Accumulation of Biomass and Mineral Elements with Calendar Time by Corn: Application of the Expanded Growth Model

Overman, A. R.; Scholtz, R. V.

doi:10.1371/journal.pone.0028515

Cited by 3 publications

(2 citation statements)

References 7 publications

(14 reference statements)

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“…Plants need leaves and roots to capture light, water, and nutrients (Evans, 2013). Similar results showed that the biomass of maize was influenced by the absorption of water, nutrients, carbon dioxide, and sunlight (Overman et al, 2011). Interactions between materials and biochar dosage in plant biomass.…”

Section: Leaf Areamentioning

confidence: 87%

Improvement of N, P, and K availability of post-brick mining soil to increase maize yield by applying different types of biochar

Widowati,

Wilujeng,

Nurhidayati

et al. 2024

J. Degrade. Min. Land Manage.

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The low fertility of post-brick mining soil may be improved by applying biochar to the soil because biochar is an excellent soil amendment, although its quality varies depending on the raw materials used. Therefore, soil fertility, nutrient availability, and crop yields are affected by the type and amount of biochar added to soils. This study examined the effect of types and dosages of biochar on nitrogen, phosphorus, and potassium availability of post-brick mining soil to increase maize yield. The treatment combinations of biochar dosages (0 t ha-1, 15 t ha-1, 30 t ha-1, and 45 t ha-1) and biochar types (coconut shell, wood, and rice husk biochars) were arranged in randomized block design with three replications. Each treatment plot measuring 4 m x 4.5 m was planted with maize seeds with a planting space of 80 cm x 25 cm. Urea (135 kg N ha-1), SP36 (36 kg P2O5 ha-1), and KCl (110 kg K2O ha-1) were applied as basal fertilizers. The results showed that at eight weeks after biochar application, the amount and type of biochar positively affected maize yield. The application of rice-husk biochar at 30 t ha-1 resulted in the highest maize yield. The application of each type of biochar at 45 t ha-1 yielded the highest increase in the availability of nitrogen, phosphorus, and potassium in the soil.

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Section: Leaf Areamentioning

confidence: 87%

Improvement of N, P, and K availability of post-brick mining soil to increase maize yield by applying different types of biochar

Widowati,

Wilujeng,

Nurhidayati

et al. 2024

J. Degrade. Min. Land Manage.

View full text Add to dashboard Cite

show abstract

“…One of the studies reported data on absorption of solar energy within the plant canopy, which provided a rational basis for the simple exponential model. The growth model has also been used to describe high quality data from a field study at Florence, SC, USA [4]. The planting time of April 2 maximized capture of solar energy for biomass production.…”

Section: Introductionmentioning

confidence: 99%

Accumulation of Biomass and Mineral Elements with Calendar Time by Cotton: Application of the Expanded Growth Model

Overman

Scholtz

2013

PLoS ONE

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Accumulation of plant biomass (Mg ha−1) with calendar time (wk) occurs as a result of photosynthesis for green land-based plants. A corresponding accumulation of mineral elements (kg ha−1) such as nitrogen, phosphorus, and potassium occurs from the soil through plant roots. Field data from literature for the warm-season annual cotton (Gossypium hirsutum L.) are used in this analysis. The expanded growth model is used to describe accumulation of biomass and mineral elements with calendar time. The growth model predicts a simple linear relationship between biomass yield and the growth quantifier, which is confirmed with the data. The growth quantifier incorporates the unit processes of distribution of solar energy which drives biomass accumulation by photosynthesis, partitioning of biomass between light-gathering and structural components of the plants, and an aging function. A hyperbolic relationship between plant nutrient uptake and biomass yield is assumed, and is confirmed for the mineral elements nitrogen, phosphorus, and potassium. It is concluded that the rate limiting process in the system is biomass accumulation by photosynthesis and that nutrient accumulation occurs in virtual equilibrium with biomass accumulation. The expanded growth model describes field data from California and Alabama rather well. Furthermore, all model parameters were common for the two sites with the exception of the yield factor A which accounts for differences in soil types, environmental conditions, fertilizer levels, and plant population.

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Distinguishing the Biomass Allocation Variance Resulting from Ontogenetic Drift or Acclimation to Soil Texture

et al. 2012

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In resource-poor environments, adjustment in plant biomass allocation implies a complex interplay between environmental signals and plant development rather than a delay in plant development alone. To understand how environmental factors influence biomass allocation or the developing phenotype, it is necessary to distinguish the biomass allocations resulting from environmental gradients or ontogenetic drift. Here, we compared the development trajectories of cotton plants (Gossypium herbaceum L.), which were grown in two contrasting soil textures during a 60-d period. Those results distinguished the biomass allocation pattern resulting from ontogenetic drift and the response to soil texture. The soil texture significantly changed the biomass allocation to leaves and roots, but not to stems. Soil texture also significantly changed the development trajectories of leaf and root traits, but did not change the scaling relationship between basal stem diameter and plant height. Results of nested ANOVAs of consecutive plant-size categories in both soil textures showed that soil gradients explained an average of 63.64–70.49% of the variation of biomass allocation to leaves and roots. Ontogenetic drift explained 77.47% of the variation in biomass allocation to stems. The results suggested that the environmental factors governed the biomass allocation to roots and leaves, and ontogenetic drift governed the biomass allocation to stems. The results demonstrated that biomass allocation to metabolically active organs (e.g., roots and leaves) was mainly governed by environmental factors, and that biomass allocation to metabolically non-active organs (e.g., stems) was mainly governed by ontogenetic drift. We concluded that differentiating the causes of development trajectories of plant traits was important to the understanding of plant response to environmental gradients.

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Accumulation of Biomass and Mineral Elements with Calendar Time by Corn: Application of the Expanded Growth Model

Cited by 3 publications

References 7 publications

Improvement of N, P, and K availability of post-brick mining soil to increase maize yield by applying different types of biochar

Improvement of N, P, and K availability of post-brick mining soil to increase maize yield by applying different types of biochar

Accumulation of Biomass and Mineral Elements with Calendar Time by Cotton: Application of the Expanded Growth Model

Distinguishing the Biomass Allocation Variance Resulting from Ontogenetic Drift or Acclimation to Soil Texture

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