Plant Partitioning Research Articles

Phloem transport of amino acids is differentially altered by phosphorus deficiency according to the nitrogen availability in young barley plants

The phloem transport of amino acids is a key step in the efficient use of nitrogen (N). Despite the importance of this issue, little information is known about the regulation of phloem transport of amino acids in plants with low phosphorus (P) supply and even less in relation to N availability. To this end, we studied not only the assimilate partitioning in young barley plants grown with low N or/and P supply, but also we analyzed the implications of the different isoforms of glutamine synthetase, cytokinin oxidase/dehydrogenase 2 and several senescence-related proteases. Our results demonstrated that low P supply causes an accumulation of different nitrogenous compounds in expanded leaves depending on N availability and an inhibition of the phloem exudation rate of amino acids only in high-N plants, indicating an interaction between N and P in the establishment of N-partitioning. The accumulation of nitrogenous compounds in leaves of low-P plants without the accompaniment in amino acid export to the phloem was not related to an increase in nitrate assimilation pathway neither with the modulation of glutamine synthetase 1_1 expression, as it had been observed for N availability. But, these results could be explained as a consequence of a delay in the transition from sink to source of leaves, thus keeping the older leaves as sink organs, as indicated by the increase in cytokinin oxidase/dehydrogenase 2 expression and the repression of several senescence-related proteases in low-P plants with good availability of N.

Dry matter and nutrient partitioning in Castor plants in two growing seasons

The aim of the present study was to evaluate dry matter partitioning and macro- and micronutrient accumula­tion and distribution in small-sized castor plants grown in season and off-season. The experiments were conducted during the 2005-2006 season and in the 2006 off-season in an Oxisol. A completely randomized block design was used, with eight replications. Plots consisted of plant sampling periods, which were con­ducted in the vegetative period (17 days after emergence - DAE), the grain fill period (between 73 and 80 DAE) and at end of the cycle (120 DAE). Castor leaves accumulated most of dry matter (DM) and macro- and micronutrients in the vegetative period, regardless of the growing period. In the following cycle periods, most of biomass and nutrients were located in the reproductive structures and grains, especially in the off-season crop. It was concluded that leaves and stems are strong nutrient sinks in the castor plant in season crops, while lower water availability during off-season induces plants to use physiological mechanisms to allocate more resources (biomass and nutrients) for their reproduction.

Consistency of spectral hypergraph partitioning under planted partition model

Hypergraph partitioning lies at the heart of a number of problems in machine learning and network sciences. Many algorithms for hypergraph partitioning have been proposed that extend standard approaches for graph partitioning to the case of hypergraphs. However, theoretical aspects of such methods have seldom received attention in the literature as compared to the extensive studies on the guarantees of graph partitioning. For instance, consistency results of spectral graph partitioning under the stochastic block model are well known. In this paper, we present a planted partition model for sparse random non-uniform hypergraphs that generalizes the stochastic block model. We derive an error bound for a spectral hypergraph partitioning algorithm under this model using matrix concentration inequalities. To the best of our knowledge, this is the first consistency result related to partitioning non-uniform hypergraphs.

A simple spectral algorithm for recovering planted partitions

Abstract In this paper, we consider the planted partition model, in which n = ks vertices of a random graph are partitioned into k “clusters,” each of size s. Edges between vertices in the same cluster and different clusters are included with constant probability p and q, respectively (where 0 ≤ q < p ≤ 1). We give an efficient algorithm that, with high probability, recovers the clusters as long as the cluster sizes are are least (√n). Informally, our algorithm constructs the projection operator onto the dominant k-dimensional eigenspace of the graph’s adjacency matrix and uses it to recover one cluster at a time. To our knowledge, our algorithm is the first purely spectral algorithm which runs in polynomial time and works even when s = Θ (√n), though there have been several non-spectral algorithms which accomplish this. Our algorithm is also among the simplest of these spectral algorithms, and its proof of correctness illustrates the usefulness of the Cauchy integral formula in this domain.

