D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Plant Science and Agronomy D-index 34 Citations 4,999 90 World Ranking 1356 National Ranking 373

Overview

What is he best known for?

The fields of study he is best known for:

  • Agriculture
  • Agronomy
  • Ecology

His scientific interests lie mostly in Agronomy, Canopy, Crop, Vegetation and Precision agriculture. The various areas that Yuxin Miao examines in his Agronomy study include Nitrogen management and Normalized Difference Vegetation Index. His work on Red edge as part of general Canopy study is frequently linked to Sanjiang Plain and Attenuation, therefore connecting diverse disciplines of science.

His Crop study integrates concerns from other disciplines, such as Enhanced vegetation index and Fertilizer. As part of his studies on Vegetation, Yuxin Miao often connects relevant areas like Remote sensing. His research investigates the link between Growing season and topics such as Soil contamination that cross with problems in Crop yield.

His most cited work include:

  • Long-term experiments for sustainable nutrient management in China. A review (265 citations)
  • Pursuing sustainable productivity with millions of smallholder farmers. (244 citations)
  • Closing yield gaps in China by empowering smallholder farmers (177 citations)

What are the main themes of his work throughout his whole career to date?

Yuxin Miao mainly focuses on Agronomy, Crop, Canopy, Vegetation and Remote sensing. His studies deal with areas such as Precision agriculture, Nitrogen management and Normalized Difference Vegetation Index as well as Agronomy. His study looks at the relationship between Crop and topics such as Cultivar, which overlap with Temperate climate and Nitrogen dilution.

Yuxin Miao interconnects Stem elongation, Forestry, Cropping system and Crop factor in the investigation of issues within Canopy. His work on Red edge as part of general Vegetation research is frequently linked to Sanjiang Plain, thereby connecting diverse disciplines of science. His work deals with themes such as Biomass, Scale and Stage, which intersect with Remote sensing.

He most often published in these fields:

  • Agronomy (58.82%)
  • Crop (29.41%)
  • Canopy (29.41%)

What were the highlights of his more recent work (between 2018-2021)?

  • Remote sensing (9.24%)
  • Remote sensing (26.05%)
  • Crop (29.41%)

In recent papers he was focusing on the following fields of study:

His primary areas of investigation include Remote sensing, Remote sensing, Crop, Soil type and Agriculture. In Remote sensing, he works on issues like Vegetation, which are connected to Biomass, Dry weight, Multispectral image and Precision agriculture. Crop is a subfield of Agronomy that he studies.

His work in Agronomy covers topics such as Soil water which are related to areas like Normalized Difference Vegetation Index. His studies in Agriculture integrate themes in fields like Multispectral pattern recognition, Ground truth and Scale. His work focuses on many connections between Nitrogen management and other disciplines, such as High yielding, that overlap with his field of interest in Canopy.

Between 2018 and 2021, his most popular works were:

  • Improving Unmanned Aerial Vehicle Remote Sensing-Based Rice Nitrogen Nutrition Index Prediction with Machine Learning (17 citations)
  • Developing Active Canopy Sensor-Based Precision Nitrogen Management Strategies for Maize in Northeast China (6 citations)
  • In-Season Diagnosis of Winter Wheat Nitrogen Status in Smallholder Farmer Fields Across a Village Using Unmanned Aerial Vehicle-Based Remote Sensing (5 citations)

In his most recent research, the most cited papers focused on:

  • Agriculture
  • Ecology
  • Agronomy

Yuxin Miao mainly focuses on Remote sensing, Remote sensing, Canopy, Crop and Soil water. His Remote sensing research is multidisciplinary, incorporating perspectives in Vegetation, Ground truth, Multispectral pattern recognition and Food security. His Remote sensing research includes themes of Agriculture and Precision agriculture.

