Seasonal Production Research Articles

Weed smothering efficiency of mulching types on groundnut (Arachis hypogea L.) productivity in the dry savanna region of Nigeria

In order to increase groundnut productivity, a field experiment was carried out in the dry season of 2020 to assess the effectiveness of various mulching materials at suppressing weeds. The experimental treatments comprised of five mulching types; Control (no mulch), transparent polythene mulch, black polythene mulch, rice straw mulch and saw dust mulch) and three groundnut varieties (SAMNUT 23, SAMNUT 24 and SAMNUT 26). These were factorially combined and laid out in a Randomized complete block design with three replications. Findings revealed that mulching had a significant (p < 0.05) impact on crop qualities including canopy cover, chlorophyll content, pod yield, 100 kernel weight, and groundnut kernel yield as well as weed attributes like weed cover scores, weed density, weed dry weight, and weed control efficiency in both BUK and Wasai, respectively. The weed compositions were further grouped into various families comprising Poaceae (11), Euphorbiaceae (3), Amaranthaceae (4), Asteraceae (3), Cyperaceae (2), Cucurbitaceae, and Aizoaceae, each having one species with a different level of occurrence across the two locations. On the other hand, SAMNUT 26 significantly produced higher pod (2798 & 2119) and kernel yields (1198 & 1191), although SAMNUT 23 produced a heavier 100 kernel weight (55.51 & 54.52) at BUK and Wasai, respectively. In comparison to the other mulching types, applying black polythene mulch or transparent mulch lowered weed density and dry weight by limiting the amount of sunlight that the weeds got, preventing them from growing. Therefore, for dry season production of groundnut in the Sudan savannah ecology of Nigeria, mulching with black or transparent polythene film using the SAMNUT 26 variety was found to be effective in conserving soil moisture for optimum crop growth and development, while on the other hand, weed populations were suppressed.

Long-term effects of COVID-19 pandemic on physical activity and eating behaviour of the Italian population: a longitudinal study.

Restrictive measures due to the Covid-19 pandemic strongly impacted lifestyle and daily behaviour. The purpose of this longitudinal retrospective study was to investigate short-term and long-term effects of Covid-19 pandemic on physical activity and eating habits of the Italian population investigating three time periods: pre-, during- and post-lockdown. A sample of 2773 adults recruited through social media provided data by an online survey administered from July to October 2023. Participants completed the International Physical Activity Questionnaire-Short Form (IPAQ-SF), the Mediterranean Diet Adherence Screener (MEDAS) and provided information about eating habits, socio-demographic and anthropometric characteristics. There was a significant increase (p < 0.001) in mean BMI from pre-pandemic period (24.53 ± 5.34 Kg/m2) to post-pandemic period (25.22 ± 6.0 Kg/m2). Physical Activity significantly decreased during the pandemic period compared to the pre-pandemic period (χ² = 271.97; p < 0.001; φ = 0.31) with an increase in inactive subjects from 25.7% to 52.8%. In the post pandemic period, there was an increase in the level of Physical Activity compared to the pandemic period (χ² = 413.61; p < 0.001; φ = 0.39) with a reduction of inactive subjects from 52.8% to 25.6%. Adherence to Mediterranean Diet score significantly (p < 0.001) increase from pre-pandemic (7.18 ± 1.58) to during-pandemic (7.29 ± 1.69) and post-pandemic (7.75 ± 1.63) periods with significant differences emerged in the consumption of single MEDAS items during the pandemic period by different BMI classes. Consumption of seasonal fruit and vegetables, water intake, the preparation/consumption of traditional or local dishes and the time dedicated for dinner and lunch significant increase (p < 0.001) during pandemic. The Covid-19 pandemic changed people's lifestyles, but in different ways for Physical Activity and diet. During the pandemic there was a negative effect for PA that decreased while the time spent sitting increased. This seems to be a temporary effect as, after the end of the phase of mandatory restrictions, it returns to the original level. The lockdown period improved the quality of the Italian population's eating habits, with an increase in adherence to the Mediterranean diet even after the end of the pandemic showing a rediscovery of traditional dishes, increase in consumption of seasonal products, greater preference for local products and more time spent preparing meals.

