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Precision maize stand analysis using remote sensing methods: plant density measurement with spectral data integration
Views:212The aim of this study was to use remote sensing with a drone equipped with a multispectral camera to take a stand survey of maize after the phenological stage of emergence, and to count the number of emerged plants and determine its accuracy. Our investigations were carried out at the University of Debrecen, Látókép Production Experimental Station in a sowing date long-term experiment. In the 2024 growing season, Sowing Date I was on 4 April and Sowing Date II on 12 April. The same maize hybrids with 8-8 different genotypes were used for each sowing date. There is a strong correlation between number of plants/plot and number of plants/rowx2 for the two plant density measurements presented in this paper, with an r value of 0.977*** (p < 0.001). Among the plant density and NDVI values, the correlation between number of plants/rowx2 at the second measurement time (July 4) was significant at r=-0.418***. The analysis of the relationship between number of rows and yield showed that the hybrids included in the study compensated well for differences in number of rows due to sowing or emergence and this did not translate into an increase or decrease in yield. By using the plant density count method and results to identify emergence imbalances, farmers can correct their crop stand management strategies in a timely manner. Knowing the exact number of plants can also be important for subsequent agrotechnical decisions.
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The role of precision farming in crop production’s adaptation to climate change
Views:18As a result of climate change, agricultural production is facing ever-greater challenges, including rising temperatures, changes in the distribution and quantity of precipitation, and an increase in the frequency of extreme weather events. The aim of this study is to outline the role of precision farming in adapting to climate change, with a particular focus on remote sensing, drone-based data collection, water and soil management, and the application of vegetation indices. The methodological basis of the research is a comprehensive review of relevant domestic and international literature. The study carries out a comparative assessment of the climate adaptation technologies and practical applications of precision farming, drawing on scientific publications, book chapters, doctoral theses, as well as statistical and specialist data sources. Following a review of the literature, it can be concluded that precision technologies contribute to the continuous monitoring of cropland, the implementation of site-specific interventions and the more efficient use of resources. Vegetation indices – in particular the NDVI, GNDVI, NDRE, NGRDI (VIGreen) and the leaf area index (LAI) – have proved to be particularly important in practical application, as they provide objective information on the current condition of the crop and support evidence-based decision-making regarding cultivation techniques. When combined with an appropriate agronomic approach and state-of-the-art digital technologies, precision farming can significantly increase the adaptability of agriculture, thereby contributing to the realisation of sustainable crop production. From a practical perspective, the findings of this review can facilitate the more targeted selection and application of precision technologies and vegetation indices, thereby directly supporting farmers’ data-driven decision-making, increasing resource efficiency, and mitigating production risks arising from climate change.
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The role of sensor technology in sustainable and efficient agricultural production - Review
Views:231Agricultural sensor technology has become a cornerstone of modern precision farming over the past two decades. Our research focused on the applications of remote and proximal sensing technologies, with an emphasis on satellite, drone-based, soil-embedded, and plant-mounted sensors. The study analyzed the presence of sensors in scientific publications and the evolution of research trends. The results showed that the number of scientific publications on sensor technology has grown exponentially, particularly in the last decade, reflecting increasing scientific and practical interest in the field. It was found that modern advancements, such as nanotechnology, have significantly contributed to reducing sensor size and enhancing their sensitivity, thereby supporting sustainable agricultural practices. Sensor applications enable the optimization of water, nutrient, and energy use, contributing to agricultural sustainability. Our research highlighted the importance of sensor technology in improving production efficiency and addressing global agricultural challenges.