The Eddy Covariance method (EC) is widely used for measuring carbon (C) and energy fluxes at high frequency between the atmosphere and the ecosystem, but has some methodological limitations and a spatial restriction to an area, called a footprint. Remotely sensed information is usually used in combination with eddy covariance data in order to estimate C fluxes over larger areas. In fact, spectral vegetation indices derived from available satellite data can be combined with EC measurements to estimate C fluxes outside of the tower footprint. Following this approach, the present study aimed to model C fluxes for a karst grassland in Slovenia. Three types of model were considered: (1) a linear relationship between Net Ecosystem Exchange (NEE) or Gross Primary Production (GPP) and each vegetation index; (2) a linear relationship between GPP and the product of a vegetation index with PAR (Photosynthetically Active Radiation); and (3) a simplified LUE (Light Use-Efficiency) model assuming a constant LUE. We compared the performance of several vegetation indices derived from two remote platforms (Landsat and Proba-V) as predictors of NEE and GPP, based on three accuracy metrics, the coefficient of determination (R2), the Root Mean Square Error (RMSE) and the Akaike Information Criterion (AIC). Two types of aggregation of flux data were explored: midday average and daily average fluxes. The vapor pressure deficit (VPD) was used to separate the growing season into two phases, a wet and a dry phase, which were considered separately in the modelling process, in addition to the growing season as a whole. The results showed that NDVI is the best predictor of GPP and NEE during the wet phase, whereas water-related vegetation indices, namely LSWI and MNDWI, were the best predictors during the dry phase, both for midday and daily aggregates. Model 1 (linear relationship) was found to be the best in many cases. The best regression equations obtained were used to map GPP and NEE for the whole study area. Digital maps obtained can practically contribute, in a cost-effective way to the management of karst grasslands.
COBISS.SI-ID: 5360038
The concept of precision farming is wide, and it represents the efficiency which is achieved with the help of precision. For the navigation of field machines, the RTK (Real Time Kinematic) navigation is needed. In order to verify the positive effects in practice, RTK navigation system equipped with Fentd 828 was applied to test the width of overlap, and fuel and time that could be saved compared with manual driving. The experiment was conducted on two areas of land size of 172 m x 58 m with two working machines width 3 m and 6 m. Result indicated that 15.7% of the time and 8.66% of the fuel were saved on a working machine of 3 meters width, and 12.6% of the time and 8.28% of the fuel were saved on a working machine of 6 m width. The width of the overlap represent 10% of the working width of the machine, and with the method of turning, which RTK navigation allows, additional time was saved. Ecological footprint, CO2 emissions and global warming potential (GWP) was estimated under different guiding system. The largest footprint was related to manual tillage with 3 m width working machine, while estimation on CO2 (kg) emissions and GWP got the same result. The use of precision agriculture technologies allows better planning and analyzing of working procedures. The air, water and soil pollution is less intensive.
COBISS.SI-ID: 4624428
In the process of applying a plant protection product mixed with water (spray mixture) at the prescribed concentration with conventional sprayers for chemical protection of tree canopies in an orchard, standard models are used to express the dose rate of the plant protection product. Characteristic properties of the tree canopy in an orchard are not taken into consideration. Such models result in fixed quantities of spray mixture being sprayed through individual nozzles into a tree canopy. In this research work, an autonomous system is presented, which ensures a controlled quantity of spray mixture sprayed through the nozzles onto different tree canopy segments. The autonomous system is based on a fuzzy logic system (FLS) that includes information about the estimated leaf area to ensure more appropriate control of the spray mixture. An integral part of the FLS is a fuzzy logic controller for three electromagnetic valves operating in the pulse width mode and installed on the axial sprayer prototype. The results showed that, with the FLS, it was possible to control the quantity of spray mixture in the specific range depending on the estimated value of the leaf area, with a quantitative spray mixture average saving of 17.92%. For the phenological growth stage BBCH 91, this method represents a powerful tool for reducing the quantity of spray mixture for plant protection in the future.
COBISS.SI-ID: 4566828