5th Global Conference on Agriculture

Extreme temperature and water deficit conditions pose significant threats to crop growth and food security in changing climates. Maize, a widely distributed crop, is particularly sensitive to water deficiency during its reproductive stage. Among the recommended management techniques to cope with drought stress, seed priming, a low-cost and sustainable technology, can increase crop drought tolerance, potentially enhancing crop productivity and food security under changing climate conditions. The current study intended to investigate the physiological (photosynthetic rate, transpiration, cell membrane injury) and biochemical (total phenols, DPPH activity) response of seed thermo-priming to drought stress applied during reproductive stage using three maize genotypes (Red, White, P-3057w). The experiment was carried out in pots and was split into six treatments (control, drought, thermo-priming 40oC, thermo-priming 40oC + drought, thermo-priming 50oC and thermo-priming 50oC + drought. The drought stress was induced at stage V7 before heading, for a period of 12 days in a split plot under completely randomized design. Our results showed that the drought stress significantly reduced photosynthetic rate (34%), transpiration (41%) and cell membrane injury (70%) while increasing phenols (14%) and DPPH activity (6%) in non-primed seeds whereas thermo-priming 40oC and 50oC treatments reduced significantly the negative effects of drought on photosynthesis (15%; 17%), transpiration (13%; 14%) and cell membrane injury (19%; 22%) through increased DPPH activity (10%). However, there were no significant differences between thermo-priming 40oC and 50oC treatments. Consequently, both thermopriming treatments were found to be effective for increasing the drought stress tolerance during reproductive stage in maize.

Food security is one of the greatest challenges we face in the 21st century. To feed the growing population with safe and nutritious food we need highly trained agricultural scientists that not only understand the science but the many challenges the industry faces. e developed an innovative PhD training programme. The programme was led by the British supermarket Waitrose and brought together three academic institutions, a research institute and more than 20 fresh produce suppliers. Over the course of 8 years the programme has trained 28 PhD scientists in a broad suite of topics relevant to the sustainable production of fresh produce. These included natural pest control, soil erosion, microplastics and air pollution. Students were all jointly supervised by academic and industry supervisors and presented their work to all suppliers on a regular basis. At the same time they all undertook placements with their industrial partner, spending time learning about the business, they visited suppliers and learned about the industry through talks and discussions. Our students have been very successful and have gone on to a range of roles including some who are now working in the fresh produce industry.

As a common metabolite of various agricultural products, 1-octen-3-ol plays a key role in cereal quality evaluation with adverse impacts on human health after inhalation, of which the detectors meeting the detection limit of ppb level that satisfies the request of application have been reported rarely. Herein, ZnFe2O4 and ZnSnO3 are selected to design heterostructured materials for highly sensitive and selective detection of 1-octen-3-ol gas. The sensing results prove that fine-tuned surface oxygen vacancies and highly-efficient electron transition of the nanocomposites are achieved through modulating the loading amount of ZnFe2O4, contributing to the significantly enhanced response (40.15 @ 50 ppm), low limit of detection (420 ppb), optimized selectivity and excellent long-term stability (40.786±1.693 @ 50 ppm for 15 days). The enhancement mechanism is explained by a large specific surface area with hollow mesoporous structures, consequent bandgap narrowing and decreased charge transfer resistance, which is further verified through DFT analysis. Moreover, the practical application for the unhusked rice detection is carried out. This work shed light on a new promising candidate for detecting characterized volatile organic compounds released from mildewed rice which may strikingly affect the rice storage industry by simplifying the quality control approach to a great extent.

Mangrove and nypa palm forests are abundant in the Niger Delta, the latter being invasive had competed aggressively with the former and altering benthic community structure. This study determined the diversity and abundance of benthic community from August to November, 2023 in nypa palm invaded mangrove forest. Sediment samples were taken from the two sites, a mangrove forest and a nypa palm forest along the Andoni River using an Eckman grab and then transferred in well labelled containers to the laboratory. Laboratory analysis was done using standard procedures. Data was subjected to SPSS, ANOVA, Shannon Weiner, Pielou and Margalef analyses. Results showed that a total of 640 organisms were extracted from four taxonomic groups, 5 classes and 16 species in the study area. Mangrove forest recorded a higher diversity index (1.716) than Nypa palm forest (1.56), but the mangrove forest recorded a relatively lower species evenness (0.634) than the Nypa palm forest (0.679). Species richness showed that benthos in the mangrove had a higher richness than those in the Nypa palm. Results of water physico-chemical parameters revealed that the mangrove forest (28.68±0.67oC) recorded a lower temperature than the Nypa palm (29.06±0.63oC) (p>0.05); pH in the mangrove (8.86±1.15) was lower than in the Nypa palm (p>0.05). Total dissolved solid was higher in the mangrove (2327.25±1952.20 mg/l) than in the Nypa palm (2021.67±1697.08mg/l) (p>0.05). Mean salinity value was higher in mangrove (0.72±0.17) than in the Nypa palm (0.70±0.16) (p>0.05). The mean DO values were higher in the mangrove (4.95±0.62mg/l) than in the Nypa palm (4.20±0.76) (p>0.05). This study revealed that nypa palm has an adverse effect on the abundance, richness and evenness of benthic organisms in the study area. Longer period of study of the ecosystem is required.

