How plant allometry influences bud phenology and fruit yield in two Vaccinium species

Fournier, Marie-Pier; Paré, Maxime C.; Buttò, Valentinà; Delagrange, Sylvain; Lafond, Jean; Deslauriers, Annie

doi:10.1093/aob/mcaa083

Cited by 18 publications

(31 citation statements)

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“…This explains positive associations between yield-related traits and stem structural traits, which need further physiological studies to confirm. It was previously observed in wild blueberries that greater stem length is related to higher fruit biomass [12]. Additionally, genotypes with a higher StemL might be benefitted in terms of successful pollination by bees, which is one of the major yield determining factors of wild blueberries [46].…”

Section: Discussionmentioning

confidence: 96%

“…Thus, these features can be considered the parts of a developmental module that dictates crop performance and yield; the optimization of these developmental features is essential for the efficient performance of crop plants. Genotypes of wild blueberries with a greater vegetative biomass, which is represented by several structural traits, i.e., stem height and number of leaves, can produce more flowers, which ultimately results in higher fruit biomass [12]. Plant stem height and diameter are closely related to biomass production and are important morphological traits affecting yield performance [10].…”

Section: Introductionmentioning

confidence: 99%

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High Variation in Yield among Wild Blueberry Genotypes: Can Yield Be Predicted by Leaf and Stem Functional Traits?

et al. 2022

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Wild lowbush blueberry fields are characterized by high genetic diversity, with a large number of genotypes coexisting in every field. Yield also varies among genotypes, which could be related to the variation in physiological and structural traits, but this has not been rigorously tested. In this study, we aimed to quantify the inter-genotype variation in yield, as well as leaf and stem functional traits, and to establish the relationship between functional traits and yield-related traits in wild blueberries. To do so, we carried out a study during the 2019 harvest season measuring structural and functional traits including stem number, stem length, stem diameter, leaf chlorophyll concentration, leaf mass area, leaf area per stem, leaf number per stem, number of branches per stem, leaf temperature, soil temperature, and soil water content and yield data including yield, berry size (weight of 100 berries), number of berries per stem, and length of berry cluster from two wild blueberry farms. We found high variations in structural, functional, and yield-related traits among genotypes, but not between two fields. We also found negative associations of the leaf mass per unit area and midday leaf temperature with the yield, whereas the leaf chlorophyll concentration was positively associated with the yield. Additionally, we found a quadratic correlation between yield-related traits (weight of 100 berries, number of berries per stem, and length of berry cluster) and stem length, with the optimum stem length for yield at 25 cm. Our results suggest that several leaf and stem functional traits are correlated with yield-related traits; thereby, those traits can be used to predict wild blueberry yields. Our findings could help growers and breeders select better-yielding genotypes based on structural and functional traits.

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Section: Discussionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

High Variation in Yield among Wild Blueberry Genotypes: Can Yield Be Predicted by Leaf and Stem Functional Traits?

et al. 2022

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“…In diffuse-porous species, BAI and the number of vessels decreased in 2012, while stem elongation and the number of total ramifications decreased slightly in 2012 and more strongly in the following year, i.e., 2013. The number of shoots and lateral branches is predetermined and depends upon carbon storage of the previous year ( Fournier et al, 2020 ). We observed that the number of total ramifications strongly depends upon SPEI 3 variation during the previous year, especially in diffuse-porous species.…”

Section: Discussionmentioning

confidence: 99%

Contrasting Carbon Allocation Strategies of Ring-Porous and Diffuse-Porous Species Converge Toward Similar Growth Responses to Drought

