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Guo, T.,
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IEEE DOI
1903
crops, soil, vegetation mapping, reduced prediction saturation,
view effects, leaf area index, winter wheat, vegetation indices, LAI,
winter wheat
BibRef
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Yang, G.[Guijun],
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Elsevier DOI
1903
Unmanned aerial vehicle, Vegetation indices,
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1903
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1904
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Integrating Growth and Environmental Parameters to Discriminate
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Automatic Wheat Ear Counting Using Thermal Imagery,
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1904
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Agriculture, Machine learning, Actual yield, Yield Gap,
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Soil moisture, Soil measurements, Synthetic aperture radar,
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Shang, J.L.[Jia-Li],
Liao, C.H.[Chun-Hua],
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Sun, J.[Jing],
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Spatiotemporal Dynamics of the Northern Limit of Winter Wheat in
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2008
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Deriving Wheat Crop Productivity Indicators Using Sentinel-1 Time
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2008
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Zhou, X.F.[Xian-Feng],
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Yuan, L.[Lin],
Ye, H.C.[Hui-Chun],
Huang, W.J.[Wen-Jiang],
Assessment of Leaf Chlorophyll Content Models for Winter Wheat Using
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DOI Link
2008
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Upreti, D.[Deepak],
Pignatti, S.[Stefano],
Pascucci, S.[Simone],
Tolomio, M.[Massimo],
Huang, W.J.[Wen-Jiang],
Casa, R.[Raffaele],
Bayesian Calibration of the Aquacrop-OS Model for Durum Wheat by
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2008
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Lang, T.T.[Ting-Ting],
Yang, Y.Z.[Yan-Zhao],
Jia, K.[Kun],
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Remotely-Sensed Imagery and Process-Based Model Simulations,
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2009
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Aranguren, M.[Marta],
Castellón, A.[Ander],
Aizpurua, A.[Ana],
Wheat Yield Estimation with NDVI Values Using a Proximal Sensing Tool,
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2009
BibRef
Cicuéndez, V.[Víctor],
Rodríguez-Rastrero, M.[Manuel],
Recuero, L.[Laura],
Huesca, M.[Margarita],
Schmid, T.[Thomas],
Inclán, R.[Rosa],
Litago, J.[Javier],
Sánchez-Girón, V.[Víctor],
Palacios-Orueta, A.[Alicia],
First Insights on Soil Respiration Prediction across the Growth
Stages of Rainfed Barley Based on Simulated MODIS and Sentinel-2
Spectral Indices,
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2009
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Wang, S.[Shuai],
Chen, J.[Jin],
Rao, Y.H.[Yu-Han],
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Elsevier DOI
2009
Spring frost, Winter wheat, Damage assessment, Remote sensing, North China
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Zhu, K.Y.[Kang-Ying],
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Zhao, F.H.[Feng-Hua],
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Lai, J.B.[Jian-Bin],
Long, B.[Buju],
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Remotely sensed canopy resistance model for analyzing the stomatal
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Elsevier DOI
2009
Remote sensing model, Canopy resistance, Stomatal behavior,
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Nutrient Prediction for Tef (Eragrostis tef) Plant and Grain with
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2009
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Lee, T.[Trey],
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Franzluebbers, A.[Alan],
Ma, S.F.[Sheng-Fang],
Zhou, Y.T.[Yu-Ting],
Assessing Remote Sensing Vegetation Index Sensitivities for Tall
Fescue (Schedonorus arundinaceus) Plant Health with Varying Endophyte
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RS(13), No. 3, 2021, pp. xx-yy.