Life history strategies predict responses of lacustrine fish communities to eutrophication

The demographic traits of an organism are key components of its fitness and life history theory aims at identifying the environmental drivers underlying the evolution of life history strategies. For fishes, the equilibrium species, those investing into larval survival (large eggs, parental care) rather than into absolute fecundity, are hypothesized to have evolved in stable and predictable environments with high biotic pressure. Human induced nutrient enrichment in many lakes around the world makes them increasingly subjected to perturbations such as anoxia and toxic algal blooms. We hypothesized that eutrophication results in lakes becoming more unstable, unpredictable and less resource-limited, in turn less favorable to equilibrium species. Another hypothesis states that lacustrine environment stability increases with ecosystem size. This study presents the first attempt to compare the two hypotheses in a group of 26 lakes. We found that the population abundance of equilibrium species was negatively related to increasing eutrophication. Long-lived and highly fecund periodic species responded more positively to eutrophication than short lived opportunistic species, with no parental care. This result could be demonstrated by seasonality in primary productivity which favors periodic species, disconnection from the river which prevents good colonist (i.e., opportunistic) species to (re)-establish after perturbation events, and predation by periodic species on opportunistic species. In contrast, we found no support for the ecosystem size hypothesis. Overall, we showed that human driven eutrophication affected species according to their life history strategies, reinforcing the usefulness of life history theory as a framework for assessing fish community response to a large array of human perturbations. More generally, our study emphasizes the importance of species traits to assess, explain, and predict community responses to human and natural perturbations.

The coupling of winds, ocean turbulence, and High Salinity Shelf Water in the Terra Nova Bay Polynya

The Terra Nova Bay (TNB) Polynya in the Western Ross Sea of Antarctica is a major producer of High Salinity Shelf Water (HSSW), a precursor to Antarctica Bottom Water (AABW). Processes occurring in and around the polynya can therefore effect change in the lower limb of overturning circulation in this region. Here, we use data from a densely-instrumented upper-ocean mooring, deployed for 1 year in a region of active HSSW formation within TNB, to examine the coupling of surface brine rejection and vertical mixing to katabatic wind forcing. We find a high correlation between salinity and winds during the wintertime HSSW production season at the mooring site, with a lag-response of 20 h in near-surface (∼47 m) salinity to winds measured at the nearby Automatic Weather Station (AWS) Manuela. Salinity and temperature measurements show a fully destratified water column by June, with a lag-response of near-seabed (∼360 m) salinity to near-surface salinity of just 5 h. Measurements of turbulent kinetic energy (TKE) dissipation rate (ɛ) from moored pulse-coherent acoustic Doppler current profilers (ADCPs) show general agreement with classic boundary layer scaling (BLS), and calculations of a vertical mixing timescale using the Obukhov length scale average to ∼2.5 h during austral winter, consistent with the 5-h lag time observed in the salinity data. Comparisons to data from concurrent mooring deployments along the southern boundary of TNB, as well as to previously published assessments of model simulations and data from Climatic Long-term Interaction for the Mass-balance in Antarctica (CLIMA) moorings, allow us to explore spatial variability in the coupling of winds and salinity across TNB and to speculate on possible HSSW circulation pathways.