Lower grain nitrogen content of wheat at elevated CO2 can be improved through post-anthesis NH4+ supplement

We test the hypothesis that reduction in grain N concentration under elevated CO2 concentration (e[CO2]) is associated with N types (NH4+ and NO3−) and their ratios. Wheat (Triticum aestivum L. cv. H45) was grown in a glasshouse under two CO2 concentrations (389 μmol mol−1 and 700 μmol mol−1), supplied with equal amount of N with different ratios of NH4+ and NO3−: (i) 100% NO3−–N; (ii) 50% NO3−–N and 50% NH4+–N; and (iii) 25% NO3−–N and 75% NH4+–N. Plant growth, N uptake and partitioning were measured during plant development. Plant biomass and grain yield was increased at e[CO2] when N was supplied as an equal proportion of NO3− and NH4+. Despite the yield increment, grain N concentration was not affected by e[CO2], in 50% NO3−–N treatment. In contrast, grain N concentration decreased in 100% NO3−–N and 25% NO3−–N treatments. In 50% NO3−–N treatment, N uptake during post-anthesis stage (from 69 to 141 days after planting) was significantly stimulated under e[CO2] compared to 100% NO3−–N and 25% NO3−–N treatments. We concluded that supplement of N in an equal proportion of NO3− and NH4+ which increases post-anthesis N uptake, avoid the reduction of grain N concentration under e[CO2].

Clustering from general pairwise observations with applications to time-varying graphs

We present a general framework for graph clustering and bi-clustering where we are given a general observation (called a label) between each pair of nodes. This framework allows a rich encoding of various types of pairwise interactions between nodes. We propose a new tractable and robust approach to this problem based on convex optimization and maximum likelihood estimators. We analyze our algorithms under a general statistical model extending the planted partition and stochastic block models. Both sufficient and necessary conditions are provided for successful recovery of the underlying clusters. Our theoretical results subsume many existing graph clustering results for a wide range of settings, including planted partition, weighted clustering, submatrix localization and partially observed graphs. Furthermore, our results are applicable to novel settings including time-varying graphs, providing new insights to solutions of these problems. We provide empirical results on both synthetic and real data that corroborate with our theoretical findings.

Equivalence between modularity optimization and maximum likelihood methods for community detection.

We demonstrate an equivalence between two widely used methods of community detection in networks, the method of modularity maximization and the method of maximum likelihood applied to the degree-corrected stochastic block model. Specifically, we show an exact equivalence between maximization of the generalized modularity that includes a resolution parameter and the special case of the block model known as the planted partition model, in which all communities in a network are assumed to have statistically similar properties. Among other things, this equivalence provides a mathematically principled derivation of the modularity function, clarifies the conditions and assumptions of its use, and gives an explicit formula for the optimal value of the resolution parameter.

Phosphorus uptake, partitioning and redistribution during grain filling in rice.

In cultivated rice, phosphorus (P) in grains originates from two possible sources, namely exogenous (post-flowering root P uptake from soil) or endogenous (P remobilization from vegetative parts) sources. This study investigates P partitioning and remobilization in rice plants throughout grain filling to resolve contributions of P sources to grain P levels in rice. Rice plants (Oryza sativa 'IR64') were grown under P-sufficient or P-deficient conditions in the field and in hydroponics. Post-flowering uptake, partitioning and re-partitioning of P was investigated by quantifying tissue P levels over the grain filling period in the field conditions, and by employing 33P isotope as a tracer in the hydroponic study. Post-flowering P uptake represented 40-70% of the aerial plant P accumulation at maturity. The panicle was the main P sink in all studies, and the amount of P potentially remobilized from vegetative tissues to the panicle during grain filling was around 20% of the total aerial P measured at flowering. In hydroponics, less than 20% of the P tracer taken up at 9 d after flowering (DAF) was found in the above-ground tissues at 14 DAF and half of it was partitioned to the panicle in both P treatments. The results demonstrate that P uptake from the soil during grain filling is a critical contributor to the P content in grains in irrigated rice. The P tracer study suggests that the mechanism of P loading into grains involves little direct transfer of post-flowering P uptake to the grain but rather substantial mobilization of P that was previously taken up and stored in vegetative tissues.