Yuxin Miao combines subjects such as Panicle, Chlorophyll, Paddy field and Animal science with his study of Canopy. His study in Crop is interdisciplinary in nature, drawing from both Crop yield and Spatial variability. Yuxin Miao has researched Soil water in several fields, including Agronomy, Sowing and Normalized Difference Vegetation Index.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Pursuing sustainable productivity with millions of smallholder farmers.

Zhenling Cui;Hongyan Zhang;Xinping Chen;Chaochun Zhang.
Nature (2018)

324 Citations

Long-term experiments for sustainable nutrient management in China. A review

Yuxin Miao;Bobby A. Stewart;Fusuo Zhang.
Agronomy for Sustainable Development (2011)

324 Citations

On-farm evaluation of an in-season nitrogen management strategy based on soil Nmin test

Zhenling Cui;Fusuo Zhang;Xinping Chen;Yuxin Miao.
Field Crops Research (2008)

251 Citations

Closing yield gaps in China by empowering smallholder farmers

Weifeng Zhang;Guoxin Cao;Xiaolin Li;Hongyan Zhang.
Nature (2016)

242 Citations

On‐Farm Evaluation of the Improved Soil Nmin–based Nitrogen Management for Summer Maize in North China Plain

Zhenling Cui;Xinping Chen;Yuxin Miao;Fusuo Zhang.
Agronomy Journal (2008)

199 Citations

Improving estimation of summer maize nitrogen status with red edge-based spectral vegetation indices

Fei Li;Yuxin Miao;Guohui Feng;Fei Yuan.
Field Crops Research (2014)

173 Citations

Multitemporal crop surface models: accurate plant height measurement and biomass estimation with terrestrial laser scanning in paddy rice

Nora Tilly;Dirk Hoffmeister;Qiang Cao;Shanyu Huang.
Journal of Applied Remote Sensing (2014)

160 Citations

Hyperspectral canopy sensing of paddy rice aboveground biomass at different growth stages

Martin L. Gnyp;Martin L. Gnyp;Yuxin Miao;Fei Yuan;Susan L. Ustin.
Field Crops Research (2014)

159 Citations

Evaluating hyperspectral vegetation indices for estimating nitrogen concentration of winter wheat at different growth stages

Fei Li;Fei Li;Yuxin Miao;Simon D. Hennig;Martin L. Gnyp;Martin L. Gnyp.
Precision Agriculture (2010)

159 Citations

Estimating N status of winter wheat using a handheld spectrometer in the North China Plain

Fei Li;Fei Li;Martin L. Gnyp;Liangliang Jia;Yuxin Miao.
Field Crops Research (2008)

129 Citations

Best Scientists Citing Yuxin Miao

Fusuo Zhang

Fusuo Zhang

China Agricultural University

Publications: 85

Xinping Chen

Xinping Chen

Southwest University

Publications: 75

Zhenling Cui

Zhenling Cui

China Agricultural University

Publications: 70

Lin Ma

Lin Ma

Chinese Academy of Sciences

Publications: 23

Urs Schmidhalter

Urs Schmidhalter

Technical University of Munich

Publications: 20

Bruno Basso

Bruno Basso

Michigan State University

Publications: 16

Xiaotang Ju

Xiaotang Ju

China Agricultural University

Publications: 15

Xuejun Liu

Xuejun Liu

China Agricultural University

Publications: 14

Jianbo Shen

Jianbo Shen

China Agricultural University

Publications: 14

Chunqin Zou

Chunqin Zou

China Agricultural University

Publications: 13

Peter Christie

Peter Christie

Chinese Academy of Sciences

Publications: 13

Oene Oenema

Oene Oenema

Wageningen University & Research

Publications: 13

Rongfeng Jiang

Rongfeng Jiang

China Agricultural University

Publications: 12

Baojing Gu

Baojing Gu

Zhejiang University

Publications: 12

Xiaolin Li

Xiaolin Li

China Agricultural University

Publications: 10

Guohua Mi

Guohua Mi

China Agricultural University

Publications: 10

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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