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Soil seedbed engineering and its impact on germination and establishment in sugar beet (Beta vulgaris L.) as affected by seed–soil contact

Published online by Cambridge University Press:  21 May 2018

Sebastian Blunk*
Affiliation:
Division of Agriculture and Environmental Science – University of Nottingham, Nottingham, UK
Martine I. de Heer
Affiliation:
Syngenta Ltd, Bracknell, UK
Craig J. Sturrock
Affiliation:
Division of Agriculture and Environmental Science – University of Nottingham, Nottingham, UK
Sacha J. Mooney
Affiliation:
Division of Agriculture and Environmental Science – University of Nottingham, Nottingham, UK
*
Author for correspondence: Sebastian Blunk, Email: [email protected]

Abstract

Seed–soil contact plays an essential role in the process of germination as seeds absorb water through direct contact with the moist soil aggregates that surround them. Factors influencing seed–soil contact can be considered as those pertaining to soil physical properties (e.g. texture, bulk density, porosity, etc.) and those related to environmental conditions (e.g. temperature, rainfall, frost). Seed–soil contact is furthermore influenced by the specific field management processes that farmers apply, which have developed significantly over the last 30 years. However, the precise effect of cultivation on the actual contact area of the seed with the surrounding soil is based on a series of assumptions and is still largely unknown. This review considers the influence of soil management and its direct impact on seed–soil contact and establishment. We review the state of the art in methodology for measuring seed–soil contact and assess the potential for soil amendments such as plant residues and waste materials to improve seed–soil contact. Engineering the ‘optimal’ seed–soil contact remains a challenge due to the localized variation between the interaction with field management techniques and soil texture, climatic conditions and crop type. The latest imaging approaches show great promise to assess the impact of management on germination. Combining the techniques with the latest network models offers great potential to improve our ability to accurately predict germination, emergence and establishment.

Type
Review Paper
Copyright
Copyright © Cambridge University Press 2018 

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