Agriculture in Uganda is not only the backbone of the economy but also a vital lifeline for millions of smallholder farmers. Despite the potential for high productivity, many farmers face challenges such as climate variability, soil degradation, and limited access to modern technology. This study presents detailed insights into the farming practices of Mr. Nsimbi Daniel, an experienced Ugandan farmer, who has successfully implemented a blend of traditional knowledge and modern techniques to enhance yield and promote sustainable farming.

In recent years, with the increase in the number of patients suffering from lifestyle-related diseases, soybeans, which are rich in plant-based protein, have attracted attention as a substitute for animal protein. Tocopherols, one of the major nutritional components of soybeans, have high antioxidant capacity. Therefore, the tocopherol content greatly affects the quality of soybeans, making the accurate determination of tocopherols necessary. Soybeans are often consumed as cooked beans. Since tocopherols are lipid-soluble, lipid extraction is essential to measure their content. However, boiled soybeans contain a large amount of water, which may hinder effective extraction using conventional lipid extraction method. Therefore, in this study, lipid extraction and tocopherol content analysis of boiled soybeans were investigated. The results showed that the precision and accuracy of each tocopherol standard at known concentrations ranged from 1.75 % to 10.8 % and 92.3 % to 109.7 %, respectively, when measured using high-performance liquid chromatography after pretreatment with a combination of chloroform/methanol agitation extraction and saponification. For the boiled soybean samples, the accuracy ranged from 0.49 % to 8.62 %. Both the standards and the samples met the standard values for accuracy and precision at each concentration. These results indicated that pretreatment with chloroform/methanol agitation extraction and saponification was sufficient for the determination of tocopherols in boiled soybeans.

In the mountainous regions of the Lesser Caucasus in Azerbaijan, pastures are subject to soil erosion at varying rates, especially in common village pastures where carrying capacity is unmet. This can be attributed to unsystematic livestock grazing, resulting in overgrazing compound by a lack of pasture improvement measures, leading to a deterioration in the quality and sustainability of the grazing land. The decline in vegetation cover has been shown to accelerates erosion processes, forming gullies on slopes and posing a threat to areas at lower elevations. The primary objective of the present research is a comparative analysis of samples taken from the same area of village pastures in the Lesser Caucasus in 2016 with samples taken in 2022/2023 aiming at an evaluation of ecological changes, vegetation cover, and degradation over time. The ecological assessment method employed adhered to the guidelines outlined in the Monitoring Manual for Summer Pastures in the Greater Caucasus in Azerbaijan by Etzold & Neudert (2013). The present paper sets out the findings of a comparative study of two village pasture areas. The analysis indicates that between 30% and 40% of the areas examined in the study locations have undergone some form of degradation with an increase in pasture degradation by 6-8% between 2016 and 2023. The study suggests a sharp decline in grazing quality within a decade, highlighting urgent action needed. The presentation will therefore also explore the preliminary results from focus group discussions exploring the potential local acceptance of degradation mitigation strategies.

