scholarly journals Acclimation of Leaf Nitrogen to Vertical Light Gradient at Anthesis in Wheat Is a Whole-Plant Process That Scales with the Size of the Canopy

2012 ◽  
Vol 160 (3) ◽  
pp. 1479-1490 ◽  
Author(s):  
Delphine Moreau ◽  
Vincent Allard ◽  
Oorbessy Gaju ◽  
Jacques Le Gouis ◽  
M. John Foulkes ◽  
...  
Keyword(s):  
Leaf Nitrogen ◽  
Light Gradient ◽  
Whole Plant ◽  
Plant Process

Herbaceous monocot plant form and function along a tropical rain-forest light gradient: a reversal of dicot strategy

2009 ◽  
Vol 25 (1) ◽  
pp. 103-106 ◽  
Author(s):  
Nathan G. Swenson
Keyword(s):  
Tropical Forests ◽  
Environmental Gradients ◽  
Plant Performance ◽  
Seed Plants ◽  
Form And Function ◽  
Light Gradient ◽  
Whole Plant ◽  
Plant Form ◽  
And Function ◽  
High Degree

Whole plant form and function vary spectacularly across the seed plants. In recent years, plant evolutionary ecologists have begun to document this diversity on large geographic scales by analysing ‘functional traits’ that are indicative of whole plant performance across environmental gradients (Swenson & Enquist 2007, Wright et al. 2004). Despite the high degree of functional diversity in tropical forests, convergence in function does occur locally along successional or light gradients (Bazzaz & Pickett 1980, Swaine & Whitmore 1988).

Incorporating sulfur reactions and interactions with iron and phosphorus into a general plant-wide model

2018 ◽  
Vol 79 (1) ◽  
pp. 26-34 ◽  
Author(s):  
Hélène Hauduc ◽  
Tanush Wadhawan ◽  
Bruce Johnson ◽  
Charles Bott ◽  
Matthew Ward ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Optimization Design ◽  
Oxygen Demand ◽  
Phosphorus Release ◽  
Sulfur Cycle ◽  
Precipitate Formation ◽  
Treatment Processes ◽  
Whole Plant ◽  
Plant Process ◽  
P Removal

Abstract Sulfur causes many adverse effects in wastewater treatment and sewer collection systems, such as corrosion, odours, increased oxygen demand, and precipitate formation. Several of these are often controlled by chemical addition, which will impact the subsequent wastewater treatment processes. Furthermore, the iron reactions, resulting from coagulant addition for chemical P removal, interact with the sulfur cycle, particularly in the digester with precipitate formation and phosphorus release. Despite its importance, there is no integrated sulfur and iron model for whole plant process optimization/design that could be readily used in practice. After a detailed literature review of chemical and biokinetic sulfur and iron reactions, a plant-wide model is upgraded with relevant reactions to predict the sulfur cycle and iron cycle in sewer collection systems, wastewater and sludge treatment. The developed model is applied on different case studies.

scholarly journals Whole‐plant optimality predicts changes in leaf nitrogen under variable CO 2 and nutrient availability

2019 ◽  
Vol 225 (6) ◽  
pp. 2331-2346 ◽  
Author(s):  
Silvia Caldararu ◽  
Tea Thum ◽  
Lin Yu ◽  
Sönke Zaehle
Keyword(s):  
Nutrient Availability ◽  
Leaf Nitrogen ◽  
Whole Plant

scholarly journals Capturing and Selecting Senescence Variation in Wheat

2020 ◽  
Author(s):  
Elizabeth A. Chapman ◽  
Simon Orford ◽  
Jacob Lage ◽  
Simon Griffiths
Keyword(s):  
Genetic Mapping ◽  
Leaf Senescence ◽  
Quantitative Trait ◽  
Flag Leaf ◽  
Visual Assessment ◽  
Thermal Time ◽  
Singular Metrics ◽  
Whole Plant ◽  
Holistic Understanding ◽  
Plant Process

AbstractSenescence is a highly quantitative trait, but in wheat the genetics underpinning senescence regulation remain relatively unknown. To select senescence variation, and ultimately identify novel genetic regulators, accurate characterisation of senescence phenotypes is essential. When investigating senescence, phenotyping efforts often focus on, or are limited to, visual assessment of the flag leaves. However, senescence is a whole plant process, involving remobilisation and translocation of resources into the developing grain. Furthermore, the temporal progression of senescence poses challenges regarding trait quantification and description, whereupon the different models and approaches applied result in varying definitions of apparently similar metrics.To gain a holistic understanding of senescence we phenotyped flag leaf and peduncle senescence progression, alongside grain maturation. Reviewing the literature, we identified techniques commonly applied in quantification of senescence variation and developed simple methods to calculate descriptive and discriminatory metrics. To capture senescence dynamism, we developed the idea of calculating thermal time to different flag leaf senescence scores, for which between year Spearman’s rank correlations of r ≥ 0.59, P < 4.7 × 10−5(TT70), identify as an accurate phenotyping method. Following our experience of senescence trait genetic mapping, we recognised the need for singular metrics capable of discriminating senescence variation, identifying Thermal Time to Flag Leaf Senescence score of 70 (TT70) and Mean Peduncle senescence (MeanPed) scores as most informative. Moreover, grain maturity assessments confirmed a previous association between our staygreen traits and grain fill extension, illustrating trait functionality.Here we review different senescence phenotyping approaches and share our experiences of phenotyping two independent RIL populations segregating for staygreen traits. Together, we direct readers towards senescence phenotyping methods we found most effective, encouraging their use when investigating and discriminating senescence variation of differing genetic bases, and to aid trait selection and weighting in breeding and research programs alike.

