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Engineering Nitrogen Utilization in Crop Plants

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Cover of 'Engineering Nitrogen Utilization in Crop Plants'

Table of Contents

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    Book Overview
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    Chapter 1 Developing Crop Varieties with Improved Nutrient-Use Efficiency
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    Chapter 2 Improving Nitrogen Use Efficient in Crop Plants Using Biotechnology Approaches
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    Chapter 3 Transcription Factor-Based Genetic Engineering to Increase Nitrogen Use Efficiency
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    Chapter 4 Modeling Plant Metabolism: Advancements and Future Capabilities
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    Chapter 5 Molecular Targets for Improvement of Crop Nitrogen Use Efficiency: Current and Emerging Options
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    Chapter 6 From Arabidopsis to Crops: The Arabidopsis QQS Orphan Gene Modulates Nitrogen Allocation Across Species
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    Chapter 7 Tackling Nitrogen Use Efficiency in Cereal Crops Using High-Throughput Phenotyping
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    Chapter 8 Nitrogen Partitioning and Remobilization in Arabidopsis Under Sufficient and Depleted Conditions
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    Chapter 9 Field Testing for Improved Nitrogen Use Efficiency of Corn—From Whole-Plant Physiology to Agroecosystem Scales
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    Chapter 10 Legume Nitrogen Utilization Under Drought Stress
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    Chapter 11 Exploiting Genetic Variability of Root Morphology as a Lever to Improve Nitrogen Use Efficiency in Oilseed Rape
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    Chapter 12 Genetic Improvement of Nitrogen Use Efficiency in Oilseed Rape
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    Chapter 13 The Importance of Organic Nitrogen Transport Processes for Plant Productivity and Nitrogen Use Efficiency
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    Chapter 14 New Screening Strategies for Dinitrogen Fixation in Soybean
Attention for Chapter 6: From Arabidopsis to Crops: The Arabidopsis QQS Orphan Gene Modulates Nitrogen Allocation Across Species
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Chapter title
From Arabidopsis to Crops: The Arabidopsis QQS Orphan Gene Modulates Nitrogen Allocation Across Species
Chapter number 6
Book title
Engineering Nitrogen Utilization in Crop Plants
Published by
Springer, Cham, July 2018
DOI 10.1007/978-3-319-92958-3_6
Book ISBNs
978-3-31-992957-6, 978-3-31-992958-3
Authors

Seth O’Conner, Andrea Neudorf, Wenguang Zheng, Mingsheng Qi, Xuefeng Zhao, Chuanlong Du, Dan Nettleton, Ling Li

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 29%
Student > Ph. D. Student 1 14%
Unspecified 1 14%
Unknown 3 43%
Readers by discipline Count As %
Unspecified 1 14%
Mathematics 1 14%
Computer Science 1 14%
Agricultural and Biological Sciences 1 14%
Unknown 3 43%