Depth Development of Roots with Time: An Empirical Description

Borg, Heinz; Grimes, D. W.

doi:10.13031/2013.30125

Cited by 215 publications

(83 citation statements)

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“…This result was similar to that reported by Borg and Grimes (1986). This general trend decreased gradually from P2 to P10.…”

Section: Discussionsupporting

confidence: 92%

Dynamics of Root Growth and Distribution in Maize from the Black Soil Region of NE China

Liu¹,

Song²,

Zhu³

et al. 2012

JAS

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Root growth is related to its water and mineral uptake. The structure and architecture of the root system is influenced by soil properties. Better understanding of root architecture and growth dynamics of maize grown on black soil may lead to more efficient use of applied nutrients and water by maize. Maize (Zea mays L.), cultivar Yedan 13, was grown in a black soil field in large root boxes in 2007. Plants were regularly sampled and the following data were recorded: number of emerged roots per phytomer, mean length and maximal length of axile root per phytomer, maximum rooting depth of axile root per phytomer, and angle of axile root per phytomer by excavation methods. The distribution dynamics of root dry weight at different black soil depths, and vertical and horizontal distribution in large root boxes were measured. There were more axile roots on the upper phytomers than on lower phytomers. The number of roots on phytomers P8, P9 and P10 were 15.71%，24.82%, and 25.86% of total number of per plant, respectively. Angles of the axile roots on lower phytomers were larger than those on upper phytomers. The angle of the axile root on P2 was the largest (81.51°), followed by P4 (69.33°), P3 (56.9°), and P5 (56.06°). The angles on phytomers from P6 to P10 were smaller, ranging from 30.13-40.72°. Mean length, maximal length, and maximum rooting depth of axile root on each phytomer all increased with day after seeding (DAS). Mean length, maximal length, and maximum rooting depth of axile roots on lower phytomers were larger www.ccsenet.org/jas Journal of Agricultural Science Vol. 4, No. 2; 2012 ISSN 1916-9752 E-ISSN 1916 22 than those on upper phytomers. Mean length, maximal length and maximum rooting depth of axile roots on P3 were the largest (2.37 m, 2.92 m and 2.12 m at 90 DAS, respectively). Root dry weight in each soil layer increased with DAS; there was a rapid increase from 50 to 90 DAS. About 80 % of root dry weight was in the soil above 40 cm. The general trend of percentage of dry weight in total dry weight per plant decreased as the distance from the plant increased. Over 78 % of root dry weight in total dry weight per plant was within 20 cm in the horizontal direction from the plant, and less than 6% was in the 40 cm to 60 cm zone in the horizontal direction from the plant.

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“…This result was similar to that reported by Borg and Grimes (1986). This general trend decreased gradually from P2 to P10.…”

Section: Discussionsupporting

confidence: 92%

Dynamics of Root Growth and Distribution in Maize from the Black Soil Region of NE China

Liu¹,

Song²,

Zhu³

et al. 2012

JAS

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“…Previous studies indicated that the vast majority of summer maize roots grow in the upper 40 cm of soil (Yi et al, 2009;Liu et al, 2009). Root biomass reaches its maximum at tasseling, pin silk, or milk stages (Yi et al, 2009), and the rooting depth development can be described as a sine function with time (Borg and Grimes, 1986).…”

Section: Relationship Between Root Distribution and Water Uptakementioning

confidence: 99%

Using stable isotopes to determine seasonal variations in water uptake of summer maize under different fertilization treatments

Song

2016

Science of The Total Environment

107

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“…Using Equation given by Borg and Grimes (1986) root growth during the growing season was calculated as follows:…”

Section: Measurement and Methodologiesmentioning

confidence: 99%

Evaluation and Improvement of Crop Production Functions for Simulation Winter Wheat Yields with Two Types of Yield Response Factors

Tafteh¹,

Babazadeh²,

Ebrahimipak³

et al. 2013

JAS

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Water is an important item of crop production and Irrigation water is limiting for crop production in arid and semi-arid areas. On the other hand, considering the population growth and increasing the water and food needs and also limited resources of water, the optimization of water consumption, especially in section of agriculture is important. For this purpose, in first step, the production function of expected products in any region should be obtained acceptably, because in this case, the models are totally dependent on the production function. Thus, finding the optimal production function has the lowest error in the estimation of risk-taking and decision-making power in the future will be important. So this study was conducted in Esmaeil Abad in Qazvin plain in Iran in the growing season of 2009-2012. Deficit Irrigations applied on different growth stages of winter wheat. The maximum evapotranspiration 641 mm and maximum attainable yield 5847 kg/ha was determined. After that the different production functions were studied and these methods have been tried to improve a new method with the least error. On the other hand yield response factor (K y ) per month was defined as either one of the standard values by FAO and the other using correction values by Najarchi et al. (2011). The result showed that the new model in this study is normalized with yield response factors of Najarchi et al. (2011) with 5% normal root mean square (NRMSE) has the lowest error. Therefore this technique for estimating water deficits of winter wheat in the Qazvin Plain was suggested.

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Depth Development of Roots with Time: An Empirical Description

Cited by 215 publications

References 0 publications

Dynamics of Root Growth and Distribution in Maize from the Black Soil Region of NE China

Dynamics of Root Growth and Distribution in Maize from the Black Soil Region of NE China

Using stable isotopes to determine seasonal variations in water uptake of summer maize under different fertilization treatments

Evaluation and Improvement of Crop Production Functions for Simulation Winter Wheat Yields with Two Types of Yield Response Factors

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