Blueberry holds a significant place among the berry cultures, with year-to-year increase in its demand and production both globally and in Georgia, something that is often limited by diseaseinducing pathogenic microorganisms. The purpose of our study was to register and identify the diseases that damage Blueberry crops in weestern Georgia, namely in the following regions: Imereti (Samtredia, village Patara Etseri, Village Bashi), Samegrelo (Zugdidi, village Narazeni; Khobi, village Torsa), Guria (Ozurgeti, village Kvemo Natanebi), Adjara (Keda, village Arsenauli). The study was conducted under the project (PHDF-23-827) funded by the Shota Rustaveli National Science Foundation, using the approved methods in phytopathology and plant protection: determining the percentage of disease spread, re-seeding onto artificial growth medium, creating a ‘humid camera’, identifying the pathogens using morphologic studies. The following fungal pathogens were identified on various breeds of Blueberry: Alternaria tenuissima Kunze, Botrytis cinerea Pers., Colletotrichum acutatum J.H., Septoria sp., Naohidemyces vaccinii (Wint.), Exobasidium vaccinii Wor., Botryosphaeria vaccinii (Schear.) Barr. The disease spread percentage and intensity was calculated based on the monitoring and the registry. It was determined, that as the intensity of production on the fields increase, the number of diseases decrease. The highest number of diseases were found on smaller, less looked-after fields. The disease spread percentage varied between 5% and 55% in 2023 and sbetween 16.7% and 87.5% in 2024. It's clear, based on the results, that Blueberry diseases are highly spread in Western Goergia, and integrated defense mechanisms are important to be implemented.

The objective of this study was to evaluate the effectiveness of clay in improving natural nickel-rich soils, using the nickel-hyperaccumulating plant Odontarrhena chalcidica (Janka) Španiel et al. as a test plant. The experiment was conducted in a greenhouse using a completely randomized design with three replications. Clay soil from Durrës (Central Albania) was used as the clay source, while the nickel-rich soil was collected from Rrajca, an ultramafic region in eastern Albania. The experiment was conducted in 2 kg plastic pots, with four clay application rates: 0.0, 21.4, 44.3 and 64 g kg-1, corresponding to 0, 30, 60 and 90 t ha-1, respectively. The plants were watered regularly and NPK fertilization was applied. After 60 days, total nickel content was analyzed using XRF, while available nickel was determined by DTPA extraction and atomic absorption spectroscopy. The cumulative nickel content in the dry biomass of the aerial parts of Odontarrhena chalcidica, as well as the bioaccumulation factor in plants (BFP) and roots (BFR) were evaluated. The results, analyzed using the F- test and regression analysis, showed that increasing doses of clay significantly reduced the cumulative nickel content in the plant, as well as the BFP and BFR values. This suggests that the application of clay increases the absorption of nickel into the soil, there by reducing its uptake by the plant.

There are a number of variables that have contributed to the growing worry over the influence that climate change would have on agricultural crop production in the Republic of Azerbaijan. These factors include rising temperatures, altering patterns of precipitation, and severe weather events. The purpose of this research is to investigate the ways in which the unpredictability of climate has an effect on key crops including wheat, barley, maize, and cotton, which are the foundation of Azerbaijan's agricultural industry. The economy of the nation relies heavily on each and every one of these crops. We emphasize patterns in temperature rise, changes in the distribution of rainfall, and an increase in the frequency of droughts via the research, which makes use of historical climate data and yield statistics. Specifically, we highlight these trends by quantitative analysis. Policy ideas include investments in environmentally responsible agriculture, advancements in weather forecasting, and educational initiatives for farmers to strengthen their ability to withstand adverse conditions. These recommendations are among a variety of policy recommendations. Azerbaijan's agricultural sector is facing a number of challenges as a result of climate change, and the results of this study demonstrate how important it is to solve these challenges. This is of utmost significance when it comes to ensuring the nation's economic stability and the safety of its food supply.

In Figuig (an oasis in Morocco), date palm (Phoenix Dactylifera L.) cultivation generates 8500 tones/year of dry palm residues as by-products. This represents an opportunity for sustainable waste management through composting. The present study investigates the economic viability of a composting station dedicated to the recycling of date palm by-products by evaluating the agronomic quality of the compost, conducting a socio-economic survey of local farmers, and performing a detailed cost analysis to determine the station’s economic sustainability. Agronomic tests confirmed the compost's quality, demonstrating its ability to enhance soil fertility and support sustainable agricultural practices in the oasis. The socio-economic survey examined the characteristics of local farmers and their willingness to adopt composting technology. The cost analysis provided a thorough breakdown of the station’s operational and investment expenses, revealing its potential to create jobs and generate positive environmental, economic, and social impacts. This study highlights the value of circular agriculture approach in improving rural livelihoods and promoting environmentally sustainable practices, making it a cornerstone for replicable, scalable solutions in similar agro-ecosystems in Morrocco and in other countries.

