Variable rate technology (VRT) in nutrient management has been developed in order to apply crop inputs according to the required amount of fertilizers. Meteorological conditions rarely differ within one field; however, differences in soil conditions responding to precipitation or evaporation results within field variations. These variations in soil properties such as moisture content, evapotranspiration ability, etc. requires site-specific treatments for the produced crops. There is an ongoing debate among experts on how to define management zones as well as how to define the required amount of fertilizers for phosphorus and nitrogen replenishment for winter wheat (Triticum aestivum L.) production. For management zone delineation, vegetation based or soil based data collection is applied, where various sensor technology or remote sensing is in help for the farmers. and The objective of the study reported in this paper was to investigate the effect of soil moisture data derived from Sentinel-2 satellite images moisture index and variable rate phosphorus and nitrogen fertilizer by means of variable rate application (VRA) in winter wheat in Mezőföld, Hungary. Satellite based moisture index variance at the time of sowing has been derived, calculated and later used for data comparison. Data for selected points showed strong correlation (R2 = 0.8056; n = 6) between moisture index and yield, however generally for the whole field correlation does not appear. Vegetation monitoring has been carried out by means of NDVI data calculation. On the field level, as indicated earlier neither moisture index values at sowing nor vegetation index data was sufficient to determine yield. Winter wheat production based on VRA treatment resulted significant increase in harvested crop: 5.07 t/h in 2013 compared to 8.9 t/ha in 2018. Uniformly managed (control) areas provided similar yield as VRA treated areas (8.82 and 8.9 t/ha, respectively); however, the input fertilizer was reduced by 108 kg/ha N and increased by 37 kg/ha P.
This paper deals with the identification of BIFs and associated sulphide mineralisation. An integrated approach, including the use of Landsat ETM-plus and Cartosat DEM data, GIS analysis, and geological data, is adopted for this purpose in the Nagavi area of Gadag Schist Belt (GSB), India. This integrated approach has enabled in identifying BIFs and structures. Band-7 of the ETM-plus sensor of Landsat-7 is used to identify BIFs and Band-5 for lineaments and shear zones. As a result of this study, the presence of gold mineralisation in sheared zones is noticed. BIFs are the economically prominent litho-units in the GSB hosting high-grade iron ore deposits along with sulphide mineralised shear zones. The strata bound ore is hosted primarily by BIF, consisting of chlorite, alternating chert and magnetite, sulphides and carbonate bands of a millimetre to centimetre scale.
An overview is given on the fluorescence imaging of plants. Emphasis is laid upon multispectral fluorescence imaging in the maxima of the fluorescence emission bands of leaves, i.e., in the blue (440 nm), green (520 nm), red (690 nm), and far-red (740 nm) spectral regions. Details on the origin of these four fluorescence bands are presented including emitting substances and emitting sites within a leaf tissue. Blue-green fluorescence derives from ferulic acids covalently bound to cell walls, and the red and far-red fluorescence comes from chlorophyll (Chl) a in the chloroplasts of green mesophyll cells. The fluorescence intensities are influenced (1) by changes in the concentration of the emitting substances, (2) by the internal optics of leaves determining the penetration of excitation radiation and partial re-absorption of the emitted fluorescence, and (3) by the energy distribution between photosynthesis, heat production, and emission of Chl fluorescence. The set-up of the Karlsruhe multispectral fluorescence imaging system (FIS) is described from excitation with UV-pulses to the detection with an intensified CCD-camera. The possibilities of image processing (e.g., formation of fluorescence ratio images) are presented, and the ways of extraction of physiological and stress information from the ratio images are outlined. Examples for the interpretation of fluorescence images are given by demonstrating the information available for the detection of different developmental stages of plant material, of strain and stress of plants, and of herbicide treatment. This novel technique can be applied for near-distance screening or remote sensing. and C. Buschmann, G. Langsdorf, H. K. Lichtenthaler.
So called small basins were originally specified with the aim to obtain more accurate data about the hydrological and hydrometeorological regimes of an extensive region. Later on the attention was also paid to the monitoring of chemical components and geochemical processes. Gradually it was discovered that small basins can also supply valuable information about the ecological stability and social and economic processes in relation to the ethnic features and local history of the studied region. Obviously, a decision about the size of small basins should be adapted to the nature of solved problems and with respect to the size of the region under consideration. A proposal how to define a small basin is presented as one of the conclusions. and Malá povodí byla původně zakládána s cílem získat zpřesněná data o hydrologickém a hydrometeorologickém režimu v rámci širšího regionu. Později se pozornost soustředila i na sledování chemismu a geochemických procesů. Postupně se ukázalo, že povodí poskytují další významné informace o ekologické stabilitě, a o procesech sociálních a ekonomických ve vztahu k etnickému složení populace; také o místní historii. Rozhodování o velikosti povodí je postupně podřizováno povaze řešených úloh a lze je posuzovat především ve vztahu k velikosti povodí, pro něž se informace získávají. Proto je návrh možné definice malého povodí uveden až v samém závěru tohoto příspěvku. V následujícím příspěvku jsou diskutovány některé typické úlohy, při jejichž řešení se významně uplatnily různé informace získané z malých povodí.
Non-destructive and rapid method for assessment of leaf photosynthetic characteristics is needed to support photosynthesis modelling and growth monitoring in crop plants. We determined the quantitative relationships between leaf photosynthetic characteristics and canopy spectral reflectance under different water supply and nitrogen application rates. The responses of reflectance at red radiation (wavelength 680 nm) to different water contents and nitrogen rates were parallel to those of leaf net photosynthetic rate (PN). The relationships of reflectance at 680 nm and ratio index of R(810,680) (near infrared/red, NIR/R) to PN of different leaf positions and leaf layers in rice indicated that the top two full leaves were the best leaf positions for quantitative monitoring of leaf PN with remote sensing technique, and the ratio index R(810,680) was the best ratio index for evaluating leaf photosynthetic characteristics in rice. Testing of the models with independent data sets indicated that R(810,680) could well estimate PN of top two leaves and canopy leaf photosynthetic potential in rice, with the root mean square error of 0.25, 0.16, and 4.38, respectively. Hence R(810,680) can be used to monitor leaf photosynthetic characteristics at different growth stages of rice under diverse growing conditions. and Y. Tian, Y. Zhu, W. Cao.