Snapshot Hyperspectral Imaging in Agriculture & Food Literature


Literature

Snapshot Hyperspectral Imaging in Agriculture & Food

2021

Ren, Y., Huang, W., Ye, H., Zhou, X., Ma, H., Dong, Y., Shi, Y., Geng, Y., Huang, Y., Jiao, Q. and Xie, Q., 2021. Quantitative identification of yellow rust in winter wheat with a new spectral index: Development and validation using simulated and experimental data. International Journal of Applied Earth Observation and Geoinformation, 102, p.102384.
Tags: Wheat pigment, water body, PROSPECT-D, yellow rust optimal index (YROI)

Shi, Y., Han, L., Kleerekoper, A., Chang, S., & Hu, T. (2021). A Novel CropdocNet for Automated Potato Late Blight Disease Detection from the Unmanned Aerial Vehicle-based Hyperspectral Imagery. arXiv preprint arXiv:2107.13277.
Tags: Late blight disease, spectral feature-based approach, CropdocNet model

Changchun, L. I., Chunyan, M. A., Peng, C. H. E. N., Yingqi, C. U. I., Jinjin, S. H. I., & Yilin, W. A. N. G. (2021). Machine learning-based estimation of potato chlorophyll content at different growth stages using UAV hyperspectral data. Zemdirbyste-Agriculture, 108(2).
Tags: potato, chlorophyll (Chl) content, support vector machine (SVM)

Cui, L., Yan, L., Zhao, X., Lin, Y., Jin, J., & Zhang, J. (2021). Detection and Discrimination of Tea Plant Stresses Based on Hyperspectral Imaging Technique at a Canopy Level. Phyton, 90(2), 621.
Tags: plant stress, the quality of tea, successive projection algorithm (SPA), K-nearest neighbor (KNN), Random Forest (RF), Fisher discriminant analysis

Khairunniza-Bejo, S., Shahibullah, M. S., Azmi, A. N. N., & Jahari, M. (2021). Non-Destructive Detection of Asymptomatic Ganoderma boninense Infection of Oil Palm Seedlings Using NIR-Hyperspectral Data and Support Vector Machine. Applied Sciences, 11(22), 10878.
Tags: Ganoderma boninense Infection, support vector machine (SVM), operating characteristic curve (AUC)

Zhu, W., Sun, Z., Yang, T., Li, J., Peng, J., Zhu, K., Li, S., Gong, H., Lyu, Y., Li, B. and Liao, X., (2020). Estimating leaf chlorophyll content of crops via optimal unmanned aerial vehicle hyperspectral data at multi-scales. Computers and Electronics in Agriculture, 178, p.105786.
Tags: Leaf chlorophyll content (LCC), nutrition in crop plants, nitrogen (N)

Ma, H., Huang, W., Dong, Y., Liu, L., & Guo, A. (2021). Using UAV-Based Hyperspectral Imagery to Detect Winter Wheat Fusarium Head Blight. Remote Sensing, 13(15), 3024.
Tags: Fusarium head blight (FHB), wavelet features (WFs)

Feng, H., Tao, H., Zhao, C., Li, Z., & Yang, G. (2021). Comparison of UAV RGB Imagery and Hyperspectral Remote-sensing Data for Monitoring Winter-wheat Growth. Link
Tags: comprehensive growth index (CGI), modified green-red vegetation index(MGRVI)

Zhang, J., Tian, Y., Yan, L., Wang, B., Wang, L., Xu, J., & Wu, K. (2021). Diagnosing the symptoms of sheath blight disease on rice stalk with an in-situ hyperspectral imaging technique. Biosystems Engineering, 209, 94-105.
Tags: Rhizoctonia solani, stalk disease, Hyperspectral Feature Profile Scanning-based Scab Detection (HFPSSD)

Zhang, Y., Xia, C., Zhang, X., Cheng, X., Feng, G., Wang, Y., & Gao, Q. (2021). Estimating the maize biomass by crop height and narrowband vegetation indices derived from UAV-based hyperspectral images. Ecological Indicators, 129, 107985.
Tags: aboveground biomass (AGB), Stepwise regression, random forest (RF) regression, XGBoost regression

Azmi, A. N., Bejo, S. K., Jahari, M., Muharam, F. M., & Yule, I. (2021). Differences between healthy and Ganoderma boninense infected oil palm seedlings using spectral reflectance of young leaf data. Basrah Journal of Agricultural Sciences, 34, 171-179.
Tags: basal stem rot (BSR), Ganoderma boninense

