Boron Deficiency Precisely Identified on Growth Stage V4 of Maize Crop Using Texture Image Analysis

ABSTRACT The aim of this study was to evaluate the diagnostic imaging approach to identify the deficiency of boron in leaves of maize. The experiment was conducted in a greenhouse under a hydroponic system. The treatments were four levels of boron (B) in solution nutrition (zero, 0.12, 0.24 and 0.60 mg L−1), combined at V4, V7, and R1 growing stages. Plant parts sampled included index leaf and new leaf to chemical analysis and texture image analysis. Our proposal was to apply these texture analysis and pattern classification schemes to identify the levels of B. Texture methods achieved 98% of accuracy in differentiating between leaves properly fertilized with B, from leaves with deficiency, in V4. In all tests, with index leaf success rate was higher than 80%, and around 90% for the new leaf. The image analysis by texture techniques applied on maize leaves are able to identify boron deficiencies in younger plants.

[1]  T. Fujiwara,et al.  Boron transport in plants: co-ordinated regulation of transporters. , 2009, Annals of botany.

[2]  Matti Pietikäinen,et al.  A comparative study of texture measures with classification based on featured distributions , 1996, Pattern Recognit..

[3]  B. Dell,et al.  Boron deficiency in maize , 2011, Plant and Soil.

[4]  P. Fontes,et al.  Teores de clorofila determinados por medidor portátil e sua relação com formas de nitrogênio em folhas de tomateiro cultivados em dois tipos de solo , 1999 .

[5]  Wilhelm Burger,et al.  Digital Image Processing - An Algorithmic Introduction using Java , 2008, Texts in Computer Science.

[6]  J. J. Camacho-Cristóbal,et al.  Boron deficiency and transcript level changes. , 2011, Plant science : an international journal of experimental plant biology.

[7]  H. Marschner Mineral Nutrition of Higher Plants , 1988 .

[8]  John Daugman,et al.  Gabor wavelets for statistical pattern recognition , 1998 .

[9]  Variation in responses to boron in rice , 2013, Plant and Soil.

[10]  Odemir Martinez Bruno,et al.  Automatic Leaf Structure biometry: Computer Vision Techniques and their Applications in Plant Taxonomy , 2009, Int. J. Pattern Recognit. Artif. Intell..

[11]  William R. Raun,et al.  Estimating vegetation coverage in wheat using digital images , 1999 .

[12]  B. Dell,et al.  Physiological response of plants to low boron , 1997, Plant and Soil.

[13]  Rio de Janeiro. Introdução à Fisiologia Vegetal , 2014 .

[14]  André Ricardo Backes,et al.  A complex network-based approach for boundary shape analysis , 2009, Pattern Recognit..

[15]  Matti Pietikäinen,et al.  Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  T. Fujiwara,et al.  Physiological roles and transport mechanisms of boron: perspectives from plants , 2008, Pflügers Archiv - European Journal of Physiology.

[17]  L. Rambo,et al.  Parâmetros de planta para aprimorar o manejo da adubação nitrogenada de cobertura em milho , 2004 .

[18]  Odemir Martinez Bruno,et al.  Plant leaf identification using Gabor wavelets , 2009, Int. J. Imaging Syst. Technol..

[19]  M. Bauer,et al.  Comparison of petiole nitrate concentrations, SPAD chlorophyll readings, and QuickBird satellite imagery in detecting nitrogen status of potato canopies , 2007 .

[20]  O. Bruno,et al.  A Diagnostic Tool for Magnesium Nutrition in Maize Based on Image Analysis of Different Leaf Sections , 2014 .

[21]  L. B. Vieira,et al.  Determinação do "status" nutricional de nitrogênio no feijoeiro utilizando imagens digitais coloridas , 2007 .

[22]  D. R. Hoagland,et al.  The Water-Culture Method for Growing Plants Without Soil , 2018 .

[23]  F. Aref EVALUATION OF APPLICATION METHODS AND RATES OF ZINC AND BORON ON NITROGEN, PHOSPHORUS AND POTASSIUM CONTENTS OF MAIZE LEAF , 2012 .

[24]  H. L. D. Santos,et al.  Nutrição e adubação do milho. , 1980 .

[25]  D. D. Neto,et al.  Produção de milho , 2000 .

[26]  Odemir Martinez Bruno,et al.  Gabor wavelets combined with volumetric fractal dimension applied to texture analysis , 2014, Pattern Recognit. Lett..

[27]  O. Bruno,et al.  Use of artificial vision techniques for diagnostic of nitrogen nutritional status in maize plants , 2014 .

[28]  E. Malavolta,et al.  Evaluation of extraction procedures on determination of critical soil and foliar levels of boron and zinc in coffee plants , 1998 .

[29]  P. Brown,et al.  Boron in Plant Biology , 2002 .

[30]  R. Bell,et al.  Micronutrients for Sustainable Food, Feed, Fibre and Bioenergy Production , 2008 .

[31]  C. Marschner Mineral Nutrition of Higher Plants, 2nd edition, H. Marschner. Academic Press, London (1995), 889, (ISBN 0-12-473543-6). Price: 29.95 Pound Sterling , 1996 .

[32]  Odemir Martinez Bruno,et al.  Fractal analysis of leaf-texture properties as a tool for taxonomic and identification purposes: a case study with species from Neotropical Melastomataceae (Miconieae tribe) , 2010, Plant Systematics and Evolution.

[33]  Lance M. Kaplan Extended fractal analysis for texture classification and segmentation , 1999, IEEE Trans. Image Process..