Impacts of nitrogen fertilizer on major insect pests and their predators in transgenic Bt rice lines T2A‐1 and T1C‐19

AbstractNitrogen is a critical factor for plant development and nitrogen input is one of the important tactics to enhance the development and yield of crops. Nevertheless, nitrogen input could influence the occurrence of insects positively or negatively. Nitrogen is also one of the main elements composing the insecticidal crystal (Cry) protein. Cry protein production could affect nitrogen partitioning in Bt plants and as such nitrogen input may influence insect pest management in transgenic Bt rice, Oryza sativa L. (Poaceae). To test this possibility, we evaluated the impacts of nitrogen regimes on the main insect pests and their predators on two Bt rice lines, T2A‐1 and T1C‐19, expressing Cry2A and Cry1C, respectively, and their non‐transgenic parental counterpart MH63. The results showed that Cry proteins with different nitrogen regimes have enough insecticidal activity on rice leaffolder, Cnaphalocrocis medinalis Guenée (Lepidoptera: Crambidae), in both laboratory and field experiments. Laboratory studies indicated that relevant parameters of ecological fitness in brown planthopper, Nilaparvata lugens (Stål) (Hemiptera: Delphacidae), a non‐target insect pest, were significantly affected by nitrogen input both on Bt and MH63 rice lines. Nymphal survival, female adult longevity, and egg hatchability in N. lugens differed significantly among rice varieties. The experiments conducted in rice fields also demonstrated that nitrogen was positively correlated with the abundance of N. lugens on Bt rice, similar to that on MH63 rice. The abundances of two predators – the wolf spider Pirata subpiraticus (Boesenberg & Strand) (Araneae: Lycosidae) and the bug Cyrthorhinus lividipennis Reuter (Hemiptera: Miridae) – were significantly affected by rice growth stages but not by nitrogen input and rice varieties. In conclusion, the above results indicate that high nitrogen regimes for Bt rice (T2A‐1 and T1C‐19) and non‐Bt rice (MH63) cannot facilitate the management of insect pests.

Performance of a community detection algorithm based on semidefinite programming

The problem of detecting communities in a graph is maybe one the most studied inference problems, given its simplicity and widespread diffusion among several disciplines. A very common benchmark for this problem is the stochastic block model or planted partition problem, where a phase transition takes place in the detection of the planted partition by changing the signal-to-noise ratio. Optimal algorithms for the detection exist which are based on spectral methods, but we show these are extremely sensible to slight modification in the generative model. Recently Javanmard, Montanari and Ricci-Tersenghi [1] have used statistical physics arguments, and numerical simulations to show that finding communities in the stochastic block model via semidefinite programming is quasi optimal. Further, the resulting semidefinite relaxation can be solved efficiently, and is very robust with respect to changes in the generative model. In this paper we study in detail several practical aspects of this new algorithm based on semidefinite programming for the detection of the planted partition. The algorithm turns out to be very fast, allowing the solution of problems with O(105) variables in few second on a laptop computer.

Seasonality and nitrogen supply modify carbon partitioning in understory vegetation of a boreal coniferous forest

AbstractGiven the strong coupling between the carbon (C) and nitrogen (N) cycles, there is substantial interest in understanding how N availability affects C cycling in terrestrial ecosystems, especially in ecosystems limited by N. However, most studies in temperate and boreal forests have focused on the effects of N addition on tree growth. By comparison, less is known about the effects of N availability on the cycling of C in understory vegetation despite some evidence that dwarf shrubs, mosses, and lichens play an important role in the forest C balance. In this study, we used an in situ 13CO2 pulse‐labeling technique to examine the short‐term dynamics of C partitioning in understory vegetation in three boreal Pinus sylvestris forest stands exposed to different rates of N addition: a low and high N addition that receive annual additions of NH4NO3 of 20 and 100 kg N/ha, respectively, and an unfertilized control. Labeling was conducted at two distinct periods (early vs. late growing season), which provided a seasonal picture of how N addition affects C dynamics in understory vegetation. In contrast to what has been found in trees, there was no obvious trend in belowground C partitioning in ericaceous plants in response to N additions or seasonality. Increasing N addition led to a greater percentage of 13C being incorporated into ericaceous leaves with a high turnover, whereas high rates of N addition strongly reduced the incorporation of 13C into less degradable moss tissues. Addition of N also resulted in a greater percentage of the 13C label being respired back to the atmosphere and an overall reduction in total understory carbon use efficiency. Taken together, our results suggest a faster cycling of C in understory vegetation with increasing N additions; yet the magnitude of this general response was strongly dependent on the amount of N added and varied seasonally. These results provide some of the first in situ C and N partitioning estimates for plants growing under the complex web of resource limitations in the boreal understory.