et al. 2021

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Extreme climatic events that are expected under global warming expose forest ecosystems to drought stress, which may affect the growth and productivity. We assessed intra-annual growth responses of trees to soil water content in species belonging to different functional groups of tree-ring porosity. We pose the hypothesis that species with contrasting carbon allocation strategies, which emerge from different relationships between wood traits and canopy architecture, display divergent growth responses to drought. We selected two diffuse-porous species (Acer saccharum and Betula alleghaniensis) and two ring-porous species (Quercus rubra and Fraxinus americana) from the mixed forest of Quebec (Canada). We measured anatomical wood traits and canopy architecture in eight individuals per species and assessed tree growth sensitivity to water balance during 2008–2017 using the standardized precipitation evapotranspiration index (SPEI). Stem elongation in diffuse-porous species mainly depended upon the total number of ramifications and hydraulic diameter of the tree-ring vessels. In ring-porous species, stem elongation mainly depended upon the productivity of the current year, i.e., number of vessels and basal area increment. Diffuse-porous and ring-porous species had similar responses to soil water balance. The effect of soil water balance on tree growth changed during the growing season. In April, decreasing soil temperature linked to wet conditions could explain the negative relationship between SPEI and tree growth. In late spring, greater water availability affected carbon partitioning, by promoting the formation of larger xylem vessels in both functional groups. Results suggest that timings and duration of drought events affect meristem growth and carbon allocation in both functional groups. Drought induces the formation of fewer xylem vessels in ring-porous species, and smaller xylem vessels in diffuse-porous species, the latter being also prone to a decline in stem elongation due to a reduced number of ramifications. Indeed, stem elongation of diffuse-porous species is influenced by environmental conditions of the previous year, which determine the total number of ramifications during the current year. Drought responses in different functional groups are thus characterized by different drivers, express contrasting levels of resistance or resilience, but finally result in an overall similar loss of productivity.

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“…The first investigative model considered seasonal mean temperature, total precipitations, and number of freezing days—days with minimum mean temperature <−5 °C [ 44 ]—between April and August inclusively in vegetative and fruit-bearing years. The second investigative model considered mean temperatures and total precipitations for phenological stages described by Fournier et al [ 45 ] and presented in Table 1 .…”

Section: Methodsmentioning

confidence: 99%

Conditioning Machine Learning Models to Adjust Lowbush Blueberry Crop Management to the Local Agroecosystem

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Lafond

Paré

et al. 2020

Plants

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Agroecosystem conditions limit the productivity of lowbush blueberry. Our objectives were to investigate the effects on berry yield of agroecosystem and crop management variables, then to develop a recommendation system to adjust nutrient and soil management of lowbush blueberry to given local meteorological conditions. We collected 1504 observations from N-P-K fertilizer trials conducted in Quebec, Canada. The data set, that comprised soil, tissue, and meteorological data, was processed by Bayesian mixed models, machine learning, compositional data analysis, and Markov chains. Our investigative statistical models showed that meteorological indices had the greatest impact on yield. High mean temperature at flower bud opening and after fruit maturation, and total precipitation at flowering stage showed positive effects. Low mean temperature and low total precipitation before bud opening, at flowering, and by fruit maturity, as well as number of freezing days (<−5 °C) before flower bud opening, showed negative effects. Soil and tissue tests, and N-P-K fertilization showed smaller effects. Gaussian processes predicted yields from historical weather data, soil test, fertilizer dosage, and tissue test with a root-mean-square-error of 1447 kg ha−1. An in-house Markov chain algorithm optimized yields modelled by Gaussian processes from tissue test, soil test, and fertilizer dosage as conditioned to specified historical meteorological features, potentially increasing yield by a median factor of 1.5. Machine learning, compositional data analysis, and Markov chains allowed customizing nutrient management of lowbush blueberry at local scale.

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How plant allometry influences bud phenology and fruit yield in two Vaccinium species

Cited by 18 publications

References 50 publications

High Variation in Yield among Wild Blueberry Genotypes: Can Yield Be Predicted by Leaf and Stem Functional Traits?

High Variation in Yield among Wild Blueberry Genotypes: Can Yield Be Predicted by Leaf and Stem Functional Traits?

Contrasting Carbon Allocation Strategies of Ring-Porous and Diffuse-Porous Species Converge Toward Similar Growth Responses to Drought

Conditioning Machine Learning Models to Adjust Lowbush Blueberry Crop Management to the Local Agroecosystem

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