16.7–20.0 % to the ecosystem respiration (ER). Water pH could function as a potentially reliable CO2 flux predictor in the polyculture ponds, while Chl a was an internal driving factor. The polyculture of clams at low density may have exerted a “bottom-up” effect, accelerating nutrient cycling and thus stimulating the planktonic community, gross primary production (GPP), and ER, whereas a high stocking density of clams can have a “top-down” effect that would have the opposite ecological effects through increased predation pressure from clams. Although GPP and ER were simultaneously promoted or inhibited by clams at different stocking densities, the effect on GPP was always greater than that on ER, resulting in the CO2 sink function that the polyculture ponds performed through the water-air interface being strengthened at low clam densities and weakened at high clam densities. Given the good predictive ability of water pH on CO2 flux, monitoring and management of water pH could be an effective way to regulate the CO2 sink function of mariculture ponds.

Enhancing Gardenia Leaf Nutrients via Shading, Vermicompost, and Chelated Iron

This study aimed to investigate the impact of shading, vermicompost, and chelated iron on the leaf content of certain elements in Gardenia jasminoides plants. Conducted at a private nursery in Erbil during the 2022 agricultural season, the experiment utilized gardenia plants propagated by cuttings and grafted onto one-year-old rootstocks. Over five months (April to October 2022), the effects of two shading levels (0% and 75% direct sunlight), vermicompost application at two levels, and chelated iron application at three levels (0, 0.1, and 0.2 g.L-1) were assessed. Results indicated that 75% shading significantly increased leaf nitrogen (1.72%) and iron content (73.94 mg.kg-1). Vermicompost at 25% significantly enhanced leaf nitrogen (1.75%), phosphorus (0.248%), potassium (1.36%), and iron (67.95 mg.kg-1). Chelated iron at 0.2 g.L-1 markedly improved leaf nitrogen (1.78%), phosphorus (0.256%), potassium (1.28%), and iron (78.45 mg.kg-1). The study utilized one-year-old uniform seedlings, grown in 15-liter pots with river loam soil, and standard care practices were followed. Data analysis was performed using ANOVA and Duncan’s Multiple Range Test at a 0.05 significance level. The findings suggest that specific shading, organic fertilizer, and chelated iron treatments can significantly enhance the nutrient content of gardenia leaves, potentially improving plant health and growth.

Evaluation of growth traits of (Eruca sativa Mill) Plant with the addition of Biochar.

The experiment was carried out during the Agricultural season of 2023, Zawia University, College of science, Department of Botany. The objective of the study was to evaluate the effects of Biochar addition on growth characteristics of Eruca sativa plants including (leaf number, root length, shoot length, fresh weight, dry weight). Eruca sativa seeds were sowed in pots. The experiment included two treatments: (0%) biochar (control) and (4%) biochar, The experiment was conducted in a completely randomized block design with three replications. After 47 days, the experiment was ended and data of growth traits were collected, and statistical analysis was performed. Results showed that there was a significant effect of biochar addition on growth traits studied (leaf number, shoot length, fresh wight) but no significant effects on the other traits. The study showed that the (leaf number, shoot length, fresh wight) recorded in the biochar treatment increased by 36%, 28%, 80% respectively. Keywords: Eruca sativa Mill, Biochar, growth traits.

Growth and yield response of four bread wheat cultivars, (Triticum aestivum L.), to spraying with NPK nano fertilizer