Biomass partitioning in grassland plants along independent gradients in temperature and precipitation

How plants allocate biomass to different parts strongly affects vegetation dynamics and ecosystem processes and services such as productivity and carbon storage. We tested the hypothesis that plant size explains the majority of variation in the size of plant parts (as predicted by allometric partitioning theory, APT) and that additional variation is explained by optimal responses for a given individual reproductive state and environment (as predicted by optimal partitioning theory, OPT) for alpine-lowland species pairs from three genera of grassland plants (Veronica, Viola and Carex) sampled along orthogonal gradients in temperature and precipitation. We found general patterns of allometric scaling (allometric exponents) of roots, stems, leaves and flowers, more or less as predicted by APT, and these patterns remained fairly constant across temperature and precipitation gradients. In contrast, basic allocation (allometric coefficients) was clearly related to climate, such as less allocation to leaves but more to roots, stems and flowers with increasing temperatures, in accordance with OPT. Furthermore, our results show that basic allocation is related to habitat affinity (alpine, lowland) and individual life-history states (reproductive or not) and that there is greater variability in small plants, which suggests that biomass partitioning theory should consider both the life-history and ecology of small plants to accurately predict climate-related grassland plant allocation and its implications.

Shoot growth restriction in dry matter partitioning andminituber production of potato plants

The aim of this research was to determine the effect of shoot growth restriction in the dry matter partitioning and minituber production of potato plants grown in a closed soilless system. Minitubers of the cultivars 'Macaca' and 'Asterix' were planted in the greenhouse in the density of 100 hills m-2, during autumn and spring growing seasons. Growth restriction levels were gotten by pruning shoots at 10, 20 and 30cm height or without pruning. The growth restriction levels were identified by their respective leaf area index. The experiment was a factorial (cultivars x growth restriction x growing season) in a random design, with four replications. Growth restriction affected the dry matter production of potato plants in both growing seasons and cultivars. Pruning potato plants at 30cm is a feasible technique to control leaf area index and it has lower effect on harvest index and number than in dry matter production of minitubers. Growth restriction does not change dry matter partitioning of potato plants grown in soilless system.

Seasonality and nitrogen supply modify carbon partitioning in understory vegetation of a boreal coniferous forest.

Given the strong coupling between the carbon (C) and nitrogen (N) cycles, there is substantial interest in understanding how N availability affects C cycling in terrestrial ecosystems, especially in ecosystems limited by N. However, most studies in temperate and boreal forests have focused on the effects of N addition on tree growth. By comparison, less is known about the effects of N availability on the cycling of C in understory vegetation despite some evidence that dwarf shrubs, mosses, and lichens play an important role in the forest C balance. In this study, we used an in situ 13CO2 pulse-labeling technique to examine the short-term dynamics of C partitioning in understory vegetation in three boreal Pinus sylvestris forest stands exposed to different rates of N addition: a low and high N addition that receive annual additions of NH4NO3 of 20 and 100 kg N/ha, respectively, and this is a typo. It should be an unfertilized control. Labeling was conducted at two distinct periods (early vs. late growing season), which provided a seasonal picture of how N addition affects C dynamics in understory vegetation. In contrast to what has been found in trees, there was no obvious trend in belowground C partitioning in ericaceous plants in response to N additions or seasonality. Increasing N addition led to a greater percentage of 13C being incorporated into ericaceous leaves with a high turnover, whereas high rates of N addition strongly reduced the incorporation of 13C into less degradable moss tissues. Addition of N also resulted in a greater percentage of the 13C label being respired back to the atmosphere and an overall reduction in total understory carbon use efficiency. Taken together, our results suggest a faster cycling of C in understory vegetation with increasing N additions; yet the magnitude of this general response was strongly dependent on the amount of N added and varied seasonally. These results provide some of the first in situ C and N partitioning estimates for plants growing under the complex web of resource limitations in the boreal understory.

