The Relationship of Environmental Factors and the Cropland Suitability Levels for Soybean Cultivation Determined by Machine Learning

Radočaj, Dorijan; Vinković, Tomislav; Jurišić, Mladen; Gašparović, Mateo

doi:10.18047/poljo.28.1.8

Cited by 6 publications

(5 citation statements)

References 9 publications

(11 reference statements)

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“…Field crop production can potentially have a negative influence on the environment due to an irrational approach to soil cultivation, i.e., the result of the unprofessional application of various agrotechnical procedures, mass, and uncontrolled use of various chemical agents (herbicides, fungicides, etc.) and mineral fertilizers usage [ 20 , 21 , 22 , 23 ]. Soil contains numerous species of microorganisms like bacteria, algae and fungi.…”

Section: Introductionmentioning

confidence: 99%

Antioxidative Response and Phenolic Content of Young Industrial Hemp Leaves at Different Light and Mycorrhiza

Varga,

Kristić,

Lisjak

et al. 2024

Plants

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Due to the increasing presence of industrial hemp (Cannabis sativa L.) and its multiple possibilities of use, the influence of different light and several biopreparations based on beneficial fungi and bacteria on hemp’s morphological and physiological properties were examined. Different biopreparations and their combinations were inoculated on hemp seed and/or substrate and grown under blue and white light. A completely randomized block design was conducted in four replications within 30 days. For biopreparation treatment, vesicular arbuscular mycorrhiza (VAM) in combination with Azotobacter chroococum and Trichoderma spp. were inoculated only on seed or both on seed and in the substrate. Generally, the highest morphological parameters (stem, root and plant length) were recorded on plants in white light and on treatment with applied Trichoderma spp., both on seed and substrate. Blue light negatively affected biopreparation treatments, resulting in lower values of all morphological parameters compared to control. Leaves pigments were higher under blue light, as compared to the white light. At the same time, 1-diphenyl-2-picrylhydrazyl (DPPH), ferric reducing antioxidant power (FRAP), flavonoids, total flavanol content and phenolic acids were not influenced by light type. Biopreparation treatments did not significantly influence the leaves’ pigments content (Chl a, Chl b and Car), nor the phenolic and flavanol content.

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Section: Introductionmentioning

confidence: 99%

Antioxidative Response and Phenolic Content of Young Industrial Hemp Leaves at Different Light and Mycorrhiza

Varga,

Kristić,

Lisjak

et al. 2024

Plants

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“…Soil selection is also an important factor in sugar beet production [29][30][31][32]. High sugar beet yields can be achieved in soils with high fertility, deep arable layers, good water-air relationships, good structures, and slightly acidic, neutral to alkaline reactions [33][34][35].…”

Section: Introductionmentioning

confidence: 99%

Does the Amount of Pre-Sowing Nitrogen Fertilization Affect Sugar Beet Root Yield and Quality of Different Genotypes?

Varga,

Markulj Kulundžić,

Tkalec Kojić

et al. 2024

Nitrogen

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There has always been a specific focus on nitrogen fertilization in sugar beet production due to its important effect on sugar beet root yield and quality. For stable sugar beet growth and satisfactory root yield and quality, balanced N fertilization is crucial. Thus, this study aimed to investigate spring N fertilization in two seasons as the following treatments: N0—control, N1—only pre-sowing fertilization, and N2—pre-sowing with topdressing. Four different genotypes were included in the study (Serenada, Colonia, Fred, and Danton). The experiment was set up in a plain area, belonging to the temperate climate zone in Eastern Croatia (Županja and Vrbanja), with the long-term mean (LTM) (March–October) air temperature around 16 °C and the total precipitation of 515 mm. Pre-sowing N fertilization had a smaller impact on root yield in the year with higher precipitation (31% higher than LTM). Therefore, the average yields with pre-sowing fertilization (N1) and pre-sowing fertilization with top dressing (N2) were very similar and were only 7% higher than those of the control. In a season with less rainfall (29% less than LTM), pre-sowing fertilization with top dressing (N2) had a more pronounced effect on the increase in sugar beet root yield, which was 17% higher compared to that of the control treatment. The sugar beet sucrose content and quality parameters (brei impurities, loss of sugar in molasses, extractable sugar) differed when N fertilization was applied among locations in both seasons. The white sugar yield was the highest at N2 treatment with pre-sowing and topdressing N fertilization. In general, according to the average of all locations and years of research, the Serenada hybrid achieved the highest average root yield (81.1 t ha−1), while Colonia exhibited the highest root sugar content (14.5%) and white sugar yield (9.7 t ha−1).

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“…With the help of satellite images, the reflectance of various objects in the range of electromagnetic radiation that is not visible to humans became measurable [7]. The importance of satellite images that can be of different spatial, radiometric, spectral and temporal resolutions and therefore applicable for different purposes has been recognized worldwide, including in Croatia [8][9][10]. Satellite images of higher spatial resolutions, such as Worldview-3, reduce the possibility of overlapping spectral values among neighbouring pixels [11].…”

Section: Introductionmentioning

confidence: 99%

Methods of Land Cover Classification Using Worldview-3 Satellite Images in Land Management

Panđa,

Radočaj,

Milošević

2024

Teh. glas. (Online)

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Modern geoinformation technologies, such as remote sensing satellite missions and classification methods, are becoming increasingly prominent in land cover classification. Due to the emergence of high spatial resolution missions with improved temporal and spectral resolutions, such as Worldview-3, this approach enabled new possibilities in land management. To provide an in-depth analysis of such possibilities, this study reviews methods of land cover classification using WorldView-3 satellite imagery. With 29 different spectral channels and a spatial resolution of 1.2 m, Worldview-3 multispectral satellite images represent the most modern currently publicly available commercial multispectral images. The classification of multispectral images is performed to facilitate the identification and recognition of objects in the images. Analyzed classification methods are: supervised (semi-automatic) classification methods, unsupervised (automatic) classification methods, and object-based classification methods. In order to increase the accuracy in land cover studies, it was determined as necessary to develop automatic methods that rely on a combination of controlled and uncontrolled classification methods. This approach enables the automatic determination of samples for conducting supervised classifications of interest for land management.

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The Relationship of Environmental Factors and the Cropland Suitability Levels for Soybean Cultivation Determined by Machine Learning

Cited by 6 publications

References 9 publications

Antioxidative Response and Phenolic Content of Young Industrial Hemp Leaves at Different Light and Mycorrhiza

Antioxidative Response and Phenolic Content of Young Industrial Hemp Leaves at Different Light and Mycorrhiza

Does the Amount of Pre-Sowing Nitrogen Fertilization Affect Sugar Beet Root Yield and Quality of Different Genotypes?

Methods of Land Cover Classification Using Worldview-3 Satellite Images in Land Management

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