Abstract A field experiment was carried out during the agricultural season 2021-2022 in two locations within the administrative borders of Nineveh Governorate, the first location in the Gleokhan area within the borders of Mosul Center and the second location within the administrative borders of Namrod district, which is 45 km from the center of Mosul district, in order to know the effect of the balanced NPK 20:20:20 compound fertilizer nano the growth and yield of four varieties of bread wheat. The global experiment was carried out, which consisted of two factors, a randomized complete block design, and three replications. The first factor was fertilizer levels with four levels (1, 2, and 3 gm.L-1) added in two phases. The first is in the tillers stage (Z 2-1) and the second stage is at the beginning of the boating stage (Z 4-0) on the Zadoks scale, in addition to the comparison treatment, which was the traditional farmer’s method of fertilization (adding urea and dab fertilizer according to the times and quantities recommended by the Ministry Iraqi Agriculture), the second factor, four varieties of local bread wheat (Bhoth 22, Abu Ghraib, Rashid and Jihan), the following characteristics were studied: plant height, number of tillers, flag leaf area, total chlorophyll content of flag leaf, number of days up to 50% flowering, number of spikes, spike length, number of grains per spike, grain yield, weight of 1000 grains. The most important results of the study were as follows: The comparison treatment (the traditional farmer's method) excelled in the total chlorophyll content of the Gleokhan site and in the number of spikes and weight of 1000 grains in the Namrod site, with values of (28.41 Spad, 267.75 spikes.m-2, and 44.91 g), respectively. The 1 g spray treatment excelled in the characteristics of the number of tillers, number of spikes, length of spike, grain yield, and weight of 1000 grains at the Gleokhan site, and in the two characteristics of leaf area and spike length at the Namrod site, with averages of (178.17 tiller.m-2, 100.08 spikes.m-2, 8.58 cm , 128.83 g.m-2, 35.20 g, 34.46 cm2 and 10.85 cm) in the aforementioned order. The 3 g spray treatment was superior in the characteristics of plant height for both sites, the number of days up to 50% flowering, and grain yield of the Namrod site, with rates of (54.42 cm, 80.77 cm, 135.83 days, and 332.17 g.m-2), respectively. No significant differences were recorded between the levels of fertilizer in terms of flag leaf area and number of days up to 50% flowering for Gleokhan site and number of grains per spike for both sites. The cultivar Bhoth 22 excelled in terms of total chlorophyll content and the weight of 1000 grains at the Gleokhan site, and for the characteristics of the number of tillers, number of days up to 50% flowering, number of spikes, and grain yield of the Namrod site, as averages were recorded (27.29 Spad, 34.23 g, 302.75 tiller.m-2, 134.92 days, 290.17 spike.m-2 and 405.42 g m-2) respectively. The Abu Ghraib cultivar achieved superiority in the number of grains per spike at Al-Namrod site, with an average of (46.43 grains.spike-1). The cultivar Rashid excelled in the characteristics of the number of tillers, number of spikes, and spike length at the Gleokhan site, and for the two characteristics of the flag leaf area and spike length at the Namrod site, where the rates were recorded (169.08 tiller.m-2, 104.58 spike.m-2, 8.56 cm, 34.55 cm2 and 12.98 cm), respectively. The cultivar Jihan achieved superiority in the two characteristics of the number of days up to 50% flowering and grain yield at Gleokhan site, with values of (131 days and 108.08 g.m-2), respectively. No significant differences were recorded between the cultivars included in the study in the characteristics of plant height, flag leaf area, number of grains per spike for Gleokhan site, and for the two characteristics of total chlorophyll content and weight of 1000 grains for Namrod site. The interaction of 1 g spray treatment with Jihan cultivar recorded the highest average grain yield at Gleokhan site, and the 3 g spray treatment with Bhoth 22 cultivar had the highest average grain yield at Namrod site with values of (301 and 487.67 g.m-2), respectively.

Response of Arugula to Integrated Use of Biological, Inorganic, and Organic Fertilization.

This study evaluated the effects of solely and integrated application of inorganic (NPK), commercial organic (NC), and biological (MIX, mixed strains Ensifer meliloti and Azotobacter chroococcum) fertilizers on the chemical characteristics of arugula biomass and its yield, as well as changes in soil microbiological parameters after the experiment in relation to the control treatment (Ø). The experiment was performed in semi-controlled greenhouse conditions, in pots, from the 4th decade of March to the 2nd decade of September, in 2023, at three cutting times/swaths, during one agricultural season, with Vertisol soil. For soil characterization, the following parameters were analysed: granulometric composition using sieving and sedimentation procedure; soil acidity-potentiometrically; SOM-soil organic matter by Kotzmann method; total N using CNS analyser; available P-spectrophotometrically; available K-flame photometrically; total number of microorganisms on an agarized soil extract medium; fungi on a solid Czapek agar; actinomycetes on a solid Krasiljnikov agar with saccharose; Azotobacter spp. on a liquid Fyodorov medium with mannitol; ammonifiers on a liquid medium with asparagine; and dehydrogenase activity-spectrophotometrically. For plant characterization, the following parameters were determined: N and C, both on CNS analyser; P on spectrophotometer; K on flame photometer; air-dried yield biomass. A stimulative effect on all microbiological parameters was found in the treatment with integrated use of organic and biological fertilizer, except for fungi, which grew better in the treatments with separate inorganic and organic fertilizers. Generally, the stimulative impact on plant chemical parameters manifested in combined inorganic and biological, organic and biological, and inorganic and organic fertilization treatments, and was inhibited in treatment without fertilization, in all three swaths, which could also be stated for the plant yield. Positive influence of all fertilization treatments on chemical parameters was observed for the second swath in relation to the first and the third. The total yield in the NPK+MIX treatment was 121%, and in the NC+MIX treatment, it was 87% higher compared to the control (Ø). In general, integrated use of inorganic and biological, organic and biological, and inorganic and organic fertilizers, respectively, could be proposed as an optimal fertilization treatment in arugula cultivation.