Biomass, Nutrient, and Trace Element Accumulation and Partitioning in Cattail ( L.) during Wetland Phytoremediation of Municipal Biosolids.

Biomass and contaminant accumulation and partitioning in plants determine the harvest stage for optimum contaminant uptake during phytoremediation of municipal biosolids. This wetland microcosm bioassay characterized accumulation and partitioning of biomass, nutrients (N and P), and trace elements (Zn, Cu, Cr, and Cd) in cattail ( L.) in a growth room. Four cattail seedlings were transplanted into each 20-L plastic pail containing 3.9 kg (dry wt.) biosolids from an end-of-life municipal lagoon. A 10-cm-deep water column was maintained above the 12-cm-thick biosolids layer. Plants were harvested every 14 d over a period of 126 d for determination of aboveground biomass (AGB) and belowground biomass (BGB) yields, along with contaminant concentrations in these plant tissues. Logistic model fits to biomass yield data indicated no significant difference in asymptotic yield between AGB and BGB. Aboveground biomass accumulated significantly greater amounts of N and P and lower amounts of trace elements than BGB. Maximum N accumulation in AGB occurred 83 d after transplanting (DAT), and peak P uptake occurred at 86 DAT. Harvesting at maximum aboveground accumulation removed (percent of the initial element concentration in the biosolids) 4% N, 3% P, 0.05% Zn, 0.6% Cu, 0.1% Cd, and 0.2% Cr. Therefore, under the conditions of this study, phytoremediation would be most effective if cattail is harvested at 86 DAT. These results contribute toward the identification of the harvest stage that will optimize contaminant uptake and enhance in situ phytoremediation of biosolids using cattail.

The Assimilate Partitioning Importance for Heartwood Extractives Formation in Robinia Pseudoacacia l. of Different Ages

ABSTRACTThis study aimed to investigate the influence of tree age on the assimilates partitioning and its significance for the formation of heartwood extractives in Robinia pseudoacacia L. (black locust). Assimilate translocation in 6- and 15-year-old plants was measured in May and August 2006 using the 14CO2 feeding method. The heartwood extractives content in the sapwood-heartwood transition zone and in individual tree rings of the pure heartwood were analysed by HPLC-chromatography. All plants, buds and young leaves showed the strongest 14C specific activity compared to other plant parts in May and August(14C specific activity in buds/leaves of 6-years old plants: 35.2-37.0%, 15-years old plants: 31.4-32.2%). However, in plants labelled in August 2006 at the sapwood-heartwood transition zone also showed a strong assimilates sink, while only small amounts of assimilates were translocated to the sapwood-heartwood transition zone in the plants labelled in May 2006. The amount of assimilates transported to the sapwood-heartwood transition zone was significantly higher in the 15-year-old plants compared to the 6-year-old plants. This was monitored by a higher content of extractives in the heartwood formed by the older plants compared to heartwood formed by the younger plants. The results indicate that uneven assimilate partitioning in younger and older black locust plants affects the heartwood extractives formation, which might lead to a lower natural durability of the heartwood formed by younger trees compared to heartwood formed by older trees.

Biomass and bioenergy partitioning of sugarcane plants under water deficit

This study assessed the photosynthesis, biomass, and phytoenergy production in sugarcane plants subjected to water deficit during the initial stages of development. We hypothesize that the limitations imposed by water deficit on photosynthesis proportionally affect carbon balance, growth, and partitioning of phytoenergy in sugarcane. This study was carried out during 5 months in a growth chamber and water deficit was induced by maintaining soil moisture at 20 % of the maximum water holding capacity (WHC). As control, one group of plants was maintained at 100 % WHC. Water deficit reduced the carboxylation of Rubisco and PEPCase significantly, which were the main limiting factors for photosynthesis. As consequence, the daily leaf carbon balance was significantly reduced by drought. The total accumulated dry matter in well-watered plants was 3.6 times higher than in drought-stressed ones. Water deficit reduced the energy accumulated in sugarcane plants by approximately threefold. Regardless of water regime, a large fraction of the converted energy was not found in stalks. Under water deficit, less than 20 % of the energy is stored in stalks. Since only a tiny fraction of solar energy is used for the production of first generation ethanol, our study reinforces the importance of evaluating strategies to optimize the use of sugarcane, for example, harvesting plant organs other than stalks.

