Affordable Phenotyping of Winter Wheat under Field and Controlled Conditions for Drought Tolerance

被引:27
作者
Kumar, Dhananjay [1 ]
Kushwaha, Sandeep [1 ,2 ]
Delvento, Chiara [1 ,7 ]
Liatukas, Zilvinas [3 ]
Vivekanand, Vivekanand [4 ]
Svensson, Jan T. [5 ]
Henriksson, Tina [6 ]
Brazauskas, Gintaras [3 ]
Chawade, Aakash [1 ]
机构
[1] Swedish Univ Agr Sci SLU, Dept Plant Breeding, Box 101, SE-23053 Alnarp, Sweden
[2] Natl Inst Anim Biotechnol, Hyderabad 500032, India
[3] Lithuanian Res Ctr Agr & Forestry, Inst Agr, LT-58344 Akademija, Lithuania
[4] Malaviya Natl Inst Technol, Ctr Energy & Environm, Jaipur 302017, Rajasthan, India
[5] Nordic Genet Resource Ctr, Box 41, SE-23053 Alnarp, Sweden
[6] Lantmannen Lantbruk, SE-26831 Svalov, Sweden
[7] Univ Bari Aldo Moro, Dept Soil Plant & Food Sci, I-70126 Bari, Italy
来源
AGRONOMY-BASEL | 2020年 / 10卷 / 06期
关键词
wheat; drought; machine learning; affordable phenotyping; YIELD; TECHNOLOGIES; VARIABILITY; PLATFORM; TRAITS;
D O I
10.3390/agronomy10060882
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Drought stress is one of the key plant stresses reducing grain yield in cereal crops worldwide. Although it is not a breeding target in Northern Europe, the changing climate and the drought of 2018 have increased its significance in the region. A key challenge, therefore, is to identify novel germplasm with higher drought tolerance, a task that will require continuous characterization of a large number of genotypes. The aim of this work was to assess if phenotyping systems with low-cost consumer-grade digital cameras can be used to characterize germplasm for drought tolerance. To achieve this goal, we built a proximal phenotyping cart mounted with digital cameras and evaluated it by characterizing 142 winter wheat genotypes for drought tolerance under field conditions. The same genotypes were additionally characterized for seedling stage traits by imaging under controlled growth conditions. The analysis revealed that under field conditions, plant biomass, relative growth rates, and Normalized Difference Vegetation Index (NDVI) from different growth stages estimated by imaging were significantly correlated to drought tolerance. Under controlled growth conditions, root count at the seedling stage evaluated by imaging was significantly correlated to adult plant drought tolerance observed in the field. Random forest models were trained by integrating measurements from field and controlled conditions and revealed that plant biomass and relative growth rates at key plant growth stages are important predictors of drought tolerance. Thus, based on the results, it can be concluded that the consumer-grade cameras can be key components of affordable automated phenotyping systems to accelerate pre-breeding for drought tolerance.
引用
收藏
页数:15
相关论文
共 55 条
[1]   Time-series clustering - A decade review [J].
Aghabozorgi, Saeed ;
Shirkhorshidi, Ali Seyed ;
Teh Ying Wah .
INFORMATION SYSTEMS, 2015, 53 :16-38
[2]   Identification and Classification of Maize Drought Stress Using Deep Convolutional Neural Network [J].
An, Jiangyong ;
Li, Wanyi ;
Li, Maosong ;
Cui, Sanrong ;
Yue, Huanran .
SYMMETRY-BASEL, 2019, 11 (02)
[3]  
[Anonymous], 2013, STAND EV SYST RIC SE
[4]  
[Anonymous], 2019, SUSTAINABILITY BASEL, DOI [DOI 10.3390/su11082450, DOI 10.3390/SU11082450]
[5]   Affordable Imaging Lab for Noninvasive Analysis of Biomass and Early Vigour in Cereal Crops [J].
Armoniene, Rita ;
Odilbekov, Firuz ;
Vivekanand, Vivekanand ;
Chawade, Aakash .
BIOMED RESEARCH INTERNATIONAL, 2018, 2018
[6]   A Review on the Use of Unmanned Aerial Vehicles and Imaging Sensors for Monitoring and Assessing Plant Stresses [J].
Arnal Barbedo, Jayme Garcia .
DRONES, 2019, 3 (02) :1-27
[7]   High-throughput shoot imaging to study drought responses [J].
Berger, Bettina ;
Parent, Boris ;
Tester, Mark .
JOURNAL OF EXPERIMENTAL BOTANY, 2010, 61 (13) :3519-3528
[8]  
Buras A, 2020, BIOGEOSCIENCES, V17, P1655, DOI [10.5194/bg-17-1655-2020,2020, 10.5194/bg-17-1655-2020]
[9]   Deciphering Root Architectural Traits Involved to Cope With Water Deficit in Oat [J].
Canales, Francisco J. ;
Nagel, Kerstin A. ;
Mueller, Carmen ;
Rispail, Nicolas ;
Prats, Elena .
FRONTIERS IN PLANT SCIENCE, 2019, 10
[10]   Impact of meteorological drivers on regional inter-annual crop yield variability in France [J].
Ceglar, Andrej ;
Toreti, Andrea ;
Lecerf, Remi ;
Van der Velde, Marijn ;
Dentener, Frank .
AGRICULTURAL AND FOREST METEOROLOGY, 2016, 216 :58-67