The interplay between leaf water potential and osmotic adjustment on photosynthetic and growth parameters of tropical dry forest trees

Leite, Tiago de Sousa; Freitas, Rômulo Magno Oliveira de; Dias, Nildo da Silva; Dombroski, Jéferson Luiz Dallabona; Nogueira, Narjara Walessa

doi:10.1007/s11676-022-01495-0

Cited by 6 publications

(4 citation statements)

References 49 publications

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“…Biomass accumulation is often the main morphological characteristic affected by water de cit (Amaral et al 2023;Leite et al 2023). We observed that all yerba mate genotypes at a higher water availability tended to increase their biomass accumulation.…”

Section: Resultsmentioning

confidence: 57%

Morphological, physiological, and biochemical responses of yerba mate (Ilex paraguariensis) genotypes to water deficit

Gabira,

Bergeron,

Duarte

et al. 2023

Preprint

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Severe drought is expected to increase in frequency and intensity in South America, likely causing decreased plant productivity and altering species distributions. Yerba mate (Ilex paraguariensis) is a tree species native to South America and has an ecological, social, and economic importance in several countries. Natural forests and cultivated areas of yerba mate will be endangered by climate change because of the expected reduction in water availability. Here we determined how four clonal genotypes of yerba mate (BRS BLD Yari, BRS BLD Aupaba, BRS 408, and EC40) respond to water deficits by evaluating the plants’ morphophysiological and biochemical characteristics when subjected to four levels of soil water holding capacity (WHC at 100%, 80%, 60%, or 40%) over 60 days. We observed a reduction in plant height and biomass accumulation related to the decrease in water availability; physiological and biochemical parameters indicated that water-deficit stress reduced the plants’ C assimilation and increased their production of bioactive compounds. BRS BLD Yari and BRS BLD Aupaba had a higher tolerance to low water availability, whereas the EC40 and BRS 408 genotypes experienced a more pronounced reduction in growth and biomass accumulation. Understanding how different yerba mate genotypes respond to water deficit is essential for favoring species conservation and developing climate-adapted breeding programs.

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Section: Resultsmentioning

confidence: 57%

Morphological, physiological, and biochemical responses of yerba mate (Ilex paraguariensis) genotypes to water deficit

Gabira,

Bergeron,

Duarte

et al. 2023

Preprint

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“…The evaporative demand of water increases with temperature; therefore, leaf hydraulic responses are important to cope with the increase of leaf-to-air vapor pressure deficit [51]. Coordination between leaf hydraulics and leaf gas exchange is key for the balance of carbon gain and water loss [52,53]. Here, the relative water content (% RWC) and leaf water potential (Ψ md ) of A. clivicola were insensitive to heat waves, whereas A. deserticola displayed a significant decrease in both parameters (Figure 3B,C).…”

Section: Discussionmentioning

confidence: 99%

Two Congeneric Shrubs from the Atacama Desert Show Different Physiological Strategies That Improve Water Use Efficiency under a Simulated Heat Wave

Ostria-Gallardo,

Zúñiga-Contreras,

Carvajal

et al. 2023

Plants

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Desert shrubs are keystone species for plant diversity and ecosystem function. Atriplex clivicola and Atriplex deserticola (Amaranthaceae) are native shrubs from the Atacama Desert that show contrasting altitudinal distribution (A. clivicola: 0–700 m.a.s.l.; A. deserticola: 1500–3000 m.a.s.l.). Both species possess a C4 photosynthetic pathway and Kranz anatomy, traits adaptive to high temperatures. Historical records and projections for the near future show trends in increasing air temperature and frequency of heat wave events in these species’ habitats. Besides sharing a C4 pathway, it is not clear how their leaf-level physiological traits associated with photosynthesis and water relations respond to heat stress. We studied their physiological traits (gas exchange, chlorophyll fluorescence, water status) before and after a simulated heat wave (HW). Both species enhanced their intrinsic water use efficiency after HW but via different mechanisms. A. clivicola, which has a higher LMA than A. deserticola, enhances water saving by closing stomata and maintaining RWC (%) and leaf Ψmd potential at similar values to those measured before HW. After HW, A. deserticola showed an increase of Amax without concurrent changes in gs and a significant reduction of RWC and Ψmd. A. deserticola showed higher values of Chla fluorescence after HW. Thus, under heat stress, A. clivicola maximizes water saving, whilst A. deserticola enhances its photosynthetic performance. These contrasting (eco)physiological strategies are consistent with the adaptation of each species to their local environmental conditions at different altitudes.

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“…Crop-type information makes it possible to map agricultural land use intensity about crop sequences. The duration and diversity of crop sequences directly impact landscape complexity [5], [6] and can, consequently, lead to a decline in yields as soils are depleted, pest infestations are more likely, and pollinators or biological agents are deprived of resources [7], [8], [9]. Reliable information must be available on crops so that agricultural management can be improved, and costs can be reduced.…”

Section: Introductionmentioning

confidence: 99%

Crop Type Classification by DESIS Hyperspectral Imagery and Machine Learning Algorithms

Farmonov

Amankulova

Szatmári

et al. 2023

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Developments in space-based hyperspectral sensors, advanced remote sensing, and machine learning can help crop yield measurement, modelling, prediction, and crop monitoring for loss prevention and global food security. However, precise and continuous spectral signatures, important for large-area crop growth monitoring and early prediction of yield production with cutting-edge algorithms, can be only provided via hyperspectral imaging. Therefore, this article used new-generation Deutsches Zentrum für Luft-und Raumfahrt Earth Sensing Imaging Spectrometer (DESIS) images to classify the main crop types (hybrid corn, soybean, sunflower, and winter wheat) in Mezőhegyes (southeastern Hungary). A Wavelet-attention convolutional neural network (WA-CNN), random forest and support vector machine (SVM) algorithms were utilized to automatically map the crops over the agricultural lands. The best accuracy was achieved with the WA-CNN, a feature-based deep learning algorithm and a combination of two images with overall accuracy (OA) value of 97.89%and the user's accuracy producer's accuracy was from 97% to 99%. To obtain this, first, factor analysis was introduced to decrease the size of the hyperspectral image data cube. A wavelet transform was applied to extract important features and combined with the spectral attention mechanism CNN to gain higher accuracy in mapping crop types. Followed by SVM algorithm reported OA of 87.79%, with the producer's and user's accuracies of its classes ranging from 79.62% to 96.48% and from 79.63% to 95.73%, respectively. These results demonstrate the potentiality of DESIS data to observe the growth of different crop types and predict the harvest volume, which is crucial for farmers, smallholders, and decision-makers.

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The interplay between leaf water potential and osmotic adjustment on photosynthetic and growth parameters of tropical dry forest trees

Cited by 6 publications

References 49 publications

Morphological, physiological, and biochemical responses of yerba mate (Ilex paraguariensis) genotypes to water deficit

Morphological, physiological, and biochemical responses of yerba mate (Ilex paraguariensis) genotypes to water deficit

Two Congeneric Shrubs from the Atacama Desert Show Different Physiological Strategies That Improve Water Use Efficiency under a Simulated Heat Wave

Crop Type Classification by DESIS Hyperspectral Imagery and Machine Learning Algorithms

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