Modelling Mediterranean ocean biogeochemistry of the Last Glacial Maximum

Abstract. We present results of simulations performed with a physical–biogeochemical ocean model of the Mediterranean Sea for the Last Glacial Maximum (LGM) and analyse the differences in physical and biochemical states between the historical period and the LGM. Long-term simulations with an Earth system model based on ice sheet reconstructions provide the necessary atmospheric forcing data, oceanic boundary conditions at the entrance to the Mediterranean Sea, and river discharge to the entire basin. Our regional model accounts for changes in bathymetry due to ice sheet volume changes, reduction in atmospheric CO2 concentration, and an adjusted aeolian dust and iron deposition. The physical ocean state of the Mediterranean during the LGM shows a reduced baroclinic water exchange at the Strait of Gibraltar, a more sluggish zonal overturning circulation, and the relocation of intermediate and deep-water-formation areas – all in line with estimates from palaeo-sediment records or previous modelling efforts. Most striking features of the biogeochemical realm are a reduction in the net primary production, an accumulation of nutrients below the euphotic zone, and an increase in the organic matter deposition at the seafloor. This seeming contradiction of increased organic matter deposition and decreased net primary production challenges our view of possible changes in surface biological processes during the LGM. We attribute the origin of a reduced net primary production to the interplay of increased stability of the upper water column, changed zonal water transport at intermediate depths, and lower water temperatures, which slow down all biological processes during the LGM. Cold water temperatures also affect the remineralisation rates of organic material, which explains the simulated increase in the organic matter deposition, which is in good agreement with sediment proxy records. In addition, we discuss changes in an artificial tracer which captures the surface ocean temperature signal during organic matter production. A shifted seasonality of the biological production in the LGM leads to a difference in the recording of the climate signal by this artificial tracer of up to 1 K. This could be of relevance for the interpretation of proxy records like, e.g., alkenones. Our study not only provides the first consistent insights into the biogeochemistry of the glacial Mediterranean Sea but will also serve as the starting point for transient simulations of the last deglaciation.

The annual ovarian cycle in Northern pit vipers (Bothrops atrox) using serum steroids and ultrasound of the female reproductive tract

Knowledge on hormonal regulation of reproductive cycles in viperid snakes is still incipient, especially when it comes to females and tropical species. There is an urgent need to understand the reproduction of venomous snakes to improve assisted reproduction techniques and optimize the maintenance of these animals in captivity. With this in mind, we monitored Northern pit viper females year-round throughout different seasons via serum levels of progesterone (P4) and estradiol (E2) in conjunction with ultrasound examinations. Ovarian follicles were classified according to their size and stage of vitellogenesis in F-I and F-II (non-vitellogenic phase) or in F-III and F-IV (vitellogenic phase). During autumn and winter, five adult males were rotated among these females for reproductive pairing, which resulted in 17 copulations and 2 pregnancies in the first year and 12 copulations and 5 pregnancies in the second year. Then, we assessed changes in P4 and E2 levels according to seasons, predominant ovarian structures and the presence of embryos or eggs in the oviduct. Our findings showed high levels of E2 when a greater number of vitellogenic follicles were detected, indicating a possible influence of E2 on vitellogenesis and higher levels of P4 whenever eggs and embryos were visualized in the oviduct, implying its role in maintaining pregnancy. Descriptive analysis of the vipers’ ovarian cycles revealed a greater number of vitellogenic follicles during winter, probably as a result of increases in E2; whereas pregnancies occurred predominantly in spring, under the influence of P4. The use of ultrasound images, as a minimally invasive methodology, associated with serum steroid levels has proven to be an efficient approach in the reproductive monitoring of Northern pit vipers in vivo. In addition, these data suggest that female pit vipers under human care display a seasonal reproductive cycle, despite earlier studies involving captive males of the species indicating a lack of seasonality in sperm production and quality.

Research Article: Profitability of Producing Early Generation Rice Seed Under Pawe Districts: Northwestern Ethiopia

This research was conducted on the profitability of producing early-generation rice seeds under pawe districts in northwestern parts of Ethiopia. Early-generation seed production is a promising business that can be a solution to increase rice productivity and farmers&amp;apos; income. However, limited technology use, soil preference of commodity, and limited rice seed multiplier companies and human resources often become obstacles to addressing improved seed for farmers, especially smallholder farmers. The main purpose of early-generation seed production is to maintain the genetic potential and identity of a variety and regular provision of high-quality breeder seed which is the basis for subsequent seed production. Variety maintenance, production, and distribution of the breeder, pre-basic, and basic seed are carried out by the public breeding institutions or private seed sector. Samples were taken from rice seed farmers within two production seasons. This research aims to understand the economics of current seed production in the case of rice crops and provide basic information cost structure of EGS production for private and public enterprises. The analysis carried out includes cost analysis, income, and profitability analysis. The results showed that rice seed farmers were profitable with a 1.381 benefit-cost ratio and 27.58 profit margins. The total profit of one-hectare pre-basic seed production of rice was 47,433.565 which is the difference between total revenue (Price*Quantity =171939.39) and total cost (124,505.825).