Zhao, Y., Sun, Y., Lu, X., Zhao, X., Yang, L., Sun, Z., & Bai, Y. (2021). Hyperspectral retrieval of leaf physiological traits and their links to ecosystem productivity in grassland monocultures. Ecological Indicators, 122, 107267.
Tags: physiological traits, area-based content, mass-based concentration

Wijesingha, J., Dayananda, S., Wachendorf, M., & Astor, T. (2021). Comparison of Spaceborne and UAV-Borne Remote Sensing Spectral Data for Estimating Monsoon Crop Vegetation Parameters. Sensors, 21(8), 2886.
Tags: monsoon crops, tropical regions, finger millet, maize, lablab

Yue, J., Zhou, C., Guo, W., Feng, H., & Xu, K. (2021). Estimation of winter-wheat above-ground biomass using the wavelet analysis of unmanned aerial vehicle-based digital images and hyperspectral crop canopy images. International Journal of Remote Sensing, 42(5), 1602-1622.
Tags: above-ground biomass (AGB), image wavelet decomposition (IWD), continuous wavelet transform (CWT)

Wang, L., Chen, S., Peng, Z., Huang, J., Wang, C., Jiang, H., Zheng, Q. and Li, D., (2021). Phenology Effects on Physically Based Estimation of Paddy Rice Canopy Traits from UAV Hyperspectral Imagery. Remote Sensing, 13(9), p.1792.
Tags: PROSAIL model, leaf area index (LAI), leaf cholorphyll content (LCC), canopy chlorophyll content (CCC)

Wang, L., Chen, S., Li, D., Wang, C., Jiang, H., Zheng, Q., & Peng, Z. (2021). Estimation of paddy rice nitrogen content and accumulation both at leaf and plant levels from UAV hyperspectral imagery. Remote Sensing, 13(15), 2956.
Tags: plant nitrogen content (PNC), leaf nitrogen accumulation (LNA), plant nitrogen accumulation (PNA)

Lu, J., Li, W., Yu, M., Zhang, X., Ma, Y., Su, X., Yao, X., Cheng, T., Zhu, Y., Cao, W. and Tian, Y., (2021). Estimation of rice plant potassium accumulation based on non-negative matrix factorization using hyperspectral reflectance. Precision Agriculture, 22, pp.51-74.
Tags: plant potassium accumulation (PKA), non-negative matrix factorization (NMF)

Guo, A., Huang, W., Dong, Y., Ye, H., Ma, H., Liu, B., Wu, W., Ren, Y., Ruan, C. and Geng, Y., (2021). Wheat yellow rust detection using UAV-based hyperspectral technology. Remote Sensing, 13(1), p.123.
Tags: exture features (TFs), leaf scale disease monitoring

Yue, J., Guo, W., Yang, G., Zhou, C., Feng, H., & Qiao, H. (2021). Method for accurate multi-growth-stage estimation of fractional vegetation cover using unmanned aerial vehicle remote sensing. Plant Methods, 17(1), 1-16.
Tags: Fractional vegetation cover (FVC), pixel dichotomy model (PDM), crop canopy chlorophyll content (CCC)

Zhao, Y., Sun, Y., Chen, W., Zhao, Y., Liu, X., & Bai, Y. (2021). The Potential of Mapping Grassland Plant Diversity with the Links among Spectral Diversity, Functional Trait Diversity, and Species Diversity. Remote Sensing, 13(15), 3034.
Tags: biodiversity, terrestrial ecosystem, semi-arid

Shu, M., Shen, M., Zuo, J., Yin, P., Wang, M., Xie, Z., Tang, J., Wang, R., Li, B., Yang, X. and Ma, Y., 2021. The Application of UAV-Based Hyperspectral Imaging to Estimate Crop Traits in Maize Inbred Lines. Plant Phenomics, 2021.
Tags: aboveground biomass (AGB), total leaf area (TLA), leaf chlorophyll content (LCC), thousand kernel weight (TWK)

Shu, M., Zuo, J., Shen, M., Yin, P., Wang, M., Yang, X., … & Ma, Y. (2021). Improving the estimation accuracy of SPAD values for maize leaves by removing UAV hyperspectral image backgrounds. International Journal of Remote Sensing, 42(15), 5864-5883.
Tags: narrowband, SPAD, maize, vegetation indices

