Investigating Plant Response to Soil Characteristics and Slope Positions in a Small Catchment

Zsigmond, Tibor; Braun, Peter E.; Mészáros, János; Waltner, István; Horel, Ágota

doi:10.3390/land11060774

Cited by 3 publications

(3 citation statements)

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“…When plant growth conditions are below optimal, lower biomass or fruit production can be expected. NDVI is one of the most widely used parameters that can provide valuable information on plant greenness, biomass, and overall leaf health [ 24 , 26 , 49 , 50 ]. Sub-optimal soil chemical or physical properties of nutrient or soil water deficiency, or biological stress such as diseases caused by insects or fungi, could result in a decrease in NDVI values.…”

Section: Discussionmentioning

confidence: 99%

“…Vegetation indices can provide vital information on the current state of a plant, and can be used to study how plants respond to stressful environmental conditions [ 23 ]. Monitoring aboveground vegetation properties such as leaf chlorophyll content, the normalized vegetation index (NDVI), or leaf area index (LAI) can provide information on plant health, canopy structure, and photosynthetic activities [ 24 , 25 , 26 ]. Plant NDVI relates to plant greenness and density and has been widely used as an indicator of photosynthetic activity, light absorption, and canopy structure [ 24 ].…”

Section: Introductionmentioning

confidence: 99%

“…Plant NDVI relates to plant greenness and density and has been widely used as an indicator of photosynthetic activity, light absorption, and canopy structure [ 24 ]. NDVI values have been used in a number of studies to estimate or correlate plant traits such as net primary production [ 27 , 28 ], absorbed photosynthetically active radiation [ 26 , 28 , 29 ], LAI [ 26 , 30 , 31 ], plant biomass [ 32 , 33 ], and evapotranspiration [ 34 , 35 ]. However, these studies have reported varying findings relating to how well the values of specific plant species correlate with certain soil types and environmental parameters.…”

Section: Introductionmentioning

confidence: 99%

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Plant Growth and Soil Water Content Changes under Different Inter-Row Soil Management Methods in a Sloping Vineyard

Horel

Zsigmond

2023

Plants

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The main objective of this study was to investigate soil–plant–water interactions based on field measurements of plant reflectance and soil water content (SWC) in different inter-row managed sloping vineyards. The following three different soil management applications were studied: tilled (T), cover crops (CC), and permanent grass (NT) inter-rows. We measured SWCs within the row and between rows of vines. Each investigated row utilized 7 to 10 measurement points along the slope. Topsoil SWC and temperature, leaf NDVI and chlorophyll concentrations and leaf area index (LAI) were measured every two weeks over the vegetation period (May to November) using handheld instruments. We found that management method and slope position can significantly affect the soil’s physical and chemical properties, such as clay or soil organic carbon contents. Cover crops in the inter-row significantly reduced average SWC. The in-row average topsoil SWCs and temperatures were lower in all study sites compared to the values measured in between rows. Significantly higher SWCs were observed for the upper points compared to the lower ones for CC and T treatments (58.0 and 60.9%, respectively), while the opposite was noted for NT. Grassed inter-row grapevines had significantly lower leaf chlorophyll content than the other inter-row managed sites (p < 0.001). The highest average leaf chlorophyll contents were observed in the T vineyard (16.89 CCI). Based on slope positions, the most distinguishable difference was observed for the CC: 27.7% higher chlorophyll values were observed at the top of the slope compared to the grapevine leaves at the bottom of the slope (p < 0.01). The leaf NDVI values were not as profoundly influenced by slope position in the vineyard as the chlorophyll values were. For overall LAI values, the T treatment had significantly lower values compared to NT and CC (p < 0.001). Moderate correlations were observed between NDVI and LAI and soil nitrogen and carbon content. In general, we found that both inter-row management and slope position can significantly influence soil parameters and affect plant growth, and consequently can accelerate plant stress under sub-optimal environmental conditions such as prolonged drought.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Plant Growth and Soil Water Content Changes under Different Inter-Row Soil Management Methods in a Sloping Vineyard

Horel

Zsigmond

2023

Plants

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Boosting of fruit choices using machine learning-based pomological recommendation system

Dutta,

Gupta,

Juneja

et al. 2023

SN Appl. Sci.

