Publications by authors named "Jan Graefe"

Deep learning and multimodal remote and proximal sensing are widely used for analyzing plant and crop traits, but many of these deep learning models are supervised and necessitate reference datasets with image annotations. Acquiring these datasets often demands experiments that are both labor-intensive and time-consuming. Furthermore, extracting traits from remote sensing data beyond simple geometric features remains a challenge.

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Arbuscular mycorrhizal fungi (AMF) alter plant water relations and contribute to soil structure. Although soil hydraulic properties depend on soil structure and may limit plant water uptake, little is known about how AMF influence soil water retention (the relation between the soil water content and soil water potential) and hydraulic conductivity in different soils. Instead, these soil hydraulic properties often are considered to be independent of AMF presence in experiments.

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Rising urban food demand is being addressed by plant factories, which aim at producing quality food in closed environment with optimised use of resources. The efficiency of these new plant production systems could be further increased by automated control of plant health and nutritious composition during cultivation, allowing for increased produce value and closer match between plant needs and treatment application with potential energy savings. We hypothesise that certain leaf pigments, including chlorophylls, carotenoids and anthocyanins, which are responsive to light, may be good indicator of plant performance and related healthy compounds composition and, that the combination of leaf spectroscopy and mathematical modelling will allow monitoring of plant cultivation through noninvasive estimation of leaf pigments.

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Mechanistic models of canopy photosynthesis usually upscale leaf photosynthesis to crop level. A detailed prediction of canopy microclimate with accurate leaf morphological and physiological model parameters is the pre-requisite for accurate predictions. It is well established that certain leaf model parameters ( , ) of the frequently adopted Farquhar and Caemmerer photosynthesis model change with leaf age and light interception history.

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Soil-borne pathogens can have considerable detrimental effects on asparagus () growth and production, notably caused by the species f.sp. , and .

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Fluorescence, normalized difference vegetation index, and thermal imaging are three frequently used nondestructive methods to detect biotic stress in plants. Due, in part, to the inconsistent results reported in the literature and the lack of measurements on the whole-plant scale, we tested the suitability of a wide variety of variables obtained using these three imaging methods to classify young plants into biotically stressed and nonstressed plants. To this end, we applied the model plant-pathogen system lettuce-Rhizoctonia solani.

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Arbuscular mycorrhiza fungi (AMF) consume plant carbon and impact photosynthesis, but effects of AMF on plant gas exchange are transient and hardly predictable. This is at least partially because plant-internal nutrient-, water-, and sink-related effects, which can be influenced AMF, and atmospheric conditions integrate at the photosynthesis level. In nature and in plant production, plants face periodical and random short-term switches of environmental conditions that limit photosynthesis, which may impede stimulatory effects of AMF on leaf photosynthetic capacities.

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Arbuscular mycorrhizal (AM) fungi have become an attractive target as biostimulants in agriculture due to their known contributions to plant nutrient uptake and abiotic stress tolerance. However, inoculation with AM fungi can result in depressed, unchanged, or stimulated plant growth, which limits security of application in crop production systems. Crop production comprises high diversity and variability in atmospheric conditions, substrates, plant species, and more.

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Arbuscular mycorrhizal fungi (AMF) proliferate in soils and are known to affect soil structure. Although their contribution to structure is extensively investigated, the consequences of those processes for soil water extractability and transport has, so far, gained surprisingly little attention. Therefore we asked, whether AMF can affect water retention and unsaturated hydraulic conductivity under exclusion of root ingrowth, in order to minimize plant driven effects.

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Arbuscular mycorrhizal fungi (AMF) proliferate in soil pores, on the surface of soil particles and affect soil structure. Although modifications in substrate moisture retention depend on structure and could influence plant water extraction, mycorrhizal impacts on water retention and hydraulic conductivity were rarely quantified. Hence, we asked whether inoculation with AMF affects substrate water retention, water transport properties and at which drought intensity those factors become limiting for plant transpiration.

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