Listening to Stakeholders III: Potential Users Evaluate Product Content and Design for Subseasonal Extreme Precipitation Forecasts

Abstract Extreme precipitation over a 2-week period can cause significant impacts to life and property. Trustworthy and easy-to-understand forecasts of these extreme periods on the subseasonal-to-seasonal time frame may provide additional time for planning. The Prediction of Rainfall Extremes at Subseasonal to Seasonal Periods (PRES2iP) project team conducted three workshops over 6 years to engage with stakeholders to learn what is needed for decision-making for subseasonal precipitation. In this study, experimental subseasonal-to-seasonal (S2S) forecast products were designed, using knowledge gained from previous stakeholder workshops, and shown to decision-makers to evaluate the products for two 14-day extreme precipitation period scenarios. Our stakeholders preferred a combination of products that covered the spatial extent, regional daily values, with associated uncertainty, and text narratives with anticipated impacts for planning within the S2S time frame. When targeting longer extremes, having information regarding timing of expected impacts was seen as crucial for planning. We found that there is increased uncertainty tolerance with stakeholders when using products at longer lead times that typical skill metrics, such as critical success index or anomaly correlation coefficient, do not capture. Therefore, the use of object-oriented verification that allows for more flexibility in spatial uncertainty might be beneficial for evaluating S2S forecasts. These results help to create a foundation for the design, verification, and implementation of future operational forecast products with longer lead times, while also providing an example for future workshops that engage both researchers and decision-makers.

A leaf age-dependent light use efficiency model for remote sensing the gross primary productivity seasonality over pantropical evergreen broadleaved forests.

Tropical and subtropical evergreen broadleaved forests (TEFs) contribute more than one-third of terrestrial gross primary productivity (GPP). However, the continental-scale leaf phenology-photosynthesis nexus over TEFs is still poorly understood to date. This knowledge gap hinders most light use efficiency (LUE) models from accurately simulating the GPP seasonality in TEFs. Leaf age is the crucial plant trait to link the dynamics of leaf phenology with GPP seasonality. Thus, here we incorporated the seasonal leaf area index of different leaf age cohorts into a widely used LUE model (i.e., EC-LUE) and proposed a novel leaf age-dependent LUE model (denoted as LA-LUE model). At the site level, the LA-LUE model (average R2 = .59, average root-mean-square error [RMSE] = 1.23 gC m-2 day-1) performs better than the EC-LUE model in simulating the GPP seasonality across the nine TEFs sites (average R2 = .18; average RMSE = 1.87 gC m-2 day-1). At the continental scale, the monthly GPP estimates from the LA-LUE model are consistent with FLUXCOM GPP data (R2 = .80; average RMSE = 1.74 gC m-2 day-1), and satellite-based GPP data retrieved from the global Orbiting Carbon Observatory-2 (OCO-2) based solar-induced chlorophyll fluorescence (SIF) product (GOSIF) (R2 = .64; average RMSE = 1.90 gC m-2 day-1) and the reconstructed TROPOspheric Monitoring Instrument SIF dataset using machine learning algorithms (RTSIF) (R2 = .78; average RMSE = 1.88 gC m-2 day-1). Typically, the estimated monthly GPP not only successfully represents the unimodal GPP seasonality near the Tropics of Cancer and Capricorn, but also captures well the bimodal GPP seasonality near the Equator. Overall, this study for the first time integrates the leaf age information into the satellite-based LUE model and provides a feasible implementation for mapping the continental-scale GPP seasonality over the entire TEFs.

Inventory Optimization Model with Quadratic Demand Pattern and Non-instantaneous Deterioration Rate with Mixed Cash and Advance Payment Scheme

