Abstract
We investigated a method to quantify field-state wheat RSA in a phenotyping way, depicting the 3D topology of wheat RSA in 14d periods. The phenotyping procedure, proposed for understanding the spatio-temporal variations of root-soil interaction and the RSA dynamics in the field, is realized with a set of indices of mm scale precision, illustrating the gradients of both wheat root angle and elongation rate along soil depth, as well as the foraging potential along the side directions. The 70d was identified as the shifting point distinguishing the linear root length elongation from power-law development. Root vertical angle in the 40 mm surface soil layer was the largest, but steadily decreased along the soil depth. After 98d, larger root vertical angle appeared in the deep soil layers. PAC revealed a stable root foraging potential in the 0–70d period, which increased rapidly afterwards (70–112d). Root foraging potential, explained by MaxW/MaxD ratio, revealed an enhanced gravitropism in 14d period. No-till post-paddy wheat RLD decreased exponentially in both depth and circular directions, with 90% roots concentrated within the top 20 cm soil layer. RER along soil depth was either positive or negative, depending on specific soil layers and the sampling time.
Highlights
Crop root systems still remain as an underexplored target for improvements of crop yields and productivity[1]
A better understanding of root phenomena is critical for crop cultivars[23], the key of which should be based on detailed description of field-state crop root system architecture (RSA)
Distributed monolith sampling is an option for illustrating crop RSAs with root length and root mass spatial heterogeneities in all three spatial dimensions in
Summary
Crop root systems still remain as an underexplored target for improvements of crop yields and productivity[1]. A rich number of sampling and phenotyping methods for crop roots in the field have been proposed, including soil profiles[8], monoliths[9], nail plates, probes[10], rhizotron[8], trenching[11], shovelomics[12] and digitalization and visualization of roots in field[13,14] These methods supply a number of parameters, e.g. root dry matter, root length and diameter, root surface area, root dry weight, root diameter classes and root structure[15,16]. Field crop RSA phenotyping is hampered, by the biological, chemical, and physical complexities of the soil medium[17] and by a shortage of accurate and comprehensive information about root systems and how they work throughout the lifespan of plants in the field[18] These are the most critical aspects for modeling roots and for identifying root architectures suitable to agricultural or natural systems[19]. Its simplicity is achieved by sacrificing the detail of RSAs
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