Current Issue : April-June Volume : 2024 Issue Number : 2 Articles : 5 Articles
Veterinary antibiotics (VAs) have been indiscriminately used in animal feed for the past five decades to increase and ensure profits with negligible environmental considerations. The VAs amoxicillin (AMX), chlortetracycline (CTC), and oxytetracycline (OTC), which can be unintentionally introduced by irrigation water during rice cultivation, were evaluated for their phytotoxic effects, absorption–translocation into plants, and soil residues using a randomized complete block design. It was found that exposure to VAs can severely affect the photosynthetic pathway of rice plants. The uptake and translocation of VAs by rice plants varied significantly. CTC and OTC translocated more easily than AMX, a member of the β-lactam class, which accumulated at the lowest concentration compared to CTC and OTC across all treatments. Rice yield was about 4.3–5.7% lower in the experimental plots that received fifty-fold the background levels of VAs compared to the control. The findings indicate that these widely used veterinary antibiotics can hamper crop production, leave residues in the soil, and constitute a risk to human health if introduced into the agro-ecosystem unintentionally....
This study presents a comprehensive analysis of the potential utilization of sewage sludge in agriculture, focusing on the assessment of heavy metal contaminants and their mobility in sewage sludge-soil mixtures. The innovative approach of investigating heavy metal fractions in these mixtures sheds light on their environmental implications. In this study, sludge and soil samples from three different soil categories were collected, and the mobility of heavy metals was investigated using sequential BCR analysis. A thorough assessment of the risk of environmental contamination associated with the agricultural use of sludge was also carried out. This study included the calculation of various risk indicators, such as the Geoaccumulation Index of heavy metals in soil (Igeo), the risk assessment code (RAC), and the author’s element mobility ratio (EMR), which included a comparison of the overall metal concentrations in sludge, soil, and mixtures. This study demonstrates that the key to using sludge is to know the form of mobility of the metals present in the sludge and how they behave once they are introduced into the soil....
This research investigates how fourth-instar larvae of the potato tuber moth, Phthorimaea operculella, respond to plant secondary metabolites (sucrose, glucose, nicotine, and tannic acid) both in terms of gustatory electrophysiology and feeding behavior. The objective is to establish a theoretical foundation for employing plant-derived compounds in potato tuber moth control. We employed single-sensillum recording techniques and dual-choice leaf disk assays to assess the gustatory electrophysiological responses and feeding preferences of these larvae towards the mentioned compounds. Sensory neurons responsive to sucrose, glucose, nicotine, and tannic acid were identified in the larvae’s medial and lateral sensilla styloconica. Neuronal activity was influenced by stimulus type and concentration. Notably, the two types of sensilla styloconica displayed distinct response patterns for sucrose and glucose while they had similar firing patterns towards nicotine and tannic acid. Sucrose and glucose significantly promoted larval feeding, while nicotine and tannic acid had significant inhibitory effects. These findings demonstrate that the medial and lateral sensilla styloconica house sensory neurons sensitive to both feeding stimulants and inhibitors, albeit with differing response profiles and sensitivities. This study suggests that sucrose and glucose are promising candidates for feeding stimulants, while nicotine and tannic acid show potential as effective feeding inhibitors of P. operculella larvae....
Information and communication technology (ICT) in developing countries is a key element for growth and economic development. This work conducted an evaluation regarding the use of ICT to reduce the socioeconomic gaps of rural populations and promote its inclusion in development plans, considering its use to guarantee a sustainable development model. For this, a systematic review of 280 articles was carried out using the Scopus, Latindex, Scielo, Dialnet, Redalyc, and Google Scholar databases during the period from 2018 to 2023, of which 40 articles were selected that address the use of ICTs and the agricultural digitalization for the management of soil, water, and the application of fertilizers and agrochemicals, which guarantee sustainable agricultural development. The results show that there are numerous digital tools available based on artificial intelligence (AI), machine learning (ML), drones, apps, and the Internet of Things, which aid in soil and water management and make use of agrochemicals and water, thus improving efficiency and reducing pollution problems. However, there is a large gap at the international level in acquiring state-of-the-art technological equipment that takes advantage of the potential that exists in terms of new technologies and their efficient use. Much of the research on the use of ICTs in the agricultural field comes from countries with medium or high levels of technological development, especially from Asia, Europe, or North America. As a result, Latin America lags behind in this regard....
Potted plant canopy extraction requires a fast, accurate, stable, and affordable detection system for precise pesticide application. In this study, we propose a new method for extracting three-dimensional canopy information of potted plants using millimeter-wave radar and evaluate the system on plants in static, rotating, and rotating-while-spraying states. The position and rotation speed of the rotating platform are used to compute the rotation–translation matrix between point clouds, enabling the multi-view point clouds to be overlaid on the world coordinate system. Point cloud extraction is performed by applying the Density-Based Spatial Clustering of Applications with Noise algorithm (DBSCAN), while an Alpha-shape algorithm is used for three-dimensional reconstruction of the canopy. Our measurement results for the 3D reconstruction of plants at different growth stages showed that the reconstruction model has higher accuracy under the rotation condition than that under the static condition, with average relative errors of 41.61% and 10.21%, respectively. The significant correlation between the sampling data with and without spray reached 0.03, indicating that the effect of the droplets on radar detection during the spray process can be neglected. This study provides guidance for plant canopy detection using millimeter-wave radar for advanced agricultural informatization and automation....
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