Limitations in the spectral method for graph partitioning: Detectability threshold and localization of eigenvectors.

Investigating the performance of different methods is a fundamental problem in graph partitioning. In this paper, we estimate the so-called detectability threshold for the spectral method with both un-normalized and normalized Laplacians in sparse graphs. The detectability threshold is the critical point at which the result of the spectral method is completely uncorrelated to the planted partition. We also analyze whether the localization of eigenvectors affects the partitioning performance in the detectable region. We use the replica method, which is often used in the field of spin-glass theory, and focus on the case of bisection. We show that the gap between the estimated threshold for the spectral method and the threshold obtained from Bayesian inference is considerable in sparse graphs, even without eigenvector localization. This gap closes in a dense limit.

Variation in Adult Plant Phenotypes and Partitioning among Seed and Stem-Borne Roots across Brachypodium distachyon Accessions to Exploit in Breeding Cereals for Well-Watered and Drought Environments.

Seedling roots enable plant establishment. Their small phenotypes are measured routinely. Adult root systems are relevant to yield and efficiency, but phenotyping is challenging. Root length exceeds the volume of most pots. Field studies measure partial adult root systems through coring or use seedling roots as adult surrogates. Here, we phenotyped 79 diverse lines of the small grass model Brachypodium distachyon to adults in 50-cm-long tubes of soil with irrigation; a subset of 16 lines was droughted. Variation was large (total biomass, ×8; total root length [TRL], ×10; and root mass ratio, ×6), repeatable, and attributable to genetic factors (heritabilities ranged from approximately 50% for root growth to 82% for partitioning phenotypes). Lines were dissected into seed-borne tissues (stem and primary seminal axile roots) and stem-borne tissues (tillers and coleoptile and leaf node axile roots) plus branch roots. All lines developed one seminal root that varied, with branch roots, from 31% to 90% of TRL in the well-watered condition. With drought, 100% of TRL was seminal, regardless of line because nodal roots were almost always inhibited in drying topsoil. Irrigation stimulated nodal roots depending on genotype. Shoot size and tillers correlated positively with roots with irrigation, but partitioning depended on genotype and was plastic with drought. Adult root systems of B. distachyon have genetic variation to exploit to increase cereal yields through genes associated with partitioning among roots and their responsiveness to irrigation. Whole-plant phenotypes could enhance gain for droughted environments because root and shoot traits are coselected.

Transgenic approaches to altering carbon and nitrogen partitioning in whole plants: assessing the potential to improve crop yields and nutritional quality.

The principal components of plant productivity and nutritional value, from the standpoint of modern agriculture, are the acquisition and partitioning of organic carbon (C) and nitrogen (N) compounds among the various organs of the plant. The flow of essential organic nutrients among the plant organ systems is mediated by its complex vascular system, and is driven by a series of transport steps including export from sites of primary assimilation, transport into and out of the phloem and xylem, and transport into the various import-dependent organs. Manipulating C and N partitioning to enhance yield of harvested organs is evident in the earliest crop domestication events and continues to be a goal for modern plant biology. Research on the biochemistry, molecular and cellular biology, and physiology of C and N partitioning has now matured to an extent that strategic manipulation of these transport systems through biotechnology are being attempted to improve movement from source to sink tissues in general, but also to target partitioning to specific organs. These nascent efforts are demonstrating the potential of applied biomass targeting but are also identifying interactions between essential nutrients that require further basic research. In this review, we summarize the key transport steps involved in C and N partitioning, and discuss various transgenic approaches for directly manipulating key C and N transporters involved. In addition, we propose several experiments that could enhance biomass accumulation in targeted organs while simultaneously testing current partitioning models.