Prediction of insect-herbivory-damage and insect-type attack in maize plants using hyperspectral data

[1]  Nilton Nobuhiro Imai,et al.  Improvement of leaf nitrogen content inference in Valencia-orange trees applying spectral analysis algorithms in UAV mounted-sensor images , 2019, Int. J. Appl. Earth Obs. Geoinformation.

[2]  A. Tarquis,et al.  Self-organizing map of soil properties in the context of hydrological modeling , 2020 .

[3]  U. Schurr,et al.  Local and systemic effects of two herbivores with different feeding mechanisms on primary metabolism of cotton leaves. , 2009, Plant, cell & environment.

[4]  Eija Honkavaara,et al.  A Novel Deep Learning Method to Identify Single Tree Species in UAV-Based Hyperspectral Images , 2020, Remote. Sens..

[5]  S. Nautiyal,et al.  Vegetable Crop Biomass Estimation Using Hyperspectral and RGB 3D UAV Data , 2020, Agronomy.

[6]  Katja Berger,et al.  Retrieval of aboveground crop nitrogen content with a hybrid machine learning method , 2020, Int. J. Appl. Earth Obs. Geoinformation.

[7]  Yong He,et al.  Recognising weeds in a maize crop using a random forest machine-learning algorithm and near-infrared snapshot mosaic hyperspectral imagery , 2018, Biosystems Engineering.

[8]  L. Jorge,et al.  A Review on Deep Learning in UAV Remote Sensing , 2021, Int. J. Appl. Earth Obs. Geoinformation.

[9]  Noel D.G. White,et al.  Detection of insect-damaged wheat kernels using near-infrared hyperspectral imaging , 2009 .

[10]  Jonathan Li,et al.  A Machine Learning Framework to Predict Nutrient Content in Valencia-Orange Leaf Hyperspectral Measurements , 2020, Remote. Sens..

[11]  Hongyu Liu,et al.  Land use pattern, irrigation, and fertilization effects of rice-wheat rotation on water quality of ponds by using self-organizing map in agricultural watersheds , 2019, Agriculture, Ecosystems & Environment.

[12]  Yiannis Ampatzidis,et al.  UAV-Based Remote Sensing Technique to Detect Citrus Canker Disease Utilizing Hyperspectral Imaging and Machine Learning , 2019, Remote. Sens..

[13]  Nan-Nan Wang,et al.  Hyperspectral discrimination of foliar biotic damages in rice using principal component analysis and probabilistic neural network , 2018, Precision Agriculture.

[14]  C. M. Oliveira,et al.  Crop losses and the economic impact of insect pests on Brazilian agriculture , 2014 .

[15]  G. Asner Biophysical and Biochemical Sources of Variability in Canopy Reflectance , 1998 .

[16]  Hemerson Pistori,et al.  A random forest ranking approach to predict yield in maize with uav-based vegetation spectral indices , 2020, Comput. Electron. Agric..

[17]  Moon S. Kim,et al.  Short wave infrared (SWIR) hyperspectral imaging technique for examination of aflatoxin B1 (AFB1) on corn kernels , 2015 .

[18]  Dongyan Zhang,et al.  Automatic extraction of wheat lodging area based on transfer learning method and deeplabv3+ network , 2020, Comput. Electron. Agric..

[19]  Tinashe Nyabako,et al.  Predicting Prostephanus truncatus (Horn) (Coleoptera: Bostrichidae) populations and associated grain damage in smallholder farmers’ maize stores: A machine learning approach , 2020, Journal of Stored Products Research.

[20]  J. Gershenzon,et al.  Plant defense and herbivore counter-defense: benzoxazinoids and insect herbivores , 2016, Phytochemistry Reviews.

[21]  Teuvo Kohonen,et al.  Self-organized formation of topologically correct feature maps , 2004, Biological Cybernetics.

[22]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[23]  M. Erb,et al.  Induction and detoxification of maize 1,4-benzoxazin-3-ones by insect herbivores. , 2011, The Plant journal : for cell and molecular biology.

[24]  Lucas Prado Osco,et al.  Leaf Nitrogen Concentration and Plant Height Prediction for Maize Using UAV-Based Multispectral Imagery and Machine Learning Techniques , 2020, Remote. Sens..

[25]  Anne-Katrin Mahlein Plant Disease Detection by Imaging Sensors - Parallels and Specific Demands for Precision Agriculture and Plant Phenotyping. , 2016, Plant disease.

[26]  Shintaroh Ohashi,et al.  Detection of external insect infestations in jujube fruit using hyperspectral reflectance imaging , 2011 .

[27]  Yanbo Huang,et al.  Monitoring plant diseases and pests through remote sensing technology: A review , 2019, Comput. Electron. Agric..

[28]  V. Singh,et al.  A review of imaging techniques for plant disease detection , 2020 .

[29]  S. E. Abd El-Aziz,et al.  A review: application of remote sensing as a promising strategy for insect pests and diseases management , 2020, Environmental Science and Pollution Research.

[30]  D. Ayalew,et al.  Status and control measures of fall armyworm (Spodoptera frugiperda) infestations in maize fields in Ethiopia: A review , 2019, Cogent Food & Agriculture.

[31]  Hassan Mostafa,et al.  Applying Machine Learning Technology in the Prediction of Crop Infestation with Cotton Leafworm in Greenhouse , 2020, bioRxiv.