DOI Link
2102
BibRef
Zhuo, W.[Wen],
Huang, J.X.[Jian-Xi],
Gao, X.R.[Xin-Ran],
Ma, H.Y.[Hong-Yuan],
Huang, H.[Hai],
Su, W.[Wei],
Meng, J.[Jihua],
Li, Y.[Ying],
Chen, H.L.[Huai-Liang],
Yin, D.Q.[Dong-Qin],
Prediction of Winter Wheat Maturity Dates through Assimilating
Remotely Sensed Leaf Area Index into Crop Growth Model,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link
2009
BibRef
Sapkota, B.[Bishwa],
Singh, V.[Vijay],
Neely, C.[Clark],
Rajan, N.[Nithya],
Bagavathiannan, M.[Muthukumar],
Detection of Italian Ryegrass in Wheat and Prediction of Competitive
Interactions Using Remote-Sensing and Machine-Learning Techniques,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link
2009
BibRef
Weiß, T.[Thomas],
Ramsauer, T.[Thomas],
Löw, A.[Alexander],
Marzahn, P.[Philip],
Evaluation of Different Radiative Transfer Models for Microwave
Backscatter Estimation of Wheat Fields,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link
2009
BibRef
Chen, P.F.[Peng-Fei],
Estimation of Winter Wheat Grain Protein Content Based on Multisource
Data Assimilation,
RS(12), No. 19, 2020, pp. xx-yy.
DOI Link
2010
BibRef
Song, Y.[Yang],
Wang, J.[Jing],
Wang, L.X.[Li-Xin],
Satellite Solar-Induced Chlorophyll Fluorescence Reveals Heat Stress
Impacts on Wheat Yield in India,
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2010
BibRef
Huang, X.[Xin],
Zhu, W.Q.[Wen-Quan],
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Sun, L.X.[Li-Xin],
A Method for Monitoring and Forecasting the Heading and Flowering
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RS(12), No. 21, 2020, pp. xx-yy.
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2011
BibRef
Tian, H.F.[Hai-Feng],
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Huang, J.X.[Jian-Xi],
Li, X.[Xuecao],
Wang, J.[Jian],
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Qin, Y.[Yaochen],
Wang, L.[Li],
Garlic and Winter Wheat Identification Based on Active and Passive
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DOI Link
2011
BibRef
Shawon, A.R.[Ashifur Rahman],
Ko, J.[Jonghan],
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Lee, K.D.[Kyung Do],
Shim, S.I.[Sang In],
Two-Dimensional Simulation of Barley Growth and Yield Using a Model
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DOI Link
2011
BibRef
Aharon, S.[Shlomi],
Peleg, Z.[Zvi],
Argaman, E.[Eli],
Ben-David, R.[Roi],
Lati, R.N.[Ran N.],
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DOI Link
2012
BibRef
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Christopher, J.[Jack],
Apan, A.[Armando],
Roy Choudhury, M.[Malini],
Chapman, S.[Scott],
Menzies, N.W.[Neal W.],
Dang, Y.P.[Yash P.],
UAV-Thermal imaging and agglomerative hierarchical clustering
techniques to evaluate and rank physiological performance of wheat
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PandRS(173), 2021, pp. 221-237.
Elsevier DOI
2102
Canopy temperature, Plant water stress, Vegetation indices,
Agglomerative hierarchical clustering, Wheat genotypes, Sodic soil
BibRef
Bates, J.S.[Jordan Steven],
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Estimating Canopy Density Parameters Time-Series for Winter Wheat
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RS(13), No. 4, 2021, pp. xx-yy.