scholarly journals Capturing and Selecting Senescence Variation in Wheat

2021 ◽  
Vol 12 ◽  
Author(s):  
Elizabeth A. Chapman ◽  
Simon Orford ◽  
Jacob Lage ◽  
Simon Griffiths
Keyword(s):  
Leaf Senescence ◽  
Recombinant Inbred ◽  
Flag Leaf ◽  
Visual Assessment ◽  
Thermal Time ◽  
Singular Metrics ◽  
Whole Plant ◽  
Holistic Understanding ◽  
Plant Process

Senescence is a highly quantitative trait, but in wheat the genetics underpinning senescence regulation remain relatively unknown. To select senescence variation and ultimately identify novel genetic regulators, accurate characterization of senescence phenotypes is essential. When investigating senescence, phenotyping efforts often focus on, or are limited to, the visual assessment of flag leaves. However, senescence is a whole-plant process, involving remobilization and translocation of resources into the developing grain. Furthermore, the temporal progression of senescence poses challenges regarding trait quantification and description, whereupon the different models and approaches applied result in varying definitions of apparently similar metrics. To gain a holistic understanding of senescence, we phenotyped flag leaf and peduncle senescence progression, alongside grain maturation. Reviewing the literature, we identified techniques commonly applied in quantification of senescence variation and developed simple methods to calculate descriptive and discriminatory metrics. To capture senescence dynamism, we developed the idea of calculating thermal time to different flag leaf senescence scores, for which between-year Spearman’s rank correlations of r ≥ 0.59, P &lt; 4.7 × 10–5 (TT70), identify as an accurate phenotyping method. Following our experience of senescence trait genetic mapping, we recognized the need for singular metrics capable of discriminating senescence variation, identifying thermal time to flag leaf senescence score of 70 (TT70) and mean peduncle senescence (MeanPed) scores as most informative. Moreover, grain maturity assessments confirmed a previous association between our staygreen traits and grain fill extension, illustrating trait functionality. Here we review different senescence phenotyping approaches and share our experiences of phenotyping two independent recombinant inbred line (RIL) populations segregating for staygreen traits. Together, we direct readers toward senescence phenotyping methods we found most effective, encouraging their use when investigating and discriminating senescence variation of differing genetic bases, and aid trait selection and weighting in breeding and research programs alike.

scholarly journals Adaptation to Sun and Shade: a Whole-Plant Perspective

1988 ◽  
Vol 15 (2) ◽  
pp. 63 ◽  
Author(s):  
TJ Givnish
Keyword(s):  
Biotic Interactions ◽  
Tree Height ◽  
Light Response ◽  
Leaf Nitrogen ◽  
Compensation Point ◽  
Carbon Gain ◽  
Leaf Nitrogen Content ◽  
Energy Capture ◽  
Irradiance Level ◽  
Whole Plant

Whole-plant energy capture depends not only on the photosynthetic response of individual leaves, but also on their integration into an effective canopy, and on the costs of producing and maintaining their photosynthetic capacity. This paper explores adaptation to irradiance level in this context, focusing on traits whose significance would be elusive if considered in terms of their impact at the leaf level alone. I review traditional approaches used to demonstrate or suggest adaptation to irradiance level, and outline three energetic tradeoffs likely to shape such adaptation, involving the economics of gas exchange, support, and biotic interactions. Recent models using these tradeoffs to account for trends in leaf nitrogen content, stornatal conductance, phyllotaxis, and defensive allocations in sun v. shade are evaluated. A re-evaluation of the classic study of acclimation of the photosynthetic light response in Atriplex, crucial to interpreting adaptation to irradiance in many traits, shows that it does not completely support the central dogma of adaptation to sun v. shade unless the results are analysed in terms of whole-plant energy capture. Calculations for Liriodendron show that the traditional light compensation point has little meaning for net carbon gain, and that the effective compensation point is profoundly influenced by the costs of night leaf respiration, leaf construction, and the construction of associated support and root tissue. The costs of support tissue are especially important, raising the effective compensation point by 140 �mol m-2 s-1 in trees 1 m tall, and by nearly 1350 �mol m-2 s-1 in trees 30 m tall. Effective compensation points give maximum tree heights as a function of irradiance, and shade tolerance as a function of tree height; calculations of maximum permissible height in Liriodendron correspond roughly with the height of the tallest known individual. Finally, new models for the evolution of canopy width/height ratio in response to irradiance and coverage within a tree stratum, and for the evolution of mottled leaves as a defensive measure in understory herbs, are outlined.

