A procedure for determining average root length density in row crops by single-site augering

Gajri, P.R.; Arora, Vijay K.; Kumar, K. Ravi

doi:10.1007/bf00150344

Cited by 33 publications

(32 citation statements)

References 11 publications

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“…The different distributions for the RLD, for which relatively high values were observed in the inter-row zone, may be explained by relatively smaller diameters of the roots in the outer spheres and by overlapping of roots from neighbouring plants (e.g., Kovar et al 1992;Gajri et al 1994). Compared with RLD, the RFM seems to vary more strongly parallel to the plant rows, especially in the 0-10 cm layer.…”

Section: Root Mass and Length Distributionmentioning

confidence: 79%

“…Since effects of a greater soil structural heterogeneity close to the soil surface (Bengough et al 2000) can largely be neglected here, merely the gradually increasing overlapping of the individual root systems with depth can be used to explain the decreasing spatial variability of RLD with depth as observed in some studies (e.g., Yu et al 2007), whereas others do not report such trend (e.g., Gajri et al 1994). The relatively high CV values of RLD within horizontal layers indicate that assuming simplified 1D distribution would be fraught with errors.…”

Section: Spatial Variability Of Rldmentioning

confidence: 96%

“…Methods for characterizing the spatial distribution of root systems in soil (Böhm 1979) include root mapping (Pagès and Pellerin 1996), minirhizotron observations (Liedgens and Richner 2001), auger or core sampling (Chassot et al 2001;Sharratt and McWilliams 2005), and soil monolith excavation (Buman et al 1994;Gajri et al 1994;Li et al 2006). Most of the experimental studies considered 1D root distribution in vertical direction (i.e., soil depth) and 1D/2D in horizontal direction (i.e., perpendicular to plant rows), and soil water flow and crop growth models frequently assume simplified 1D vertical (e.g., Jones and Kiniry 1986;Jansson and Karlberg 2004) or 2D vertical RLD distributions (e.g., Heinen et al 2003;Simunek et al 1999).…”

Section: Introductionmentioning

confidence: 99%

“…Previous monolith-type field samplings were restricted mostly to 2D vertical soil slices normal to the direction of plant rows (Buman et al 1994;Gajri et al 1994;Li et al 2006). This restriction was mainly based on the prevailing simplifying assumption that variability parallel to the plant rows is negligible.…”

Section: Introductionmentioning

confidence: 99%

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Spatial distribution of maize roots by complete 3D soil monolith sampling

2008

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The spatial distribution of root length density (RLD) is important for water and nutrient uptake by plants and biomass allocation in the soil. Experimental root assessment is, however, mostly based on methods that encompass only small fractions of the soil volume. The aim of this study was to characterize the three dimensional (3D) spatial distribution of RLD in the soil of a maize crop for plots of 37.5 and 75 cm row spacing. At each plot, a 3D soil monolith of 70×40×30 (=84,000) cm 3 was completely sampled in form of 84 cubic samples of 10 cm edge length. Roots were washed from the soil and RLD was determined using the line intersect method. In 2004, mean RLD values were 0.41 cm cm −3 for narrow and 0.34 cm cm −3 for wide row spacing at row closure (55 days after planting; DAP) and 0.74 cm cm −3 (1.37 cm cm −3 in 2003) for narrow and 0.77 cm cm −3 (0.96 cm cm −3 in 2003) for wide row spacing at tasseling (104 DAP). The CV values for RLD of 48% to 72% in 2004 were first higher for wide than for narrow row spacing but at the later growth stage (tasseling) lower for wide than for narrow. For individual vertical soil slices, CV values for RLD were about 40-60%, irrespective of the orientation of the slice. The results suggest that RLD was related mainly to the spatial location and the plant row structure, and not governed unambiguously by SBD or SWC. The spatially distributed maize root data suggest that variability of RLD parallel to plant rows is not negligible. Any simplified use of 1D or 2D vertical samples at separate locations may lead to erroneous estimations of RLD profiles.