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2103
BibRef
Fu, Y.Y.[Yuan-Yuan],
Yang, G.[Guijun],
Song, X.Y.[Xiao-Yu],
Li, Z.H.[Zhen-Hong],
Xu, X.G.[Xin-Gang],
Feng, H.[Haikuan],
Zhao, C.J.[Chun-Jiang],
Improved Estimation of Winter Wheat Aboveground Biomass Using
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RS(13), No. 4, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Gorrab, A.[Azza],
Ameline, M.[Maël],
Albergel, C.[Clément],
Baup, F.[Frédéric],
Use of Sentinel-1 Multi-Configuration and Multi-Temporal Series for
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RS(13), No. 4, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Marino, S.[Stefano],
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Vegetation Indices Data Clustering for Dynamic Monitoring and
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RS(13), No. 4, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Liu, Y.[Yu],
Hatou, K.[Kenji],
Aihara, T.[Takanori],
Kurose, S.[Sakuya],
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A Robust Vegetation Index Based on Different UAV RGB Images to
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RS(13), No. 4, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Sadeghi-Tehran, P.[Pouria],
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A Neural Network Method for Classification of Sunlit and Shaded
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RS(13), No. 5, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Bhandari, M.[Mahendra],
Baker, S.[Shannon],
Rudd, J.C.[Jackie C.],
Ibrahim, A.M.H.[Amir M. H.],
Chang, A.[Anjin],
Xue, Q.W.[Qing-Wu],
Jung, J.H.[Jin-Ha],
Landivar, J.[Juan],
Auvermann, B.[Brent],
Assessing the Effect of Drought on Winter Wheat Growth Using Unmanned
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RS(13), No. 6, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Li, F.J.[Fang-Jie],
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Wu, S.R.[Shang-Rong],
Zhao, H.W.[Hong-Wei],
Zhang, N.D.[Ning-Dan],
Comparison of Regional Winter Wheat Mapping Results from Different
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RS(13), No. 6, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Rufo, R.[Rubén],
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Bellvert, J.[Joaquim],
Using Unmanned Aerial Vehicle and Ground-Based RGB Indices to Assess
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RS(13), No. 6, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Zhang, W.M.[Wen-Min],
Brandt, M.[Martin],
Prishchepov, A.V.[Alexander V.],
Li, Z.F.[Zhao-Fu],
Lyu, C.G.[Chun-Guang],
Fensholt, R.[Rasmus],
Mapping the Dynamics of Winter Wheat in the North China Plain from
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RS(13), No. 6, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Raya-Sereno, M.D.[María D.],
Ortiz-Monasterio, J.I.[J. Ivan],
Alonso-Ayuso, M.[María],
Rodrigues, F.A.[Francelino A.],
Rodríguez, A.A.[Arlet A.],
González-Perez, L.[Lorena],
Quemada, M.[Miguel],
High-Resolution Airborne Hyperspectral Imagery for Assessing Yield,
Biomass, Grain N Concentration, and N Output in Spring Wheat,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link
2104
BibRef
Dandrifosse, S.[Sébastien],
Carlier, A.[Alexis],
Dumont, B.[Benjamin],
Mercatoris, B.[Benoît],
Registration and Fusion of Close-Range Multimodal Wheat Images in
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RS(13), No. 7, 2021, pp. xx-yy.
DOI Link
2104
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Ayari, E.[Emna],
Kassouk, Z.[Zeineb],
Lili-Chabaane, Z.[Zohra],
Baghdadi, N.[Nicolas],
Bousbih, S.[Safa],
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DOI Link
2104
BibRef
Wu, B.[Bin],
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Ren, Y.[Yu],
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RS(13), No. 8, 2021, pp. xx-yy.
DOI Link
2104
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Pour, M.K.[Majid Khak],
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2104
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Qu, C.[Chang],
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A spectral index for winter wheat mapping using multi-temporal
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Elsevier DOI
2105
Winter wheat mapping, Multi-temporal Landsat NDVI,
Winter wheat index (WWI), Growth stages
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Li, S.L.[Shi-Lei],
Li, F.J.[Fang-Jie],
Gao, M.F.[Mao-Fang],
Li, Z.L.[Zhao-Liang],
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Duan, S.[Sibo],
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A New Method for Winter Wheat Mapping Based on Spectral
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RS(13), No. 9, 2021, pp. xx-yy.
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2105
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Zhao, F.[Fa],
Yang, G.J.[Gui-Jun],
Yang, X.D.[Xiao-Dong],
Cen, H.Y.[Hai-Yan],
Zhu, Y.O.[Ya-Ohui],
Han, S.Y.[Shao-Yu],
Yang, H.[Hao],
He, Y.[Yong],
Zhao, C.J.[Chun-Jiang],
Determination of Key Phenological Phases of Winter Wheat Based on the
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RS(13), No. 9, 2021, pp. xx-yy.
DOI Link
2105
BibRef
Wu, X.C.[Xiao-Cui],
Xiao, X.M.[Xiang-Ming],
Steiner, J.[Jean],
Yang, Z.W.[Zheng-Wei],
Qin, Y.W.[Yuan-Wei],
Wang, J.[Jie],
Spatiotemporal Changes of Winter Wheat Planted and Harvested Areas,
Photosynthesis and Grain Production in the Contiguous United States
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RS(13), No. 9, 2021, pp. xx-yy.