Schulze‐Brüninghoff, D., Wachendorf, M., & Astor, T. (2021). Remote sensing data fusion as a tool for biomass prediction in extensive grasslands invaded by L. polyphyllus. Remote Sensing in Ecology and Conservation, 7(2), 198-213.
Tags: fresh and dry matter yield (FMY/DMY), Lupinus polyphyllus, terrestrial 3d laser scanner

Xu, X., Nie, C., Jin, X., Li, Z., Zhu, H., Xu, H., … & Feng, H. (2021). A comprehensive yield evaluation indicator based on an improved fuzzy comprehensive evaluation method and hyperspectral data. Field Crops Research, 270, 108204.
Tags: comprehensive yield evaluation indicator (CYEI), winter-wheat, Growth status and trend (GST)

Astor, T., & Wachendorf, M. (2021). Biomass Estimation of Vegetables—Can Remote Sensing Be a Tool for It?. In The Rural-Urban Interface (pp. 95-102). Springer, Cham.
Tags: crop height, vegetable crops, Bangalore in Bengaluru

Wang, T., Liu, Y., Wang, M., Fan, Q., Tian, H., Qiao, X., & Li, Y. (2021). Applications of UAS in Crop Biomass Monitoring: A Review.Frontiers in Plant Science, 12, 595.
Tag: nondestructive, smart agriculture, precision agriculture.

Sun, Z., Wang, X., Wang, Z., Yang, L., Xie, Y., & Huang, Y. (2021). UAVs as remote sensing platforms in plant ecology: review of applications and challenges.Journal of Plant Ecology, 14(6), 1003-1023.
Tags: review, plant ecology, systems, snapshot, costs

2020

Lu, B., Dao, P. D., Liu, J., He, Y., & Shang, J. (2020). Recent advances of hyperspectral imaging technology and applications in agriculture.Remote Sensing, 12(16), 2659.
Tags: review, imaging technology, hyperspectral

Eskandari, R., Mahdianpari, M., Mohammadimanesh, F., Salehi, B., Brisco, B., & Homayouni, S. (2020). Meta-analysis of unmanned aerial vehicle (UAV) imagery for agro-environmental monitoring using machine learning and statistical models.Remote Sensing, 12(21), 3511.
Tags: Agriculture, forestry, grassland mapping, review

Vohland, M., & Jung, A. (2020). Hyperspectral imaging for fine to medium scale applications in environmental sciences.Link
Tags: special issue, multi sensor, image fusion, Lidar, 3D, underwater

Mishra, P., Lohumi, S., Khan, H. A., & Nordon, A. (2020). Close-range hyperspectral imaging of whole plants for digital phenotyping: Recent applications and illumination correction approaches.Computers and Electronics in Agriculture, 178, 105780.
Tags: Digital phenotyping, hyperspectral imaging (HSI)

Buehler, C., Schenkel, F., Gross, W., Schaab, G., & Middelmann, W. (2020). Strategic Optimization of Convolutional Neural Networks for Hyperspectral Land Cover Classification. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 43, 363-369.
Tags: convolutional neural network (1D-CNN), Transfer Learning

Zhang, N., Wang, Y., & Zhang, X. (2020). Extraction of tree crowns damaged by Dendrolimus tabulaeformis Tsai et Liu via spectral-spatial classification using UAV-based hyperspectral images. Plant Methods, 16(1), 1-19.
Tags: Tree crown extraction is, support vector machine (SVM), edge-preserving filter (EPF), Dendrolimus tabulaeformis

Sobejano-Paz, V., Mikkelsen, T. N., Baum, A., Mo, X., Liu, S., Köppl, C. J., … & García, M. (2020).Hyperspectral and thermal sensing of stomatal conductance, transpiration, and photosynthesis for soybean and maize under drought. Remote Sensing, 12(19), 3182.
Tags: crop phenotyping, hydraulic traits, leaf conductance, phenology, photosynthetic CO2 assimilation rate

Li, D., Chen, J.M., Zhang, X., Yan, Y., Zhu, J., Zheng, H., Zhou, K., Yao, X., Tian, Y., Zhu, Y. and Cheng, T., (2020). Improved estimation of leaf chlorophyll content of row crops from canopy reflectance spectra through minimizing canopy structural effects and optimizing off-noon observation time. Remote Sensing of Environment, 248, p.111985.
Tags: LAI insensitive chlorophyll index (LICI), Leaf chlorophyll content (LCC)