Objectives: To develop a mathematical model for cost minimization by examining a scenario involving a seasonal product retail market, evaluating the outcome, and providing solutions to unanswered queries of existing models are the highlights of this present work. Methods: 1. Using dynamic differential equations with initial and boundary conditions, we mathematically model a retail market scenario for perishable commodities and determine the retailer's total cost. 2. We consider a quadratic function of time to precisely describe the maintenance cost and demand function. Also, a combination of cash and advance payment schemes is implemented in our model. 3. Our model was numerically formulated using a dataset deduced from earlier research. We have included a sensitivity analysis and a numerical example with a graphical depiction of the total cost function that highlights the most and least influential factors. 4. Based on the Hessian matrix condition and the calculus derivative approach, we developed an algorithm to calculate the optimal cost. Findings: This model provides retailers with insights for effective stock management while optimizing the cost of retailing perishable commodities with non-linear demand patterns. Sensitivity analysis showed that the two factors that have the biggest impact on retailers' overall costs are non-linear demand and holding cost parameters. The smaller optimal inventory cycle time and the large value of time at which a shortage happens raise the overall cost. Additionally, because of higher demand, the time-dependent deterioration rate has the least impact on overall cost. Additionally, a three-dimensional graph of cost minimization is offered to illustrate the convexity of total cost. Novelty: Implementation of Quadratic time-dependent demand and non-linear holding costs under a mixed cash advance payment structure, along with time-dependent deterioration and partial backlog shortages. Keywords: Quadratic Demand pattern, Non­instantaneous decay rate, Cash and Advance Payment scheme, Partial Backlog Shortages

Asynchrony of the seasonal dynamics of gross primary production and ecosystem respiration

Abstract The phenological cycles of terrestrial ecosystems have shifted with the changing climate, and the altered timings of biogeochemical fluxes may also exert feedback on the climate system. As regulators of land carbon balance, relative shifts in photosynthetic and respiratory phenology under climate change are of great importance. However, the relative seasonal dynamics of these individual processes and their sensitivity to climate factors as well as the implications for carbon cycling are not well understood. In this study, we examined the relationship in the seasonality of gross primary production (GPP) and ecosystem respiration (RE) as well as their temperature sensitivities and the implications for carbon uptake with around 1500 site-years’ of data from FLUXNET 2015 and Boreal Ecosystem Productivity Simulator (BEPS) at 212 sites. The results showed that RE started earlier in the spring and ended later in the autumn than GPP over most biomes. Furthermore, the flux phenology metrics responded differently to temperature: GPP phenology was more sensitive to changes during the spring temperature than RE phenology, and less sensitive to autumn temperature than RE. We found large BEPS-observation discrepancies in seasonality metrics and their apparent temperature sensitivity. The site-based BEPS projections did not capture the observed seasonal metrics and temperature sensitivities in either GPP or RE seasonality metrics. Improved understanding of the asynchrony of GPP and RE as well as different sensitivity of environmental factors are of great significance for reliable future carbon balance projections.

Nutrient enrichment and herbivory alter carbon balance in temperate seagrass communities

Large nutrient levels and herbivory stress, particularly when acting together, drive a variety of responses in seagrass communities that ultimately may weaken their carbon balance. An in situ three-months experiment was carried out in two contrasting seasons to address the effects of two levels of nutrient load and three levels of artificial clipping on Cymodocea nodosa plants. Nutrient enrichment shifted the community from autotrophic to heterotrophic and reduced DOC fluxes in winter, whereas enhanced community carbon metabolism and DOC fluxes in summer. Herbivory stress decreased the net primary production in both seasons, whereas net DOC release increased in winter but decreased in summer. A reduction of seagrass food-web structure was observed under both disturbances evidencing impacts on the seagrass ecosystems services by altering the carbon transfer process and the loss of superficial OC, which may finally weaken the blue carbon storage capacity of these communities.

A Decision Support System for Crop Recommendation Using Machine Learning Classification Algorithms