Indigenous agricultural practices employed by the Vhavenda community in the Musina local municipality to promote sustainable environmental management

Indigenous knowledge offers insights into preserving natural resources and further contributes towards improving rural livelihoods. Incorporating this knowledge into agriculture can therefore increase acceptance and innovation of sustainable technologies. In support of this argument, rural small-scale farmers have globally proven the significance of indigenous knowledge in the agricultural sector by incorporating their local strategies and practices for both commercial and subsistence agriculture. This article demonstrates the various indigenous farming practices employed by the Vhavenda Community and how these practices promote sustainable environmental management. It reflects the essential aspects crucial to indicating the value of indigenous agriculture. Using a mixed-methods approach, we administered face-to-face structured questionnaires to elderly villagers aged 50 years and above from the study area. Our results revealed various agricultural practices such as crop rotations, polyculture, intercropping, livestock farming, ploughing rituals, water harvesting, and seasonal agriculture. The Vhavenda community incorporates local knowledge, which is unique to these agricultural practices, and uses various strategies which contribute to a sustainable environment within their area. This has, in turn, allowed them to improve their livelihoods, reduce poverty, and provide life sustenance. The study's findings demonstrate the significance of indigenous knowledge in the agricultural sector and rural peoples' efforts towards supportable environmental management. The article therefore suggests that local indigenous knowledge should be understood as a collaborative concept within the agricultural industry. Furthermore, it proposes that stakeholders who influence decision-making and progress in rural communities should consider this knowledge and work together with local inhabitants. Additionally, it advocates for acknowledging the understanding of local indigenous peoples in pursuing sustainable environmental management.

Influence of Simulated Erosion on Soil Properties and Maize Yield in the Southern Guinea Savanah Zone of Nigeria II

Aims: Long-term studies have been launched to assess the influence of artificial topsoil loss and its effects on soil properties and grain yield of cultivated maize. Place and Duration of Study: The study was conducted during the 2016 to 2019 agricultural seasons at the Federal University of Agriculture in Makurdi, Nigeria. Methodology: Three geo- referenced sites within the Federal University of Agriculture Makurdi, Nigeria namely: Site 1, Site_2 and Site_3 was used for the experiment. Erosion levels were established in June 2016 only by the incremental removal of topsoil at various depths. The study of crop productivity using simulated erosion was carried out using Randomized Complete Block Design (RCBD) with desurfaced soil depths of 0cm (control), 5cm, 10cm, 15cm and 20cm as treatments. One profile pit was also dug in each of the three sites for soil characterization and soil type establishment. Data collected on soil physical and chemical properties as well as crop growth parameters and grain yield was subjected to Analysis of Variance (ANOVA) using R core Statistical Software. Results: The study revealed that the soils of the three sites were classified as Kandic Paleustepts for Site_1, Typic Plinthustalfs for Site_2 and Typic Hapluderts for Site_3. These has brrn reported in drtail in paper I. In comparison with the 0cm (control), maize grain yield was reduced by 7%, 89%, 100% and 100% at Site_1, 5%, 64%, 82% and 85% at Site_2 and 6%, 71%, 82% and 92% at Site_3 for the 5cm, 10cm, 15cm and 20cm topsoil depth removal respectively. The topsoil loss greatly lowered the grain yield of maize. We report the effects of topsoil loss on crop productivity for two years.

Unleashing Economic Potential: Enhancing Cassava Production Efficiency in Nigeria

Purpose: This study is aimed at determining the economic efficiency of Manihot esculenta Crantz (Cassava) production in Nigeria’s Delta State. The study offers a detailed analysis of how socio-economic characteristics influence production output across both early and late farming seasons. Design/ Methodology/ Approach: This study employed a multi-stage random sampling approach in selecting a diverse cohort of 500 cassava farmers engaged in both early and late-season cultivation. Through rigorous personal interviews, primary data was gathered that was both comprehensive and insightful. Advanced parametric statistics and the Cobb-Douglas stochastic frontier function were used for the analysis. Findings: The mean economic efficiency scores were determined to be 0.63 for early-season farms, 0.78 for late-season farms, and 0.76 when considering all farms collectively. The output elasticities of material inputs, labour, and land were found to be 0.42, 0.61, and 0.05, respectively for all farms. For early-season farms, these values were 0.36, 0.68, and 0.04, whereas, for late-season farms, they were 0.31, 0.7, and 0.03. Research Limitation/Implications: This work concentrated on Cassava production efficiency within and around Nigeria’s Delta area. Practical Implication: Understanding the socio-economic factors that influence production during different seasons can help in designing strategies that maximize output in both early and late farming seasons. Social Implication: This study would help agricultural development economists and policy-makers in addressing the economic problems of Cassava farmers both present and future generations. Originality/Value: By examining both early and late farming seasons, the study provides a comprehensive understanding of how socio-economic factors vary across different agricultural cycles. This dual-season approach is relatively rare and offers more detailed insights into the dynamics of cassava production throughout the year.