Noor Azmi, A. N., Bejo, S. K., Jahari, M., Muharam, F. M., Yule, I., & Husin, N. A. (2020). Early Detection of Ganoderma boninense in Oil Palm Seedlings Using Support Vector Machines. Remote Sensing, 12(23), 3920.
Tags: Ganoderma boninense, basal stem rot (BSR), Support Vector Machine (SVM)

Zhang, J., Wang, C., Yuan, L., Liu, P., Zhang, Y., & Wu, K. (2020). Construction of a plant spectral library based on an optimised feature selection method. Biosystems Engineering, 195, 1-16.
Tags: plant spectral library, Spectral feature screening

Szalay, K., Keller, B., Rák, R., Péterfalvi, N., Kovács, L., Souček, J., Sillinger, F. and Jung, A., (2020). Artificial solar radiation protection of raspberry plantation. Progress in Agricultural Engineering Sciences, 16(S1), pp.141-150.
Tags: climate change, plant breeding, greenhouse, polytunnel solutions

Klos, F., Sut-Lohmann, M., Raab, T., & Hirsch, F. (2020, May). Innovative Drone-based Hyperspectral Detection of Heavy Metals (Ni, Zn, and Cu) in Plants cultivated for Phytomining. In EGU General Assembly Conference Abstracts (p. 9370).
Tags: soil contamination, the recycling of heavy metals, phytoremediation

Astor, T., Dayananda, S., Nautiyal, S., & Wachendorf, M. (2020). Vegetable crop biomass estimation using hyperspectral and RGB 3D UAV Data. Agronomy, 10(10), 1600.
Tags: predict fresh matter yield (FMY), growth stage, Bengaluru

Tao, H., Feng, H., Xu, L., Miao, M., Yang, G., Yang, X., & Fan, L. (2020). Estimation of the Yield and Plant Height of Winter Wheat Using UAV-Based Hyperspectral Images. Sensors, 20(4), 1231.
Tags: yield, extracted plant height HCSM, estimation model, winter wheat

WACHENDORF, M., ASTOR, T., & WIJESINGHA, J. (2020). Remotely sensed information for the protection and management of species-rich grasslands. Link
Tags: Acid detergent fibre (ADF), Crude protein (CP), nitrogen (N), neutral detergent fibre (NDF)

Yue, J., Feng, H., Tian, Q., & Zhou, C. (2020). A robust spectral angle index for remotely assessing soybean canopy chlorophyll content in different growing stages. Plant methods, 16(1), 1-18.
Tags: soybean, chlorophyll, plants, canopy

Zheng, Q., Huang, W., Ye, H., Dong, Y., Shi, Y., & Chen, S. (2020). Using continous wavelet analysis for monitoring wheat yellow rust in different infestation stages based on unmanned aerial vehicle hyperspectral images. Applied Optics, 59(26), 8003-8013.
Tags: wheat yellow rust, crop quality, wavelet, support vector machine (SVM)

Liu, M., Yu, T., Gu, X., Sun, Z., Yang, J., Zhang, Z., … & Li, J. (2020). The Impact of Spatial Resolution on the Classification of Vegetation Types in Highly Fragmented Planting Areas Based on Unmanned Aerial Vehicle Hyperspectral Images. Remote Sensing, 12(1), 146.
Tags: object-based image analysis (OBIA), eucalyptus, citrus, sugarcane

Wijesingha, J., Astor, T., Schulze-Brüninghoff, D., Wengert, M., & Wachendorf, M. (2020). Predicting Forage Quality of Grasslands Using UAV-Borne Imaging Spectroscopy. Remote Sensing, 12(1), 126.
Tags: Forage quality, grassland, crude protein (CP), acid detergent fibre (ADF)

Liu, H., Zhu, H., Li, Z., & Yang, G. (2020). Quantitative analysis and hyperspectral remote sensing of the nitrogen nutrition index in winter wheat. International Journal of Remote Sensing, 41(3), 858-881.
Tags: nitrogen nutrition index, winter wheat, crops

Qui sommes nous ?

20 ans d'Expérience en Photonique

PHOT’Innov, 20 ans d’expérience au service de l’innovation en Photonique pour vous accompagner dans votre Recherche et votre Développement et vous aider à avoir un temps d’avance.

Abonnez-vous à notre newsletter

Et recevez nos dernière actualités & offres spéciales