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Sherstneva O, Abdullaev F, Kior D, Yudina L, Gromova E, Vodeneev V. Prediction of biomass accumulation and tolerance of wheat seedlings to drought and elevated temperatures using hyperspectral imaging. Front Plant Sci 2024; 15:1344826. [PMID: 38371404 PMCID: PMC10869465 DOI: 10.3389/fpls.2024.1344826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/26/2023] [Accepted: 01/23/2024] [Indexed: 02/20/2024]
Abstract
Early prediction of important agricultural traits in wheat opens up broad prospects for the development of approaches to accelerate the selection of genotypes for further breeding trials. This study is devoted to the search for predictors of biomass accumulation and tolerance of wheat to abiotic stressors. Hyperspectral (HS) and chlorophyll fluorescence (ChlF) parameters were analyzed as predictors under laboratory conditions. The predictive ability of reflectance and normalized difference indices (NDIs), as well as their relationship with parameters of photosynthetic activity, which is a key process influencing organic matter production and crop yields, were analyzed. HS parameters calculated using the wavelengths in Red (R) band and the spectral range next to the red edge (FR-NIR) were found to be correlated with biomass accumulation. The same ranges showed potential for predicting wheat tolerance to elevated temperatures. The relationship of HS predictors with biomass accumulation and heat tolerance were of opposite sign. A number of ChlF parameters also showed statistically significant correlation with biomass accumulation and heat tolerance. A correlation between HS and ChlF parameters, that demonstrated potential for predicting biomass accumulation and tolerance, has been shown. No predictors of drought tolerance were found among the HS and ChlF parameters analyzed.
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Affiliation(s)
- Oksana Sherstneva
- Department of Biophysics, N.I. Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
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Guo J, Guo J, Li L, Bai X, Huo X, Shi W, Gao L, Dai K, Jing R, Hao C. Combined linkage analysis and association mapping identifies genomic regions associated with yield-related and drought-tolerance traits in wheat (Triticum aestivum L.). Theor Appl Genet 2023; 136:250. [PMID: 37982873 DOI: 10.1007/s00122-023-04494-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 10/26/2023] [Indexed: 11/21/2023]
Abstract
KEY MESSAGE Combined linkage analysis and association mapping identified genomic regions associated with yield and drought tolerance, providing information to assist breeding for high yield and drought tolerance in wheat. Wheat (Triticum aestivum L.) is one of the most widely grown food crops and provides adequate amounts of protein to support human health. Drought stress is the most important abiotic stress constraining yield during the flowering and grain development periods. Precise targeting of genomic regions underlying yield- and drought tolerance-responsive traits would assist in breeding programs. In this study, two water treatments (well-watered, WW, and rain-fed water stress, WS) were applied, and five yield-related agronomic traits (plant height, PH; spike length, SL; spikelet number per spike, SNPS; kernel number per spike, KNPS; thousand kernel weight, TKW) and drought response values (DRVs) were used to characterize the drought sensitivity of each accession. Association mapping was performed on an association panel of 304 accessions, and linkage analysis was applied to a doubled haploid (DH) population of 152 lines. Eleven co-localized genomic regions associated with yield traits and DRV were identified in both populations. Many previously cloned key genes were located in these regions. In particular, a TKW-associated region on chromosome 2D was identified using both association mapping and linkage analysis and a key candidate gene, TraesCS2D02G142500, was detected based on gene annotation and differences in expression levels. Exonic SNPs were analyzed by sequencing the full length of TraesCS2D02G142500 in the association panel, and a rare haplotype, Hap-2, which reduced TKW to a lesser extent than Hap-1 under drought stress, and the Hap-2 varieties presented drought-insensitive. Altogether, this study provides fundamental insights into molecular targets for high yield and drought tolerance in wheat.
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Affiliation(s)
- Jie Guo
- College of Agronomy, Key Laboratory of Sustainable Dryland Agriculture (Co-Construction By Ministry and Province), Ministry of Agriculture and Rural Affairs, Shanxi Agricultural University, Jinzhong, 030801, Shanxi, China
| | - Jiahui Guo
- College of Agronomy, Key Laboratory of Sustainable Dryland Agriculture (Co-Construction By Ministry and Province), Ministry of Agriculture and Rural Affairs, Shanxi Agricultural University, Jinzhong, 030801, Shanxi, China
- College of Agronomy, Yangzhou University, Yangzhou, 225009, Jiangsu, China
| | - Long Li
- State Key Laboratory of Crop Gene Resources and Breeding/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Xionghui Bai
- College of Agronomy, Key Laboratory of Sustainable Dryland Agriculture (Co-Construction By Ministry and Province), Ministry of Agriculture and Rural Affairs, Shanxi Agricultural University, Jinzhong, 030801, Shanxi, China
| | - Xiaoyu Huo
- College of Agronomy, Key Laboratory of Sustainable Dryland Agriculture (Co-Construction By Ministry and Province), Ministry of Agriculture and Rural Affairs, Shanxi Agricultural University, Jinzhong, 030801, Shanxi, China
| | - Weiping Shi
- College of Agronomy, Key Laboratory of Sustainable Dryland Agriculture (Co-Construction By Ministry and Province), Ministry of Agriculture and Rural Affairs, Shanxi Agricultural University, Jinzhong, 030801, Shanxi, China
| | - Lifeng Gao
- State Key Laboratory of Crop Gene Resources and Breeding/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China
| | - Keli Dai
- College of Agronomy, Key Laboratory of Sustainable Dryland Agriculture (Co-Construction By Ministry and Province), Ministry of Agriculture and Rural Affairs, Shanxi Agricultural University, Jinzhong, 030801, Shanxi, China.