THE MARKET OF OILSEEDS OF KAZAKHSTAN IN THE MEDIA: PROBLEMS AND PROSPECTS

This article analyzes the market of oilseeds in Kazakhstan based on information from the media. The study covers the development of the agro-industrial complex of the country, taking into account the gradual reduction of acreage under cereals in favor of oilseeds. The paper examines the opinions of farmers and experts on this strategy, as well as its implementation in the current agricultural season. Special attention is paid to the role of mass media in covering the issues of the oilseed market and the importance of this industry in economic and social terms.The research methodology is based on the analysis of information from the mass media and the assessment of the opinions of agricultural experts.The research methodology is based on the analysis of information from the mass media and the assessment of the opinions of agricultural experts.The main results and analysis allow us to conclude that there is a need for further development of the oilseed market in Kazakhstan, given its importance for the country's economy. The conducted research contributes to the field of knowledge about the development of agriculture and allows us to identify the key problems and prospects of the industry.The practical significance of the work is to provide information about the oilseed market in Kazakhstan, which can be used in planning and developing agricultural development strategies.

Compound droughts under climate change in Switzerland

Abstract. The co-occurrence of meteorological, agricultural, and hydrological droughts (multivariate compound droughts) in Switzerland during growing season is problematic due to limitations in water abstractions from rivers during low-flow periods, while at the same time the need for irrigation is high. We analyse compound droughts for 52 catchments in Switzerland during the extended summer season (May–October) using the transient climate and hydrological scenarios for Switzerland (CH2018 and Hydro-CH2018) for both a scenario with mitigation (representative concentration pathway 2.6 (RCP2.6), 8 model chains) and a scenario without mitigation (RCP8.5, 20 model chains). In the RCP8.5 scenario the number of compound drought days is projected to significantly increase by mid-century across all greater regions of Switzerland. The increased frequency is mainly a result of more frequent events (significant) rather than longer event durations (non-significant). Models generally agree on the sign of change. By 2085, compound drought events are projected to occur in median once per catchment per extended summer season north of the Alps and every 1–2 years south of the Alps. Further, the increases in compound drought days mainly occur between May–October, leading to a shift in the main agricultural production season and a more pronounced seasonality with the highest occurrence probabilities between mid-July and the beginning of October. Coupled to the increase in days and events, significantly more catchments are projected to be affected by compound droughts at the same time. In the RCP2.6 (mitigation) scenario, the increase in the number of compound drought days and events is not significant by the end of the 21st century. In comparison with RCP8.5, the number of compound drought days is reduced by 50 %–55 % north of the Alps and by up to 75 % south of the Alps by the end of the century. This emphasizes the need for coordinated adaptation in combination with mitigation measures taken at an early stage.

Research on a multiobjective cooperative operation scheduling method for agricultural machinery across regions with time windows

This article aims to solve the problems of high cost, low efficiency, and task delay caused by the lack of scientific scheduling strategies during the agricultural harvest season. Considering the constraints of operation time windows, a multimachine multiobjective cross-regional collaborative operation scheduling model is constructed with the goal of minimizing the transfer distance of agricultural machinery and nonoperational scheduling costs. A multiobjective genetic algorithm (HTSMOGA) based on a hybrid time window priority rule and a tabu search strategy is designed. The initial population is generated by utilizing time window priority rules, genes with earlier operation start times are preferentially retained, and a mixed search strategy is introduced to avoid local optimal solutions. Experiments were conducted among 24 farms in a region of Hebei Province, and the results showed that, compared with other algorithms, the HTSMOGA achieved an average reduction of 17.18 % in the transfer distance of agricultural machine operations and 19.36 % in the nonoperational waiting time. Therefore, this study provides a rational and feasible solution for the cross-regional operation scheduling of agricultural machinery cooperatives and provides theoretical support for ensuring the timely completion of harvesting tasks and the cost savings and efficiency of agricultural machinery operations.