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Pomology, also known as fruticulture, is a significant contributor to the economies of many nations worldwide. While vertical farming methods are not well-suited for fruit cultivation, substrate-based cultivation is commonly practiced. Vertical farming methods use no soil for cultivation of the plants, and the cultivation is done in vertically stacked layers. Therefore, smaller herbs are best suited for such cultivation, whereas, the majority of the fruit trees are big and woody. Therefore, vertical farming methods are not well suited for fruit trees. However, to maximize fruit production, smarter substrate cultivation methods are needed. Utilizing remote sensing techniques, such as Internet of Things (IoT) devices, agriculture sensors, and cloud computing, allows for precision agriculture and smart farming in autonomous systems. Nevertheless, a lack of understanding of fruit nutrient requirements, growing conditions, and soil health conditions can result in reduced fruit production. To address these challenges, this paper proposes an intelligent model based on machine learning that recommends the best fruit to grow based on prevailing soil and climatic conditions. The system is trained on a dataset that includes details on eleven different fruits, such as Nitrogen (N), Phosphorous (P), Potassium (K), temperature, humidity, pH, and rainfall. The model takes into account the soil type and nutrient contents to recommend the most suitable fruit to grow in the prevailing climate. To enhance the model's efficiency, two novel techniques, Gradient-based Side Sampling (GOSS) and Exclusive Feature Bundling (EFB), have been incorporated. The results show that the proposed system has achieved 99% accuracy in recommending the right fruit based on the given environmental conditions. As a result, this system has the potential to significantly improve the profitability of the pomology industry and boost national economies.

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Soil classification and prediction model for critical land on the slopes of Mount Raung in Indonesia

Basuki,

Anggriawan,

Sari

et al. 2024

J. Degrade. Min. Land Manage.

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Indonesia is in the ring of fire, which has an impact on the characteristics of volcanoes, one of which is Mount Raung. Mount Raung, part of the Iyang-Argopura mountains, has a role in influencing the development of soil types and the environment; it was recorded in 1586, 1987, 1597, and 1638. Soil types and environmental parameters have an influence on critical land conditions. Remote sensing technology has been used in various fields, one of which is land evaluation. This study examined the distribution of soil characteristics and the mapping of critical lands through remote sensing approaches. The method used to identify the morphological characteristics of soil classification and the potential for critical land was a descriptive-exploratory method. The results of the research on soil types are divided into three orders, namely Andisols, Inceptisols, and Alfisols. The three land orders are divided into nine great groups, with Lithic Eutrudepts having the highest area of 38.02%, followed by Typic Hapludalfs (21.70%), Typic Eutrudepts (9.79%), Typic Epiaquepts (7.84%), Aquic Eutrudepts (7.71%), Aquic Eutrudepts (5.64%), Fluventic Epiaquepts (5.30%), Typic Udivitrands (2.16%), and Vitric Hapludands (1.83%). Critical land based on the analysis of five factors of erosion, land use, slope, rainfall, and soil canopy density, is divided into four criteria i.e., critical area of 895.88 ha, medium critical 9,027.69 ha, and lightly critical of 14,096.89 ha. Land use, slope, and plant canopy density play a major role in the potential for critical land with a strong-very-strong level of closeness (0.350-0.610).

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Investigating Plant Response to Soil Characteristics and Slope Positions in a Small Catchment

Cited by 3 publications

References 51 publications

Plant Growth and Soil Water Content Changes under Different Inter-Row Soil Management Methods in a Sloping Vineyard

Plant Growth and Soil Water Content Changes under Different Inter-Row Soil Management Methods in a Sloping Vineyard

Boosting of fruit choices using machine learning-based pomological recommendation system

Soil classification and prediction model for critical land on the slopes of Mount Raung in Indonesia

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