DOI Link
2105
BibRef
de Camargo, T.[Tibor],
Schirrmann, M.[Michael],
Landwehr, N.[Niels],
Dammer, K.H.[Karl-Heinz],
Pflanz, M.[Michael],
Optimized Deep Learning Model as a Basis for Fast UAV Mapping of Weed
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RS(13), No. 9, 2021, pp. xx-yy.
DOI Link
2105
BibRef
Jenal, A.[Alexander],
Hüging, H.[Hubert],
Ahrends, H.E.[Hella Ellen],
Bolten, A.[Andreas],
Bongartz, J.[Jens],
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Investigating the Potential of a Newly Developed UAV-Mounted
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RS(13), No. 9, 2021, pp. xx-yy.
DOI Link
2105
BibRef
Shiff, S.[Shilo],
Lensky, I.M.[Itamar M.],
Bonfil, D.J.[David J.],
Using Satellite Data to Optimize Wheat Yield and Quality under
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RS(13), No. 11, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Shen, J.X.[Jian-Xiu],
Evans, F.H.[Fiona H.],
The Potential of Landsat NDVI Sequences to Explain Wheat Yield
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DOI Link
2106
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Romano, E.[Elio],
Bergonzoli, S.[Simone],
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Bisaglia, C.[Carlo],
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Methodology for the Definition of Durum Wheat Yield Homogeneous Zones
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RS(13), No. 11, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Weiß, T.[Thomas],
Ramsauer, T.[Thomas],
Jagdhuber, T.[Thomas],
Löw, A.[Alexander],
Marzahn, P.[Philip],
Sentinel-1 Backscatter Analysis and Radiative Transfer Modeling of
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RS(13), No. 12, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Fei, S.P.[Shuai-Peng],
Hassan, M.A.[Muhammad Adeel],
He, Z.H.[Zhong-Hu],
Chen, Z.[Zhen],
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Wang, J.K.[Jian-Kang],
Li, C.C.[Chang-Chun],
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Assessment of Ensemble Learning to Predict Wheat Grain Yield Based on
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RS(13), No. 12, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Ji, J.C.[Jing-Chun],
Liu, J.[Jianli],
Chen, J.J.[Jing-Jing],
Niu, Y.J.[Yu-Jie],
Xuan, K.F.[Ke-Fan],
Jiang, Y.F.[Yi-Fei],
Jia, R.[Renhao],
Wang, C.[Can],
Li, X.P.[Xiao-Peng],
Optimization of Topdressing for Winter Wheat by Accurate Growth
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RS(13), No. 12, 2021, pp. xx-yy.
DOI Link
2106
BibRef
Manivasagam, V.S.,
Sadeh, Y.[Yuval],
Kaplan, G.[Gregoriy],
Bonfil, D.J.[David J.],
Rozenstein, O.[Offer],
Studying the Feasibility of Assimilating Sentinel-2 and PlanetScope
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RS(13), No. 12, 2021, pp. xx-yy.
DOI Link
2106
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Evans, F.H.[Fiona H.],
Shen, J.X.[Jian-Xiu],
Long-Term Hindcasts of Wheat Yield in Fields Using Remotely Sensed
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RS(13), No. 13, 2021, pp. xx-yy.
DOI Link
2107
BibRef
Wengert, M.[Matthias],
Piepho, H.P.[Hans-Peter],
Astor, T.[Thomas],
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Wijesingha, J.[Jayan],
Wachendorf, M.[Michael],
Assessing Spatial Variability of Barley Whole Crop Biomass Yield and
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RS(13), No. 14, 2021, pp. xx-yy.
DOI Link
2107
BibRef
Herzig, P.[Paul],
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Knauer, U.[Uwe],
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Kilias, D.[David],
Seiffert, U.[Udo],
Pillen, K.[Klaus],
Maurer, A.[Andreas],
Evaluation of RGB and Multispectral Unmanned Aerial Vehicle (UAV)
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RS(13), No. 14, 2021, pp. xx-yy.