scholarly journals Whole-plant optimality predicts changes in leaf nitrogen under variable CO2 and nutrient availability

2019 ◽  
Author(s):  
Silvia Caldararu ◽  
Tea Thum ◽  
Lin Yu ◽  
Sönke Zaehle
Keyword(s):  
Plant Growth ◽  
Nutrient Limitation ◽  
Leaf Nitrogen ◽  
List Type ◽  
Carbon Export ◽  
N Content ◽  
Foliar N ◽  
Whole Plant ◽  
Leaf N Content ◽  
Leaf N

SummaryVegetation nutrient limitation is essential for understanding ecosystem responses to global change. In particular, leaf nitrogen (N) is known to be plastic under changed nutrient limitation. However, models can often not capture these observed changes, leading to erroneous predictions of whole-ecosystem stocks and fluxes.We hypothesise that an optimality approach can improve representation of leaf N content compared to existing empirical approaches. Unlike previous optimality-based approaches, which adjust foliar N concentrations based on canopy carbon export, we use a maximisation criteria based on whole-plant growth and allow for a lagged response of foliar N to this maximisation criterion to account for the limited plasticity of this plant trait. We test these model variants at a range of Free-Air CO2 Enrichment (FACE) and N fertilisation experimental sites.We show a model solely based on canopy carbon export fails to reproduce observed patterns and predicts decreasing leaf N content with increased N availability. However, an optimal model which maximises total plant growth can correctly reproduce the observed patterns.The optimality model we present here is a whole-plant approach which reproduces biologically realistic changes in leaf N and can thereby improve ecosystem-level predictions under transient conditions.

scholarly journals Detection and Dynamic Variation Characteristics of Rice Nitrogen Status after Anthesis Based on the RGB Color Index

Agronomy ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 1739
Author(s):  
Kaocheng Zhao ◽  
Ying Ye ◽  
Jun Ma ◽  
Lifen Huang ◽  
Hengyang Zhuang
Keyword(s):  
Nitrogen Content ◽  
Hybrid Rice ◽  
Leaf Nitrogen ◽  
Leaf Nitrogen Content ◽  
Japonica Rice ◽  
Rice Varieties ◽  
Nitrogen Levels ◽  
Monitoring Model ◽  
Whole Plant ◽  
Rice Leaves

We aimed to elucidate the color changes of rice leaves after anthesis and create an algorithm for monitoring the nitrogen contents of rice leaves and of the whole plant. Hence, we aimed to provide a theoretical basis for the precise management of rice nitrogen fertilizer and the research and development of digital image nutrition monitoring equipment and reference. We selected the leaf colors of the main stems of four major rice varieties promoted in production, including Huaidao 5 (late-maturing medium japonica rice), Yangjing 4227 (early maturing late japonica rice), Changyou 5 (late japonica hybrid rice), and Yongyou 8 (late japonica hybrid rice). Under different nitrogen levels, the leaf R, G, and B values of the four rice varieties at different stages after anthesis, the dynamic changes in RGB normalized values, the correlations between RGB normalized values and leaf SPAD values, the leaf nitrogen content and whole plant nitrogen content, and the nitrogen prediction model were studied. The research results demonstrate the following: (1) regardless of nitrogen levels, the leaf of R, G, B, NRI, NGI and NBI of different rice varieties after anthesis followed the order, G > R > B. R, G, NRI, NGI, and days after heading could be fitted according to a logarithmic equation, y = aebx (0.726 ≤ R2 ≤ 0.992); B, NBI, and days after heading could be fitted using a linear equation, y = a + bx (0.863 ≤ R2 ≤ 0.992). Both fitting effects were significant (except NGI). (2) A quadratic function (Y = −1296.192x2 + 539.419x − 10.914; Y = −1173.104x2 + 527.073x − 12.993) was adopted to construct a monitoring model for the NBI and SPAD values of japonica rice and hybrid japonica rice leaves after anthesis and the R2 values were 0.902 and 0.838, respectively. Exponential functions (Y = 5.698e7.261x; Y = 3.371e9.326x) were employed to construct monitoring models of leaf nitrogen content, and the R2 values were 0.833 and 0.706, respectively. Exponential functions (Y = 5.145e4.9143x; Y = 3.966e5.364x) were also used to construct a monitoring model for the nitrogen content of the whole plant, and the R2 values were 0.737 and 0.511, respectively. The results obtained from prediction tests by using Determination Coefficient (R2), Relative Percent Deviation (RPD), and Root Mean Square Error (RMSE) showed that it was feasible, accurate, and efficient to use a scanner for measuring the nitrogen content of rice.

Sign in / Sign up

Export Citation Format

Share Document