Today, crop suggestions and necessary guidance have become a regular need for a farmer. Farmers generally depend on their local agriculture officers regarding this, and it may be difficult to obtain the right guidance at the right time. Nowadays, crop datasets are available on different websites in the agriculture sector, and they play a crucial role in suggesting suitable crops. So, a decision support system that analyzes the crop dataset using machine learning techniques can assist farmers in making better choices regarding crop selections. The main objective of this research is to provide quick guidance to farmers with more accurate and effective crop recommendations by utilizing machine learning methods, global positioning system coordinates, and crop cloud data. Here, the recommendation can be more personalized, which enables the farmers to predict crops in their specific geographical context, taking into account factors like climate, soil composition, water availability, and local conditions. In this regard, an existing historical crop dataset that contains the state, district, year, area-wise production rate, crop name, and season was collected for 246,091 sample records from the Dataworld website, which holds data on 37 different crops from different areas of India. Also, for better analysis, a dataset was collected from the agriculture offices of the Rayagada, Koraput, and Gajapati districts in Odisha state, India. Both of these datasets were combined and stored using a Firebase cloud service. Thirteen different machine learning algorithms have been applied to the dataset to identify dependencies within the data. To facilitate this process, an Android application was developed using Android Studio (Electric Eel | 2023.1.1) Emulator (Version 32.1.14), Software Development Kit (SDK, Android SDK 33), and Tools. A model has been proposed that implements the SMOTE (Synthetic Minority Oversampling Technique) to balance the dataset, and then it allows for the implementation of 13 different classifiers, such as logistic regression, decision tree (DT), K-Nearest Neighbor (KNN), SVC (Support Vector Classifier), random forest (RF), Gradient Boost (GB), Bagged Tree, extreme gradient boosting (XGB classifier), Ada Boost Classifier, Cat Boost, HGB (Histogram-based Gradient Boosting), SGDC (Stochastic Gradient Descent), and MNB (Multinomial Naive Bayes) on the cloud dataset. It is observed that the performance of the SGDC method is 1.00 in accuracy, precision, recall, F1-score, and ROC AUC (Receiver Operating Characteristics–Area Under the Curve) and is 0.91 in sensitivity and 0.54 in specificity after applying the SMOTE. Overall, SGDC has a better performance compared to all other classifiers implemented in the predictions.

Seasonality in phytoplankton communities and production in three Arctic fjords across a climate gradient

Phytoplankton communities and production in Arctic fjords undergo strong seasonal variations. Phytoplankton blooms are periods with high primary production, leading to elevated algal biomass fueling higher trophic levels. Blooms are typically driven bottom-up by light and nutrient availability but may also be top-down controlled by grazing. While phytoplankton spring blooms are common across all Arctic systems, summer and autumn blooms and their drivers are less predictable. Here we compare the long-term (≥4 years) bloom phenology and protist community composition in three Arctic fjords: Nuup Kangerlua in western Greenland, Ramfjorden in northern Norway, and Adventfjorden in western Svalbard. While Nuup Kangerlua is impacted by tidewater glaciers, Ramfjorden and Adventfjorden are impacted by river-runoff. We discuss and contrast the presence and predictability of spring, summer, and autumn blooms in these fjords and the main physical, chemical, and biological drivers. Spring blooms occurred in all three fjords in April/May as soon as sufficient sunlight was available and typically terminated when nutrients were depleted. Chain-forming diatoms together with the haptophyte Phaeocystis pouchetii were key spring bloom taxa in all three fjords. Summer blooms were found in Nuup Kangerlua and Ramfjorden but were not common in Adventfjorden. In Nuup Kangerlua nutrient supply via subglacial upwelling was the key driver of a diatom-dominated summer bloom. This summer bloom extended far into autumn with strong winds resupplying nutrients to the surface later in the season. In Ramfjorden runoff from a vegetated catchment provided organic nutrients for a flagellate-dominated summer bloom in 2019. A late autumn bloom dominated by Skeletonema spp. and other chain-forming diatoms was present after nutrients were resupplied by wind mixing. In Adventfjorden, we observed only minor summer blooms in 2 of the 8 years, while autumn blooms were never observed. With global warming, we suggest that summer blooms will be negatively impacted in fjords where tidewater glaciers retreat and become land terminating. In fjords with rich vegetated catchments, harmful algal blooms may occur more frequently as summers and autumns become warmer and wetter. However, for fjords in high-Arctic latitudes (>78 N), the day length will continue to restrict the potential for autumn blooms.