DOI Link
2107
BibRef
Zeng, L.L.[Ling-Lin],
Peng, G.Z.[Guo-Zhang],
Meng, R.[Ran],
Man, J.G.[Jian-Guo],
Li, W.[Weibo],
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Lv, Z.G.[Zhen-Gang],
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Wheat Yield Prediction Based on Unmanned Aerial Vehicles-Collected
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RS(13), No. 15, 2021, pp. xx-yy.
DOI Link
2108
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Colaço, A.F.[André Freitas],
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Broadacre Mapping of Wheat Biomass Using Ground-Based LiDAR
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RS(13), No. 16, 2021, pp. xx-yy.
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2109
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Zhao, J.Q.[Jian-Qing],
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A Wheat Spike Detection Method in UAV Images Based on Improved YOLOv5,
RS(13), No. 16, 2021, pp. xx-yy.
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2109
BibRef
Zhao, L.C.[Li-Cheng],
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An Efficient Method for Estimating Wheat Heading Dates Using UAV
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RS(13), No. 16, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Choudhury, M.R.[Malini Roy],
Das, S.[Sumanta],
Christopher, J.[Jack],
Apan, A.[Armando],
Chapman, S.[Scott],
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Improving Biomass and Grain Yield Prediction of Wheat Genotypes on
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RS(13), No. 17, 2021, pp. xx-yy.
DOI Link
2109
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Peron-Danaher, R.[Raquel],
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Incorporating Multi-Scale, Spectrally Detected Nitrogen
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RS(13), No. 19, 2021, pp. xx-yy.
DOI Link
2110
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Kong, W.P.[Wei-Ping],
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RS(13), No. 20, 2021, pp. xx-yy.
DOI Link
2110
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Eyre, R.[Riley],
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IEEE DOI
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Agriculture, Remote sensing, Synthetic aperture radar,
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A Rapid Model (COV_PSDI) for Winter Wheat Mapping in Fallow Rotation
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2112
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Current Status and Future Opportunities for Grain Protein Prediction
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Comparison of Winter Wheat Extraction Methods Based on Different Time
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2202
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2203
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Mikhailenko, I.M.[Ilya Mikhayilovich],
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The Self-Supervised Spectral-Spatial Vision Transformer Network for
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2204
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Combining Crop Modeling with Remote Sensing Data Using a Particle
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2204
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Assessing the Potential of Downscaled Far Red Solar-Induced
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2204
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2204
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Elsevier DOI
2205
Multi-temporal, Acquisition dates, Effects evaluation,
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2205
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Dynamic Harvest Index Estimation of Winter Wheat Based on UAV
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RS(14), No. 9, 2022, pp. xx-yy.
DOI Link
2205
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Deng, Q.[Qiuzhuo],
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Winter Wheat Yield Estimation Based on Optimal Weighted Vegetation
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2205
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Chen, L.[Lin],
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Estimating Soil Moisture over Winter Wheat Fields during Growing
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2205
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Jennewein, J.S.[Jyoti S.],
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Integration of Satellite-Based Optical and Synthetic Aperture Radar
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2205
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Huang, X.J.[Xiao-Juan],
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High-Resolution Mapping of Winter Cereals in Europe by Time Series
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2205
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Developing an Active Canopy Sensor-Based Integrated Precision Rice
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2206
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UAV Remote Sensing for Detecting within-Field Spatial Variation of
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2206
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A First Approach to Determine If It Is Possible to Delineate
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2208
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2208
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2208
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2208
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2209
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SC-CAN: Spectral Convolution and Channel Attention Network for Wheat
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2209
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Stacking of Canopy Spectral Reflectance from Multiple Growth Stages
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Verrelst, J.[Jochem],
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Seasonal Mapping of Irrigated Winter Wheat Traits in Argentina with a
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2209
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IEEE DOI
2112
Head, Uncertainty, Image color analysis, Lighting,
Transforms, Detectors
BibRef
Bhagat, S.[Sandesh],
Kokare, M.[Manesh],
Haswani, V.[Vineet],
Hambarde, P.[Praful],
Kamble, R.[Ravi],
WheatNet-Lite: A Novel Light Weight Network for Wheat Head Detection,
CVPPA21(1332-1341)
IEEE DOI
2112
Deep learning, Head, Convolution, Annotations, Image edge detection,
Crops, Feature extraction
BibRef
Najafian, K.[Keyhan],
Ghanbari, A.[Alireza],
Stavness, I.[Ian],
Jin, L.L.[Ling-Ling],
Shirdel, G.H.[Gholam Hassan],
Maleki, F.[Farhad],
A Semi-self-supervised Learning Approach for Wheat Head Detection
using Extremely Small Number of Labeled Samples,
CVPPA21(1342-1351)
IEEE DOI
2112
Training, Deep learning, Adaptation models, Head,
Computational modeling, Conferences
BibRef
Gansukh, B.,
Batsaikhan, B.,
Dorjsuren, A.,
Jamsran, C.,
Batsaikhan, N.,
Monitoring Wheat Crop Growth Parameters Using Time Series Sentinel-1
And Sentinel-2 Data for Agricultural Application In Mongolia,
ISPRS20(B3:989-994).