This study offers an online traceability framework for continuous monitoring of critical environmental factors, using IoT, smart sensors, drones and open-source technology, integrating real-time data in four organic olive groves. This data-driven approach promotes more sustainable agricultural practices and supports the acquisition of evidence for improved traceability. Supply chain steps include organic olive cultivation, olive fruit processing, standardization, and production of biofunctional foods. The software ensures adherence to EU organic agricultural laws by facilitating real-time data collecting on environmental conditions, soil management, irrigation, and harvesting procedures. For smooth user interaction, it combines a responsive Bootstrap 5 web user interface, a lightweight PHP framework (CodeIgniter 4), and a relational open-source database (MariaDB). The system's capacity to enhance farm management and decision-making is demonstrated. The platform maximizes resource use, improves product quality, and fortifies customer trust by automating data collection and guaranteeing transparency. The system ensures complete supply chain visibility of organic table olives by recording important traceability data, such as fertilization management, irrigation, harvesting and transportation specifics, fruit quality, and processing activities. According to preliminary results, the suggested system greatly enhances operational effectiveness, regulatory compliance, and traceability in organic olive farming.

Olive pomace (OP) is a valuable byproduct of the olive oil industry. It is considered a low-cost source of bioactive compounds including polyphenols which have remarkable antioxidant activities and are widely recognized for their beneficial properties in human health. This study aimed to investigate the role of different solvents and extraction techniques in the recovery of phenolic compounds with high antioxidant activity from OP. The recovery of phenolic compounds from defatted OP obtained from the three-phase extraction process of the olive mill was performed using different extraction solvents (water, ethanol, methanol, hydro alcoholic mixtures, and natural deep eutectic solvents). Soxhlet, Microwave, and Ultrasound-Assisted Extraction (UAE) techniques were used to optimize bioactive compound recovery. The response surface methodology (RSM) was employed to evaluate the impact of three independent variables of UAE (sonication amplitude, extraction time, and solvent concentration) on total phenolic content (TPC), total flavonoids content (TFC), and antioxidant activity (DPPH assay). Results findings demonstrated that the optimal conditions for the recovery of phenolic compounds from OP were achieved using UAE techniques with ethanol:water (80:20), 80% sonication amplitude, and 60 minutes of extraction. The highest level of TPC, TFC, and antioxidant activity was obtained after extraction with UAE using 80 % ethanol (104 mg GAE/g, 48 mg/g, and 93.5%, respectively).

The vision for the project presented in this article was to support the agricultural sector to reduce environmental pollution generated by intensive livestock farming to help it achieve NetZero targets. In fact, agriculture and animal feeding operations contribute by nearly 11% of the total global anthropogenic greenhouse gases (GHGs) emissions where the major GHGs produced by the agricultural sector are methane (CH4), nitrous oxide (N2O) and carbon dioxide (CO2). In 2021, agriculture was the source of 11% of the total UK GHG emissions, equal to about 47.9Mt of CO2 equivalent and 49% of all methane emissions. In contrast, agriculture only accounted for about 1.9% of total carbon dioxide emissions. The project we present here aimed at demonstrating the ability of a novel air pollution abatement (APA) system, filterless and water-based, to extract carbon dioxide and methane directly from indoor air at the emission source (an operational farm housing). It is advised that CO2 concentrations should be controlled below 3000ppm to preserve animal welfare. Therefore, control systems are required for maintaining adequate indoor air quality in livestock facilities. A ventilation-controlled room was monitored over 100h under summer conditions, and actual concentrations were measured using precision reference systems at different locations within the site as well as at the inlet/outlet of the APA system. Results showed a consistent reduction in mean indoor concentrations for both CO2 and CH4. This research findings can contribute to meeting current GHGs concentration regulations in livestock buildings while enabling the reuse of these gases from the treatment water.

Lameness is a critical issue that impacts the welfare and productivity of livestock, resulting in diminished weight gain, fertility issues, and an increased susceptibility to secondary diseases. Conventional detection methods frequently fail to identify early signs due to their dependence on labour-intensive visual assessments. This study examines the use of tri-axial inertial measurements units affixed to neck collars in a sensor-based approach to objectively detect lameness in sheep. Time and frequency domain feature extraction techniques were employed to analyse data collected from livestock in Eastern and Central Macedonia, Greece, which were segmented into 2-second behaviour windows. Feature selection was performed using ReliefF to identify the most informative gyroscope and accelerometer features. Two machine learning models, Least Squares Support Vector Machine (LS-SVM) and Multiclass Random Forest (MRF), were used to classify lameness severity into three levels: healthy, mildly limp, and severely lame. The MRF model achieved a superior accuracy of over 83%, while both models exhibited good classification performance. The efficacy of integrating ubiquitous sensor data with machine learning techniques for the automated detection of lameness in sheep is underscored by these findings. This method improves animal health and farm management practices by reducing reliance on subjective evaluation and enhancing early intervention strategies.