Qualitative Production of Mixture Silage within a Sustainable Concept

Climate change and seasonality in forage production have caused alterations in animal feed. Thus, this study evaluated the composition of silages from soybean (Glycine max (L.) Merrill) mixed with tropical grasses. The experimental design was randomized blocks with four replications. Treatments were silage from soybeans, silage from soybeans with Aruana Guinea grass (Megathyrsus maximus cv. Aruana), and silage from soybeans with Congo grass (Urochloa ruziziensis cv. Comum). Silos were stored for 60 days in the laboratory at room temperature. The silage from soybeans with Aruana Guinea grass showed the highest contents of dry matter, crude fiber, neutral detergent fiber, insoluble nitrogen in neutral detergent fiber, and insoluble nitrogen in acid detergent fiber but the lowest levels of crude protein and ether extract. The highest content of mineral material and hemicellulose was observed in the silage from soybeans with Congo grass. The silages from soybeans and soybeans with Congo grass showed no significant differences for acid detergent fiber and lignin. In conclusion, the use of tropical grasses as a component to improve the quality of silage from soybeans is an alternative for forage conservation in ruminant production systems, especially at the dry season.

Performance Evaluation of Local Honey Bee Races (&amp;lt;i&amp;gt;Apis mellifera bandansi&amp;lt;/i&amp;gt;) at Wondo Genet, Sidama Regional State of Southern Ethiopia

The research was undertaken in Wondo genet agricultural a study conducted at a research facility between 2015 and 2017 focused on assessing the performance of &amp;lt;i&amp;gt;Apis mellifera bandansi&amp;lt;/i&amp;gt; honey bee races. The objective was to identify and choose the most effective honey bee races based on various parameters such as defensive behavior, hygienic practices, absconding tendencies, foraging abilities, swarming patterns, and productivity in terms of hive product area. A total of thirty bee races were evaluated during the study period (30) colonies of &amp;lt;i&amp;gt;Apis mellifera bandansi&amp;lt;/i&amp;gt;i honeybee were established on station. Basic management practices were made reasonably uniform for tested colonies. The investigation indicated the races exhibited aggressive behavior, resulting in stings on the examiner, with a maximum count of up to 158±15.3 and a minimum of 60 stings on the manipulator. The distance covered by the races extended long, reaching up to 255±74.1 meters away from the entrance. The absconding percentage from a total of thirty colonies ranged from a maximum of 50% in 2015 to a minimum of 26% in 2017. The early and late foraging behavior of the colony was also documented early morning 5:30 am time foraging, whereas late foraging time was at 7:15pm pm e back to their nest in the evening. The remaining hive products were quantified in a 5x5 cm2 comb area cell over the course of the production season, with measurements taken at 21-day intervals to assess the brood area. The values obtained, expressed as the mean ± standard deviation, indicated the range from maximum to minimum for the adult, brood, pollen, nectar, and honey area in cm&amp;lt;sup&amp;gt;2&amp;lt;/sup&amp;gt;. 79.5±13.4 107.1±24.6, 74.41±31.3, 48.2±9.0 for year (2015), 74.5±6.5, 107.1±24.6, 48.5±16.9, 81.8±31.6 for (year, 2016) and 114.8±20.5, 96.2±17.4, 50.0±19.4 and 90.7±40.2 for (year, 2017 respectively. The Apis mellifera, typically referred to in a general sense bandansi the race demonstrates positive attributes in terms of hygienic behavior and is also efficient in maximizing honey production when subjected to appropriate management strategies. It is recommended to conduct additional research on the specification of geographical location in relation to the distribution of different races and their identification for the purpose of breed determination and enhancement. This will aid in the selection of colonies that are more suitable in terms of production efficiency, temperament, resistance to pests, parasites, and diseases, as well as foraging and absconding tendencies.

Soil physico-chemical properties and yield response of cucumber (Cucumis sativus L.) To 2,4-Epibrasinolide under water stress

Dry season production of cucumber is often limited by water availability. Here, we explored the pleiotropic role of 2,4-epibrassinolide (BR) in ameliorating water stress based on changes in soil physico-chemical properties and fruit yield of cucumber under water stressed-conditions. The effects of four water stress levels-WL0, [No stress/control: 860 mL (100% daily irrigation)], WL1 [640 mL (75% daily irrigation)], WL2 [430 mL (50% daily irrigation)] and WL3 = [210 mL (25% daily irrigation)] in factorial combination with foliarly-applied two BR levels [with (BR1= 150 and 250 mL) and without (BR0= 0 mL)] were studied. The soil hydraulic conductivity (Ks) decreased substantially under the water-stressed condition. Soil pH, total nitrogen, available phosphorus, exchangeable bases, effective cation exchange capacity and base saturation were adversely (p ≤ 0.05) affected by water stress, but the exchangeable acidity (EA) was little changed. Water-stressed soil treated with BR showed a significant reduction in EA, increased Ks and nutrient availability. Although dry matter, biological yield, moisture content of the leaves and fruit yield were severely reduced by water stress, treatment with BR increased these by about 89, 27, 41 and 95%, respectively. Light interception was considerably improved under BR treatment as evidenced from the photosynthetically active radiation which increased by 42%. Over all, the increased fruit yield was a result of reduced soil acidity, increased nutrient availability and better use of light energy. Foliar application with BR could sustain growth and fruit yield of cucumber up to 50% of daily irrigation requirement.