DOI Link
2012
BibRef
Chauhan, S.,
Darvishzadeh, R.,
Lu, Y.,
Stroppiana, D.,
Boschetti, M.,
Pepe, M.,
Nelson, A.,
Wheat Lodging Assessment Using Multispectral UAV Data,
UAV-g19(235-240).
DOI Link
1912
BibRef
Aich, S.,
Josuttes, A.,
Ovsyannikov, I.,
Strueby, K.,
Ahmed, I.,
Duddu, H.S.,
Pozniak, C.,
Shirtliffe, S.,
Stavness, I.,
DeepWheat: Estimating Phenotypic Traits from Crop Images with Deep
Learning,
WACV18(323-332)
IEEE DOI
1806
crops, deconvolution, feature extraction, image colour analysis,
learning (artificial intelligence), regression analysis,
Task analysis
BibRef
Wellens, J.,
Sallah, A.H.,
Tychon, B.,
Piccard, I.,
Gobin, A.,
Curnel, Y.,
Leclef, A.,
Goffart, D.,
Planchon, V.,
Goffart, J.P.,
Delloye, C.,
Defourny, P.,
Assessment of AquaCrop for winter wheat using satellite derived
fCover data,
MultiTemp17(1-3)
IEEE DOI
1712
crops, mean square error methods, remote sensing,
AquaCrop assessment, AquaCrop plug-in model, Belgium,
yield estimate
BibRef
Nakanishi, T.,
Imai, Y.,
Morita, T.,
Akamatsu, Y.,
Odagawa, S.,
Takeda, T.,
Kashimura, O.,
Evaluation Of Wheat Growth Monitoring Methods Based On Hyperspectral
Data Of Later Grain Filling And Heading Stages In Western Australia,
ISPRS12(XXXIX-B8:295-300).
DOI Link
1209
BibRef
Zhang, H.,
Chen, H.,
Zhou, G.,
The Model Of Wheat Yield Forecast Based On Modis-ndvi: A Case Study Of
Xinxiang,
AnnalsPRS(I-7), No. 2012, pp. 25-28.
HTML Version.
1209
BibRef
d'Andrimont, R.[Raphael],
Duveiller, G.[Gregory],
Defourny, P.[Pierre],
Exploring the capacity to grasp multi-annual seasonal variability of
winter wheat in Continental Climates with MODIS,
MultiTemp11(221-224).
IEEE DOI
1109
BibRef
Chacon, M.I.[Mario I.],
Manickavasagan, A.[Annamalai],
Flores-Tapia, D.[Daniel],
Thomas, G.[Gabriel],
Jayas, D.S.[Digvir S.],
Segmentation of Wheat Grains in Thermal Images Based on Pulse Coupled
Neural Networks,
ICIP07(II: 273-276).
IEEE DOI
0709
BibRef
Guzman-Arenas, A.,
Seco, R.M.[Rosa Ma], and
Sanchez, V.G.[Victor G.],
Computer Analysis of Images for Crop Identification in Mexico,
TRIIMAS, Vol. 7, no. 135, 1976, UNAM.
Crop id - wheat/cotton in NW Mexico; standard classification
techniques; spectral signature and set of heuristic functions that
the user defines.
BibRef
7600
Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Wheat Rust, Blight, Disease .