In recent years, unmanned ground vehicles (UGVs) and Unmanned aerial vehicles (UAVs) have been widely adopted in agriculture, reducing human labor and enhancing operational safety. Autonomous navigation systems are essential to support UGVs and UAVs in diverse field conditions, enabling automated tasks such as planting, spraying, fertilizing, harvesting, thinning, weeding, and inspection. Advances in technology have led to more intelligent and adaptable navigation systems capable of long-term autonomous operation while executing specific field tasks. This study presents a navigation system for UGVs and UAVs in vineyard environment, enabling seamless bidirectional communication between a Farm Management Information System (FMIS) and autonomous vehicles within smart farming applications. The system integrates advanced route-planning algorithms within the FMIS and is compatible with agricultural vehicles via the Robot Operating System (ROS) and MAVLink protocols. It also includes a communication and computation unit (CCU) that links the FMIS algorithms, user interface, and vehicles. The system integrates advanced path planning, real-time localization, and obstacle avoidance techniques to ensure optimal performance. Key components include dynamic autonomous navigation, motion planning algorithms, sensor fusion using GNSS, LiDAR, and computer vision. The system was validated through field deployment of two ground robotic vehicles (Thorvald - Saga Robotics and Husky A200 - Clearpath Robotics) and two drones (S1000 – DJI and Farm4Drone – Acceligence) for executing route tasks in a vineyard. Case studies demonstrated over 80% efficiency in field traversal, while optimal route-planning improved field efficiency by up to 9.5%. These results highlight the potential of autonomous navigation in enhancing the efficiency and productivity of precision viticulture.

Vineyards’ monitoring is significantly important and today it is mainly conducted by the farmers and their advisors on-site. Robotic solutions with multiple sensors are gaining trust for such missions allowing farmers to reduce their on-site monitoring obligations. However, the current process of charging electric unmanned aerial and ground vehicles (UAVs and UGVs) for farming use is time-consuming and lacks automation. Typically, the battery must be manually removed from the vehicle, charged separately and then reinstalled, which significantly reduces operational efficiency and requires human intervention. To address these limitations, an automated charging system for UAVs and UGVs used in agricultural monitoring was designed. The system involves modifying the existing battery-vehicle interface to integrate a universal plug that allows for easy connection to charging stations scattered with the vineyards. A robotic arm equipped with an optical sensor autonomously detects and aligns the universal plug with the charging port on the vehicle and initiates the charging sequence. This setup eliminates the need for human intervention in the charging process, significantly improving convenience, reducing downtime and thus allowing for longer periods of crop monitoring within a given time frame. The automated charging system successfully enables fast and efficient conductive charging for UAVs and UGVs, reducing the time spent on manual battery handling and directly challenging the generally slower wireless charging methods. The system's automation not only accelerates the charging process but also enhances overall productivity in agricultural operations. This solution presents a significant advancement in electric vehicle charging technology for agriculture, supporting more efficient and scalable operations in precision farming.

Traditional pepper varieties (Capsicum annuum L.) are of great importance for biodiversity conservation and the enhancement of agricultural production. Traditional varieties are often better adapted to local climatic conditions and soils, offering resistance to diseases and environmental stresses that hybrids do not always provide. Additionally, traditional varieties contribute to preserving flavor and nutritional quality as they have evolved based on the needs and preferences of local communities. With its shifting conditions, climate change intensifies the need to develop varieties that are resilient to low inputs. Cultivating traditional pepper varieties with enhanced resilience to low-input conditions is crucial for ensuring productivity and food security, especially in vulnerable regions. Furthermore, strengthening these varieties through evaluation and subsequent improvement can offer significant solutions in a changing climate, promoting pepper crops' adaptability and long-term sustainability. This study was conducted at the Hellenic Agricultural Organization-DIMITRA Farm in Thermi in 2024. Twenty-five traditional pepper varieties were grown using a completely randomized block design (3 blocks with 10 plants per block) in an unheated open greenhouse under low-input cultivation conditions. Their evaluation and characterization followed, focusing on descriptive traits, yield (early and total), and post-harvest quality characteristics such as nutritional value and antioxidants. Genetic materials that demonstrate superiority in yield (e.g., the variety ‘Kampanoula’) or fruit biochemical characteristics (e.g., the variety ‘Filuria’ for phenolic content and ascorbic acid at commercial maturity) can be utilized in cultivation or incorporated into breeding programs aimed at developing Greek varieties or hybrids that are resilient to low inputs while providing exceptional fruit nutritional value.