| | - Ruilian Jing
- State Key Laboratory of Crop Gene Resources and Breeding/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
| | - Chenyang Hao
- College of Agronomy, Key Laboratory of Sustainable Dryland Agriculture (Co-Construction By Ministry and Province), Ministry of Agriculture and Rural Affairs, Shanxi Agricultural University, Jinzhong, 030801, Shanxi, China.
- State Key Laboratory of Crop Gene Resources and Breeding/Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, China.
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Uribeetxebarria A, Castellón A, Aizpurua A. A First Approach to Determine If It Is Possible to Delineate In-Season N Fertilization Maps for Wheat Using NDVI Derived from Sentinel-2. Remote Sensing 2022; 14:2872. [DOI: 10.3390/rs14122872] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Adjusting nitrogen fertilization to the nutritional requirements of crops is one of the major challenges of modern agriculture. The amount of N needed is mainly determined by crop yield, so yield maps can be used to optimize N fertilization. As the adoption of yield monitors is low among farmers, implementation of this approach is still low. However, as the Normalized Difference Vegetation Index (NDVI) is related to grain yield, the main objective of this work was to identify at which wheat growth stage a moderate agreement between NDVI and yield is obtained. For this, NDVI images obtained from Sentinel-2 were used, and the evolution of concordance was analyzed in 13 classified parcels of wheat employing the Kappa index (KI). In one-third of the plots, a moderate agreement (KI > 0.4) was reached before the stem elongation growth phase (when the last N application was made). In another one-third, moderate agreement was reached later, in more advanced development stages. For the cases in which this agreement did not exist, an attempt was made to find the causes. The MANOVA and subsequent descriptive discriminant analysis (DDA) showed that the NDVI dates that contribute the most to the differentiation between plots with and without agreement between grain yield maps and NDVI images were those corresponding to tillering. The sum of the NDVI values of the tillering phase was significantly lower in the group of plots that did not show concordance. Sentinel-2 imagery was successful on 66% of plots for delineation of management zones after GS 30, and thus is useful for producing fertilization maps for the upcoming season. However, to produce in-season fertilization maps, further studies are needed to better understand the mechanisms that regulate the relation between yield and NDVI at early growth stages (<GS 30).
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Kim M, Lee C, Hong S, Kim SL, Baek JH, Kim KH. High-Throughput Phenotyping Methods for Breeding Drought-Tolerant Crops. Int J Mol Sci 2021; 22:ijms22158266. [PMID: 34361030 PMCID: PMC8347144 DOI: 10.3390/ijms22158266] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 07/28/2021] [Accepted: 07/29/2021] [Indexed: 12/28/2022] Open
Abstract
Drought is a main factor limiting crop yields. Modern agricultural technologies such as irrigation systems, ground mulching, and rainwater storage can prevent drought, but these are only temporary solutions. Understanding the physiological, biochemical, and molecular reactions of plants to drought stress is therefore urgent. The recent rapid development of genomics tools has led to an increasing interest in phenomics, i.e., the study of phenotypic plant traits. Among phenomic strategies, high-throughput phenotyping (HTP) is attracting increasing attention as a way to address the bottlenecks of genomic and phenomic studies. HTP provides researchers a non-destructive and non-invasive method yet accurate in analyzing large-scale phenotypic data. This review describes plant responses to drought stress and introduces HTP methods that can detect changes in plant phenotypes in response to drought.
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Affiliation(s)
- Minsu Kim
- National Institute of Agricultural Science, RDA, Wanju 54874, Korea; (M.K.); (C.L.); (S.H.); (S.L.K.); (J.-H.B.)
| | - Chaewon Lee
- National Institute of Agricultural Science, RDA, Wanju 54874, Korea; (M.K.); (C.L.); (S.H.); (S.L.K.); (J.-H.B.)
- Department of Crop Science and Biotechnology, Chonbuk National University, Jeonju 54896, Korea
| | - Subin Hong
- National Institute of Agricultural Science, RDA, Wanju 54874, Korea; (M.K.); (C.L.); (S.H.); (S.L.K.); (J.-H.B.)
| | - Song Lim Kim
- National Institute of Agricultural Science, RDA, Wanju 54874, Korea; (M.K.); (C.L.); (S.H.); (S.L.K.); (J.-H.B.)
| | - Jeong-Ho Baek
- National Institute of Agricultural Science, RDA, Wanju 54874, Korea; (M.K.); (C.L.); (S.H.); (S.L.K.); (J.-H.B.)
| | - Kyung-Hwan Kim
- National Institute of Agricultural Science, RDA, Wanju 54874, Korea; (M.K.); (C.L.); (S.H.); (S.L.K.); (J.-H.B.)
- Correspondence:
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