Low-cost assessment of grain yield in durum wheat using RGB images

[1]  Rui Li,et al.  A method to calculate the number of wheat seedlings in the 1st to the 3rd leaf growth stages , 2018, Plant Methods.

[2]  J. Araus,et al.  Post-green revolution genetic advance in durum wheat: The case of Spain , 2018, Field Crops Research.

[3]  J. Araus,et al.  Breeding to adapt agriculture to climate change: affordable phenotyping solutions. , 2018, Current opinion in plant biology.

[4]  M. Zaman-Allah,et al.  Translating High-Throughput Phenotyping into Genetic Gain , 2018, Trends in plant science.

[5]  Adrian Gracia-Romero,et al.  Comparative Performance of Ground vs. Aerially Assessed RGB and Multispectral Indices for Early-Growth Evaluation of Maize Performance under Phosphorus Fertilization , 2017, Front. Plant Sci..

[6]  Omar Vergara-Díaz,et al.  Comparative UAV and Field Phenotyping to Assess Yield and Nitrogen Use Efficiency in Hybrid and Conventional Barley , 2017, Front. Plant Sci..

[7]  Pouria Sadeghi-Tehran,et al.  Automated Method to Determine Two Critical Growth Stages of Wheat: Heading and Flowering , 2017, Front. Plant Sci..

[8]  G. Jia,et al.  Climate change reduces extent of temperate drylands and intensifies drought in deep soils , 2017, Nature Communications.

[9]  P. Zarco-Tejada,et al.  A Novel Remote Sensing Approach for Prediction of Maize Yield Under Different Conditions of Nitrogen Fertilization , 2016, Front. Plant Sci..

[10]  Zhiguo Cao,et al.  In-field automatic observation of wheat heading stage using computer vision , 2016 .

[11]  Gustavo A. Slafer,et al.  Detecting interactive effects of N fertilization and heat stress on maize productivity by remote sensing techniques , 2016 .

[12]  Shawn C. Kefauver,et al.  RGB picture vegetation indexes for High-Throughput Phenotyping Platforms (HTPPs) , 2015, SPIE Remote Sensing.

[13]  Jordi Bort,et al.  Low-cost assessment of wheat resistance to yellow rust through conventional RGB images , 2015, Comput. Electron. Agric..

[14]  P. Zarco-Tejada,et al.  Unmanned aerial platform-based multi-spectral imaging for field phenotyping of maize , 2015, Plant Methods.

[15]  Katja Brinkmann,et al.  Monitoring of crop biomass using true colour aerial photographs taken from a remote controlled hexacopter , 2015 .

[16]  Zhenghong Yu,et al.  Vegetation segmentation robust to illumination variations based on clustering and morphology modelling , 2014 .

[17]  Craig S. T. Daughtry,et al.  Remote Sensing With Simulated Unmanned Aircraft Imagery for Precision Agriculture Applications , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[18]  J. Casadesús,et al.  Conventional digital cameras as a tool for assessing leaf area index and biomass for cereal breeding. , 2014, Journal of integrative plant biology.

[19]  John Penczek,et al.  Color Error in the Digital Camera Image Capture Process , 2013, Journal of Digital Imaging.

[20]  Zhiguo Cao,et al.  Crop segmentation from images by morphology modeling in the CIE L*a*b* color space , 2013 .

[21]  Y. Wang,et al.  Estimating nitrogen status of rice using the image segmentation of G-R thresholding method , 2013 .

[22]  Craig S. T. Daughtry,et al.  A visible band index for remote sensing leaf chlorophyll content at the canopy scale , 2013, Int. J. Appl. Earth Obs. Geoinformation.

[23]  Kevin W Eliceiri,et al.  NIH Image to ImageJ: 25 years of image analysis , 2012, Nature Methods.

[24]  D. Malacara.  Uniform Color Systems , 2011 .

[25]  D. Malacara.  Color Vision and Colorimetry: Theory and Applications, Second Edition , 2011 .

[26]  C. Daughtry,et al.  Remote Sensing Leaf Chlorophyll Content Using a Visible Band Index , 2011 .

[27]  Wfp,et al.  The State of Food Insecurity in the World , 2011 .

[28]  Xavier P. Burgos-Artizzu,et al.  utomatic segmentation of relevant textures in agricultural images , 2010 .

[29]  J. L. Araus,et al.  Using vegetation indices derived from conventional digital cameras as selection criteria for wheat breeding in water-limited environments , 2007 .

[30]  C. Daughtry,et al.  Evaluation of Digital Photography from Model Aircraft for Remote Sensing of Crop Biomass and Nitrogen Status , 2005, Precision Agriculture.

[31]  Greg J. Rebetzke,et al.  Genotypic variation in specific leaf area for genetic improvement of early vigour in wheat , 2004 .

[32]  R. Richards,et al.  Breeding Opportunities for Increasing the Efficiency of Water Use and Crop Yield in Temperate Cereals. , 2002, Crop science.

[33]  Greg J. Rebetzke,et al.  Genetic improvement of early vigour in wheat , 1999 .

[34]  Sabine Süsstrunk,et al.  Standard RGB Color Spaces , 1999, CIC.

[35]  N. Draper,et al.  Applied Regression Analysis: Draper/Applied Regression Analysis , 1998 .

[36]  R. E. Williamson,et al.  Seed and Seedling Characteristics Contributing to Variation in Early Vigor among Temperate Cereals , 1996 .

[37]  M. Nicolas,et al.  A survey of the effects of high temperature during grain filling on yield and quality of 75 wheat cultivars , 1995 .

[38]  George E. Meyer,et al.  Plant species identification, size, and enumeration using machine vision techniques on near-binary images , 1993, Other Conferences.

[39]  G. J. Burton,et al.  Color and spatial structure in natural scenes. , 1987, Applied optics.

[40]  A. Robertson.  The CIE 1976 Color-Difference Formulae , 1977 .

[41]  J. Zadoks.  A decimal code for the growth stages of cereals , 1974 .

[42]  D. M. Ellis,et al.  Applied Regression Analysis , 1968 .

[43]  Cedric A. B. Smith,et al.  Introduction to Quantitative Genetics , 1960 .

[44]  D. B. Judd,et al.  Color in Business Science and Industry , 1952 .