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Section: Root Mass and Length Distributionmentioning

confidence: 79%

Section: Spatial Variability Of Rldmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Spatial distribution of maize roots by complete 3D soil monolith sampling

2008

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“…The sampling design must cover the spatial variability of the RB to accurately extrapolate to the basis of RB per hectare. It was shown that the maize RB was highest close to the base of the plants, than decreased with distance from the plant and increased again at the mid-row position where adjacent plants contribute to the RB (Gajri et al 1994). RB sampling at different positions in row, in inter-row and on the diagonal between row and inter-row allows to cover the spatial variability.…”

Section: Root Biomass Determination In the Fieldmentioning

confidence: 99%

Estimation of rhizodeposition at field scale: upscaling of a 14C labeling study

et al. 2012

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Background and aims Rhizodeposition of plants is the most uncertain component of the carbon (C) cycle. By existing approaches the amount of rhizodeposition can only roughly be estimated since its persistence in soil is very short compared to other organic C pools. We suggest an approach to quantify rhizodeposition at the field scale by assuming a constant ratio between rhizodeposited-C to root-C. Methods Maize plants were pulse-labeled with 14 CO 2 under controlled conditions and the soil 14 CO 2 efflux was separated into root and rhizomicrobial respiration. The latter and the 14 C activity remaining in the soil corresponded to total rhizodeposition. By relating rhizodeposited-14 C to root-14 C a rhizodeposition-toroot ratio of 0.56 was calculated. This ratio was applied to the root biomass C measured in the field to estimate rhizodeposition under field conditions. Results Maize allocated 298 kg C ha −1 as root-C and 166 kg C ha −1 as rhizodeposited-C belowground, 50 % of which were recovered in the upper 10 cm. The fate of rhizodeposits was estimated based on the 14 C data, which showed that 62 % of total rhizodeposition was mineralized within 16 days, 7 % and 0.3 % was incorporated into microbial biomass and DOC, respectively, and 31 % was recovered in the soil.Conclusions We conclude that the present approach allows for an improved estimation of total rhizodeposition, since it accounts not only for the fraction of rhizodeposits remaining in soil, but also for that decomposed by microorganisms and released from the soil as CO 2 .

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Root recovery and elemental composition in a perennial grass as affected by soaking conditions

et al. 2021

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Roots of perennial grasses, with their fibrous architecture, are difficult to separate from the surrounding soil. We assessed the effect of five soaking solutions (sodium bicarbonate, sodium chloride, disodium ethylenediamine tetraacetic acid [disodium EDTA], distilled water, and sodium hexametaphosphate) and three soaking durations (15 min, 2 h, and 16 h) on root recovery and root elemental composition, with and without a mathematical correction for residual soil adhering to roots. Roots were collected by soil coring in a timothy (Phleum pratense L.) sward on a loam soil. After soaking, roots were washed, digitized, and analyzed for elemental composition. Soaking duration did not affect root mass and length, but the 16-h duration resulted in the lowest ash concentration (136.7 vs. 146.4 g kg -1 dry matter [DM] on average across shorter durations), indicating a lower contamination by soil. The greatest root recovery was obtained with sodium bicarbonate (0.118 vs. 0.101 g DM core -1 on average across other solutions). Sodium hexametaphosphate led to the lowest root ash and element concentrations but left a P residue on the roots. Distilled water did not impair root cell integrity and led to a similar root recovery as sodium chloride, disodium EDTA, and sodium hexametaphosphate. A mathematical correction improved the estimates of (a) root mass for all soaking solutions and (b) root elemental composition for elements with higher concentrations in soils than in roots. Soaking solutions should be chosen as a function of the study objectives because of the trade-off between root recovery and contamination by adhering soil.

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A procedure for determining average root length density in row crops by single-site augering

Cited by 33 publications

References 11 publications

Spatial distribution of maize roots by complete 3D soil monolith sampling

Spatial distribution of maize roots by complete 3D soil monolith sampling

Estimation of rhizodeposition at field scale: upscaling of a 14C labeling study

Root recovery and elemental composition in a perennial grass as affected by soaking conditions

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