ARTICLE | doi:10.20944/preprints202209.0395.v1
Subject: Life Sciences, Biophysics Keywords: chilling requirement; chlorophyll fluorescence; non-photochemical quenching; PAM; photoprotection; stress resilience; winter dormancy
Online: 26 September 2022 (11:01:44 CEST)
Dormancy is a physiological state that confers winter hardiness to and orchestrates phenological phase progression in temperate perennial plants. Weather fluctuations caused by climate change increasingly disturb dormancy onset and release in many plant species including tree crops leading to aberrant growth, flowering, and fruiting. Currently, research in this field is impeded by the lack of affordable non-invasive methods for on-line monitoring of dormancy. We report on an automatic framework for low-cost, long-term, and scalable dormancy studies in deciduous plants. The proposed method is based on continuous near-field sensing of the photosynthetic activity of shoots via pulse-amplitude modulated chlorophyll fluorescence sensors connected remotely to a data processing system. The resulting high-resolution time series of JIP-test parameters indicative of the responsiveness of the photosynthetic apparatus to environmental stimuli are subjected to frequency-domain analysis. The proposed approach allows to overcome the variance coming from diurnal changes of insolation and to derive estimations on the depth of dormancy. Our approach was validated over three seasons in an experimental apple (Malus × domestica Borkh.) orchard by collating the non-invasive estimations with the results of traditional methods (growing of the cuttings obtained from the tress at different phases of dormancy) and the output of commonly used chilling requirement models. We discuss the advantages of the proposed monitoring framework such as prompt detection of freeze damages along with its potential limitations.
ARTICLE | doi:10.20944/preprints202112.0325.v1
Subject: Biology, Agricultural Sciences & Agronomy Keywords: phenotyping; proximal sensing; reflectance imaging; vegetation indices; hyperspectral reflectance; chlorophylls; carotenoids; anthocyanins; senescence; ripening
Online: 21 December 2021 (12:23:13 CET)
Hyperspectral reflectance imaging is an emerging method for rapid non-invasive quantitative screening of plant traits. This method is essential for high-throughput phenotyping and hence for accelerated breeding of crop plants as well as for precision agriculture practices. However, extraction of sensible information from reflectance images is hindered by the complexity of plant optical properties, especially when they are measured in the field. We propose using reflectance indices (Plant Senescence Reflectance Index, PSRI; Anthocyanin Reflectance Index, ARI; and spectral deconvolution) previously developed for remote sensing of vegetation and point-based reflectometers to infer the spatially resolved information on plant development and biochemical composition using ripening apple fruit as the model. Specifically, the proposed approach enables capturing data on distribution of chlorophylls and primary carotenoids as well as secondary carotenoids (both linked with fruit ripening and leaf senescence during plant development) as well as the information on spatial distribution of anthocyanins (known as stress pigments) over the plant surface. We argue that the proposed approach would enrich the phenotype assessments made on the base of reflectance image analysis with valuable information on plant physiological condition, stress acclimation state, and the progression of the plant development.
ARTICLE | doi:10.20944/preprints202109.0049.v1
Subject: Biology, Plant Sciences Keywords: reflectance; dehydration stress; proximal sensing; vegetation indices; pigments.
Online: 2 September 2021 (16:38:49 CEST)
We compared two approaches to non-invasive proximal sensing of the early changes in fresh-cut lettuce leaf quality: hyperspectral imaging and imaging PAM-fluorometry of chlorophyll contained in the leaves. The assessments made by the imaging techniques were confronted with the quality assessments made by traditional biochemical assays: relative water content and foliar pigment (chlorophyll and carotenoid) composition. The hyperspectral imaging-based approach provided the highest sensitivity to the decline of fresh-cut lettuce leaf quality taking place within 24 h from cutting. Using of the imaging PAM was complicated by (i) weak correlation of the spatial distribution pattern of the Qy parameter with the actual physiological condition of the plant object and (ii) its high degree of heterogeneity. Accordingly, the imaging PAM-based approach was sensitive only to the manifestations of leaf quality degradation only at advanced stages of the process. Sealing the leaves in the polyethylene bags slowed down the leaf quality degradation at the initial stages (< 3 days) but promoted its rate at more advanced stages, likely due to build-up of ethylene in the bags. An approach was developed to the processing of hyperspectral data for non-invasive monitoring of the lettuce leaves with a potential for implementation in greenhouses and packinghouses.
Subject: Biology, Anatomy & Morphology Keywords: reflectance; hyperspectral imaging; pigments; damages; apple fruit
Online: 2 February 2021 (12:58:42 CET)
Reflected light carries ample information about biochemical composition, tissue architecture, and physiological condition of plants. Recent technical progress brought about affordable imaging hyperspectrometers (IH) providing spatially resolved spectral data on plants. The extraction of sensible information from hyperspectral reflectance images is difficult due to inherent complexity of plant tissue and canopy optics, especially when recorded by IH under ambient sunlight. We aimed at obtaining a deeper insight into plant optics as perceived by IH since there is a high demand for algorithms for fruit harvesting and grading systems equipped with computer vision and robotic systems capable of working in orchard. We report on the characteristic changes in hyperspectral reflectance accompanying the accumulation of anthocyanins in healthy fruit, pigment breakdown during sunscald and phytopathogen attacks. The measurements made outdoors with a snapshot IH were compared with traditional “point” reflectance measured with a conventional spectrophotometer under controlled illumination conditions. Most of the spectral features and patterns of plant reflectance were evident in the IH-derived reflectance images. As a step forward, a novel index for highlighting tissue damages on the background of the anthocyanin absorption, BRI-M = (1/Rorange – 1/Rred + 1/RNIR), is suggested. Difficulties of the interpretation of fruit hyperspectral reflectance images recorded in situ are discussed with possible implications for plant physiology and precision horticulture practices.