Marketing Management in Agri-Business Organization

Strategic planning and execution are key components of marketing management in agri-business organisations, with the goal of maximising the reach and profitability of agricultural products. Traditional marketing concepts are blended with the specific difficulties and possibilities of the agriculture industry in this area. Important components include agriculturally specific advertising efforts, distribution methods, price strategies, product creation, consumer behaviour study, and market research. Supply chain knowledge, product seasonality, and familiarity with regulatory frameworks are all essential for successful marketing management in the agribusiness sector. Modern agri-business marketing techniques are greatly influenced by technological advancements and environmental initiatives. Businesses in the agricultural sector may get an edge in the market, strengthen relationships with customers, and expand their reach via the use of data analytics and digital technologies. Sustainable practices are becoming more important as stakeholders and customers want goods that are both ecologically and socially responsible. To keep up with the ever-changing nature of the agribusiness industry, this abstract focuses on the most important parts of marketing management and how new strategies are needed.

On Farm Performance of Finger Millet Varieties in Dera District of South Gondar Zone

Finger millet is an important food security crop and beneficial for human health. This study aimed to evaluate the on farm performance of the finger millet varieties in Dera district. The study took place in Korata Kebele and assessed grain yield and farmer feedback. The performance differences between the Necho variety (the demonstrated variety) and the farmers&amp;apos; variety were evaluated. Recent 10 years&amp;apos; grain yield data from the Dera district agriculture office was used to analyze the growth rates of area coverage, production, and productivity in the district using the compounded annual growth rate (CAGR). Furthermore, the performance of the Necho variety was compared to its potential and farmer variety using the technology gap, extension gap, and technology index. From 2014 to 2018, the annual growth rate of area coverage and productivity in Dera district declined by 1.6% and 1.7% per year, respectively. Moreover, from 2019 to 2023, the average annual growth rate of area coverage, production, and productivity decreased by 0.75%, 2.6%, and 3.4% per year, respectively. The technology index for the Necho variety in the production seasons of 2021, 2022, and 2023 was -4%, 16%, and 36%, respectively. The higher value in the 2023 season indicated a decline in the performance of the Necho variety compared to the farmer variety. This decline was attributed to the occurrence of blast disease. To address this issue, it is recommended to practice early planting and use recommended fungicides (Natura 250EW and Tilt 250EC). The district agriculture office must ensure easy accessibility of these fungicides in the market for farmers to utilize.

Sustainability of Production in Melon Growing Farms: The Case of Hatay Province

The aim of this study is to reveal the functioning and sustainability of melon producing farms in Hatay province. In the research, a face-to-face survey was conducted with 50 melon farmers in Hatay province. Additionally, the problems and disruptions encountered in melon production were identified in the study. Female labor is used extensively in melon production. In 2022, it was determined that women working in melon cultivation work for a daily wage of ₺150 (approximately $9). In 2021, 1 638 638 tons of melons were produced in an area of 668 753 ha in Türkiye. In Hatay, 32 537 tons of melons were produced from 13 230 decares of cultivation area. In addition, Kırıkhan melon received a geographical indication. Kırıkhan melon is a product that attracts attention in terms of taste and aroma. Melon prices follow a fluctuating trend during the production season. Input costs are also a serious problem in melon production. The average melon production cost was ₺10692 (approximately $590) for 1 decare. High costs threaten the sustainability of small family farms in production. As a result, farmers need to be supported and encouraged for production. Otherwise, melon production will be abandoned by small family farms. In this regard, it is important to increase training and publication activities.