Chlorophyll fluorescence as a tool for nutrient status identification in rapeseed plants

In natural conditions, plants growth and development depends on environmental conditions, including the availability of micro- and macroelements in the soil. Nutrient status should thus be examined not by establishing the effects of single nutrient deficiencies on the physiological state of the plant but by combinations of them. Differences in the nutrient content significantly affect the photochemical process of photosynthesis therefore playing a crucial role in plants growth and development. In this work, an attempt was made to find a connection between element content in (i) different soils, (ii) plant leaves, grown on these soils and (iii) changes in selected chlorophyll a fluorescence parameters, in order to find a method for early detection of plant stress resulting from the combination of nutrient status in natural conditions. To achieve this goal, a mathematical procedure was used which combines principal component analysis (a tool for the reduction of data complexity), hierarchical k-means (a classification method) and a machine-learning method—super-organising maps. Differences in the mineral content of soil and plant leaves resulted in functional changes in the photosynthetic machinery that can be measured by chlorophyll a fluorescent signals. Five groups of patterns in the chlorophyll fluorescent parameters were established: the ‘no deficiency’, Fe-specific deficiency, slight, moderate and strong deficiency. Unfavourable development in groups with nutrient deficiency of any kind was reflected by a strong increase in F o and ΔV/Δt 0 and decline in φ Po , φ Eo δ Ro and φ Ro . The strong deficiency group showed the suboptimal development of the photosynthetic machinery, which affects both PSII and PSI. The nutrient-deficient groups also differed in antenna complex organisation. Thus, our work suggests that the chlorophyll fluorescent method combined with machine-learning methods can be highly informative and in some cases, it can replace much more expensive and time-consuming procedures such as chemometric analyse

The role of plants and soil properties in the enzyme activities of substrates on hard coal mine spoil heaps

© 2021 The Authors. Published by Springer. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1038/s41598-021-84673-0Knowledge about biotic (plant species diversity, biomass) and/or abiotic (physicochemical substrate parameters) factors that determine enzyme activity and functional diversity of the substrate on hard coal spoil heaps is limited. Spontaneously developed vegetation patches dominated by herbaceous species commonly occurring on these spoil heaps: grasses (Poa compressa, Calamagrostis epigejos) and forbs (Daucus carota, Tussilago farfara), were examined. The activity of dehydrogenase and alkaline phosphatase was twice as high in plots dominated by grass species compared with those dominated by forbs. Significant positive correlations were found between the activity of dehydrogenase and alkaline phosphatase with pH, available P, soil moisture, and water holding capacity and negative correlations between the activity of urease and soil organic carbon. Strong positive correlations were found between values for Shannon–Wiener diversity index, evenness, species richness and soil functional diversity in plots dominated by grasses. We found that the soil physicochemical parameters had a greater impact on enzyme activity of the substrate than plant biomass and species diversity. However, grasses, through their extensive root system, more effectively increased enzyme activity and health of the substrate than other herbaceous species, and as they stabilize the substrate and form dense plant cover, they can be recommended for reclamation purposes.This study was funded by the InfoRevita project (TANGO1/268600/ NCBR/2015) financed by The National Centre for Research and Development in Poland.Accepted versio

Vegetation diversity on coal mine spoil heaps-how important is the texture of the soil substrate?

© 2019, The Author(s). The relationship between the size of the particle fractions of the soil substrate and the diversity of the spontaneously developing vegetation was investigated on coal mine spoil heaps in Upper Silesia (Southern Poland). The analyses were based on 2567 research plots of developed spontaneous vegetation and their associated soil substrate samples collected from 112 coal mine spoil heaps. For each research plot the prevailing particle size fraction was determined (stones, gravel, sand, silt), the species composition and abundance was recorded and the species richness (S), Shannon-Wiener diversity index (H′), Simpson (C) and Evenness (E) indices were used to determine species diversity. From a total of 119 research plots (in all particle size fraction categories), the values of 15 physicochemical properties (pH, electrical conductivity, water holding capacity, moisture, carbon content, total N, available P, Mg and exchange cations Ca, Mg, K, Na, fine particles (%), gravel (%), stone (%)) were obtained to asses their impact on the floristic composition of vegetation patches using Canonical Correspondence Analysis (CCA). Additionally, functional traits of the dominant species of each vegetation patch (life forms, life strategies and socio-ecological groups), were selected to analyse their relation to substrate texture. It was shown that the highest species richness and the highest values for Shannon-Wiener diversity index, as well as Simpson and Evenness indices, were obtained in plots formed on stones. Moreover, the greatest variation in the participation of species representing different habitats, life forms, and life strategies was found on gravelly substrates. Contrary to our expectations, the vegetation diversity (in terms of both species and their functional traits) was not highest in habitats with a high composition of fine size particles.Published versio

Chlorophyll fluorescence as a tool for nutrient status identification in rapeseed plants

In natural conditions, plants growth and development depends on environmental conditions, including the availability of micro- and macroelements in the soil. Nutrient status should thus be examined not by establishing the effects of single nutrient deficiencies on the physiological state of the plant but by combinations of them. Differences in the nutrient content significantly affect the photochemical process of photosynthesis therefore playing a crucial role in plants growth and development. In this work, an attempt was made to find a connection between element content in (i) different soils, (ii) plant leaves, grown on these soils and (iii) changes in selected chlorophyll a fluorescence parameters, in order to find a method for early detection of plant stress resulting from the combination of nutrient status in natural conditions. To achieve this goal, a mathematical procedure was used which combines principal component analysis (a tool for the reduction of data complexity), hierarchical k-means (a classification method) and a machine-learning method-super-organising maps. Differences in the mineral content of soil and plant leaves resulted in functional changes in the photosynthetic machinery that can be measured by chlorophyll a fluorescent signals. Five groups of patterns in the chlorophyll fluorescent parameters were established: the ‘no deficiency’, Fe-specific deficiency, slight, moderate and strong deficiency. Unfavourable development in groups with nutrient deficiency of any kind was reflected by a strong increase in F_{o} and \DeltaV/\Deltat_{0} and decline in \phi_{Po}, \phi_{Eo} \delta_{Ro} and \phi_{Ro}. The strong deficiency group showed the suboptimal development of the photosynthetic machinery, which affects both PSII and PSI. The nutrient-deficient groups also differed in antenna complex organisation. Thus, our work suggests that the chlorophyll fluorescent method combined with machine-learning methods can be highly informative and in some cases, it can replace much more expensive and time-consuming procedures such as chemometric analyses