Using big data to predict the likelihood of low falling numbers in wheat-Reference-Cited by-同舟云学术

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Using big data to predict the likelihood of low falling numbers in wheat

Published:2019-03-07 Issue:3 Volume:96 Page:411-420
ISSN:0009-0352
Container-title:Cereal Chemistry
language:en
Short-container-title:Cereal Chem

Author:

Williams Richard M.¹²^ORCID,Diepeveen Dean A.²³,Evans Fiona H.²⁴

Affiliation:

1. groIQ Mount Hawthorn Western Austrlia Australia

2. School of Veterinary and Life Sciences Murdoch University Murdoch Western Austrlia Australia

3. Department of Primary Industries and Regional Development South Perth Western Austrlia Australia

4. Centre for Digital Agriculture Curtin University Bentley Western Austrlia Australia

Funder

Department of Primary Industries and Regional Development, Agribusiness Innovation Fund

Publisher

Wiley

Subject

Organic Chemistry,Food Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cche.10140

Reference33 articles.

1. Research on Big Data – A systematic mapping study

2. The effect of rainfall and temperature on the preharvest sprouting tolerance of winter wheat in the dryland production areas of the free state province;Barnard A.;Field Crops Research,2009

3. Drought and high temperature increases preharvest sprouting tolerance in a genotype without grain dormancy

4. Influence of high temperature and terminal moisture stress on dormancy in wheat (Triticum aestivum L.)

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. The Impact of a Six-Hour Light–Dark Cycle on Wheat Ear Emergence, Grain Yield, and Flour Quality in Future Plant-Growing Systems;Foods;2024-02-28

2. Is it necessary to manage falling number in the field?;Agrosystems, Geosciences & Environment;2020-01

3. Pressurization of some starches compared to heating: Calorimetric, thermo-optical and X-ray examination;Food Research International;2008-08

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