Phenotyping for Resilient and Sustainable Crops

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Crop Breeding and Genetics".

Deadline for manuscript submissions: closed (20 August 2020) | Viewed by 9182

Special Issue Editor


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Guest Editor
Department of Food Science- Plant, Food & Climate, Aarhus University, Agro Food Park 48, DK-8200 Aarhus N, Denmark
Interests: stress and evolution genetics

Special Issue Information

Dear Colleagues,

There is a need to reveal and ultimately exploit the physiological and genotypic resilience mechanisms to combinations of multiple stresses and eCO2. Crops are continuously subjected to a number of different abiotic stresses in nature and in the field.

By 2050, climate change may boost yields by 8%–25%, but abiotic stresses such as drought and heat will have a negative effect. Stress might be alleviated by elevated CO2 but limited by other factors. Heat and drought are two major abiotic stresses that usually occur together. Crops are more vulnerable to multiple stress than single stress and sensitivity peaking in the reproductive phase, and the responses to multiple stresses cannot be deduced by studies of single stress, so the Special Issue is focusing on the huge and unmet need to understand and link the mechanistic basis of responses to multiple stress events to physiology, genetic markers, and on the yield stability which is the focus for the Special Issue.

Please share your success stories from research around the world in this Special Issue.

Submissions on the following topics (but not limited to) are invited:

1) Innovative and novel application of phenotyping in controlled conditions or in fields;

2) Stress effects on crop physiology and productivity;

3) Linking the physiology of crops to genetic marker;

4) Novel phenotyping methods for crops.

Dr. Carl-Otto Ottosen
Guest Editor

Manuscript Submission Information

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Keywords

  • phenotyping
  • multiple stresses
  • elevated CO2
  • stress
  • crop resilience

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Published Papers (2 papers)

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Research

22 pages, 5054 KiB  
Article
Investigating Combined Drought- and Heat Stress Effects in Wheat under Controlled Conditions by Dynamic Image-Based Phenotyping
by Lamis Osama Anwar Abdelhakim, Eva Rosenqvist, Bernd Wollenweber, Ioannis Spyroglou, Carl-Otto Ottosen and Klára Panzarová
Agronomy 2021, 11(2), 364; https://doi.org/10.3390/agronomy11020364 - 18 Feb 2021
Cited by 22 | Viewed by 4947
Abstract
As drought and heat stress are major challenges for crop productivity under future climate changes, tolerant cultivars are highly in demand. This study investigated the potential of existing Nordic wheat genotypes to resist unfavorable conditions. Four genotypes were selected based on their heat [...] Read more.
As drought and heat stress are major challenges for crop productivity under future climate changes, tolerant cultivars are highly in demand. This study investigated the potential of existing Nordic wheat genotypes to resist unfavorable conditions. Four genotypes were selected based on their heat sensitivity (heat-sensitive: LM19, SF1; heat-tolerant: LM62, NS3). At the tillering stage, the plants were subjected to four treatments under controlled conditions: control, drought, heat and combined drought and heat stress. The morpho-physiological performance was quantified during the early and late phase of stress, as well as the recovery phase. We applied an integrative image-based phenotyping approach monitoring plant growth dynamics by structural Red Green Blue (RGB) imaging, photosynthetic performance by chlorophyll fluorescence imaging and transpiration efficiency by thermal infrared imaging. The results demonstrated that the selected genotypes were moderately affected in their photosynthetic efficiency and growth under drought stress, whereas heat and combined stress caused rapid reductions in photosynthesis and growth. Furthermore, drought stress had a major impact on canopy temperature. The NS3 genotype was the most robust genotype, as indicated by its improved response under all stress treatments due to its relatively small biomass. However, the genotypes showed different tolerance to individual and combined stress. Full article
(This article belongs to the Special Issue Phenotyping for Resilient and Sustainable Crops)
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14 pages, 2181 KiB  
Article
Forecasting Yield and Lignocellulosic Composition of Energy Cane Using Unmanned Aerial Systems
by Uriel Cholula, Jorge A. da Silva, Thiago Marconi, J. Alex Thomasson, Jorge Solorzano and Juan Enciso
Agronomy 2020, 10(5), 718; https://doi.org/10.3390/agronomy10050718 - 17 May 2020
Cited by 14 | Viewed by 3838
Abstract
Crop monitoring and appropriate agricultural management practices of elite germplasm will enhance bioenergy’s efficiency. Unmanned aerial systems (UAS) may be a useful tool for this purpose. The objective of this study was to assess the use of UAS with true color and multispectral [...] Read more.
Crop monitoring and appropriate agricultural management practices of elite germplasm will enhance bioenergy’s efficiency. Unmanned aerial systems (UAS) may be a useful tool for this purpose. The objective of this study was to assess the use of UAS with true color and multispectral imagery to predict the yield and total cellulosic content (TCC) of newly created energy cane germplasm. A trial was established in the growing season of 2016 at the Texas A&M AgriLife Research Center in Weslaco, Texas, where 15 energy cane elite lines and three checks were grown on experimental plots, arranged in a complete block design and replicated four times. Four flights were executed at different growth stages in 2018, at the first ratoon crop, using two multi-rotor UAS: the DJI Phantom 4 Pro equipped with RGB camera and the DJI Matrice 100, equipped with multispectral sensor (SlantRange 3p). Canopy cover, canopy height, NDVI (Normalized Difference Vegetation Index), and ExG (Excess Green Index) were extracted from the images and used to perform a stepwise regression to obtain the yield and TCC models. The results showed a good agreement between the predicted and the measured yields (R2 = 0.88); however, a low coefficient of determination was found between the predicted and the observed TCC (R2 = 0.30). This study demonstrated the potential application of UAS to estimate energy cane yield with high accuracy, enabling plant breeders to phenotype larger populations and make selections with higher confidence. Full article
(This article belongs to the Special Issue Phenotyping for Resilient and Sustainable Crops)
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