Application of Remote Sensing for Phenotyping Tar Spot Complex Resistance in Maize

Loladze, Alexander; Rodrigues, F. A.; Toledo, Fernando H.; Vicente, Félix San; Gérard, Bruno; Prasanna, Boddupalli M.

doi:10.3389/fpls.2019.00552

Cited by 33 publications

(33 citation statements)

References 51 publications

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“…Limited options are currently available for disease or pest damage detection, spatial distribution, and evaluation. Canopy reflectance in visual and near-infrared wavebands has been used at CIMMYT-Mexico for tar spot complex phenotyping in maize (Loladze et al 2019 ).…”

Section: Increasing Genetic Gain In the Stress-prone Tropical Environmentioning

confidence: 99%

Beat the stress: breeding for climate resilience in maize for the tropical rainfed environments

Cairns²,

et al. 2021

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Key message Intensive public sector breeding efforts and public-private partnerships have led to the increase in genetic gains, and deployment of elite climate-resilient maize cultivars for the stress-prone environments in the tropics. Abstract Maize (Zea mays L.) plays a critical role in ensuring food and nutritional security, and livelihoods of millions of resource-constrained smallholders. However, maize yields in the tropical rainfed environments are now increasingly vulnerable to various climate-induced stresses, especially drought, heat, waterlogging, salinity, cold, diseases, and insect pests, which often come in combinations to severely impact maize crops. The International Maize and Wheat Improvement Center (CIMMYT), in partnership with several public and private sector institutions, has been intensively engaged over the last four decades in breeding elite tropical maize germplasm with tolerance to key abiotic and biotic stresses, using an extensive managed stress screening network and on-farm testing system. This has led to the successful development and deployment of an array of elite stress-tolerant maize cultivars across sub-Saharan Africa, Asia, and Latin America. Further increasing genetic gains in the tropical maize breeding programs demands judicious integration of doubled haploidy, high-throughput and precise phenotyping, genomics-assisted breeding, breeding data management, and more effective decision support tools. Multi-institutional efforts, especially public–private alliances, are key to ensure that the improved maize varieties effectively reach the climate-vulnerable farming communities in the tropics, including accelerated replacement of old/obsolete varieties.

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Section: Increasing Genetic Gain In the Stress-prone Tropical Environmentioning

confidence: 99%

Beat the stress: breeding for climate resilience in maize for the tropical rainfed environments

Cairns²,

et al. 2021

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“…Tenkorang and Lowenberg-Doboer [102] reported that in agriculture, remote sensing has the potential to improve average on-farm profit by about $31.74/ha at standardized budget assumptions. The localization of maize experimental site at CIMMYT Mexico on fungicide and non-fungicide treatments was reported using remote sensing techniques (Figure 2a) [103], crop acreage estimate at the peak of crop growth during growing season using SPOT-5 satellite (Figure 2b), and monthly SPOT NDVI crop phenology behavior in a rainfed area of Punjab (Figure 2c) [104].…”

Section: Remote Sensingmentioning

confidence: 99%

Estimation of Maize (Zea mays L.) Yield Per Harvest Area: Appropriate Methods

Tandzi

Mutengwa

2019

Agronomy

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Standardization of crop yield estimation methods at various levels of farming helps to obtain accurate agricultural statistics as well as assessing the suitability of agricultural practices under various production conditions. The current paper reviews various maize yield estimation methods, taking into account available yield parameters, and it also analyses the yield gap between maize potential and attainable yield. The easiest and more reliable methods of yield estimation are based on yield parameters collected from the field. However, farmer estimation methods are cheaper and faster compared to any other method of yield estimation from farmers’ fields. This paper also elaborates on the importance of the use of more complex methods for yield estimation, such as remote sensing and crop modelling. These complex methods are more accurate and can predict yield before field harvest with less deviation from the exact harvest yield. However, they are very expensive and not efficient for small plots of land (less than 1 ha). Factors that contribute to the gap between potential and actual yield include poor implementation of agricultural policies, strict regulation of fertilizer inputs, vulnerability of smallholder cropping systems to adverse climatic conditions, occurrence of biotic and abiotic constraints, as well as unavailability of seeds and labor.

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“…High-throughput imaging phenotyping techniques are increasingly being used in crop improvement (Araus and Cairns, 2014;Xu et al, 2019;Loladze et al, 2019;Juliana et al, 2019). The most successful study was the application of multispectral camera by Xu et al (2019) to phenotype cotton accessions for canopy cover, as illustrated in Figure 3.…”

Section: Phenotyping For Abiotic Stress Tolerance and Resource Use-efmentioning

confidence: 99%

“…The application was not only efficient in terms of reduced time, but also a strong correlation (R 2 = > 0.92) was found between calculated and measured maximum plant heights and a moderate association (R 2 = 0.32-0.57) between normalized vegetation index and canopy cover. Similarly, Loladze et al (2019) also applied hyperspectral and infrared thermal cameras to phenotype grain yield in maize (Zea mays L.) with different levels of disease infection. The study not only showed strong relationships between grain yield, vegetation index, and canopy temperature under disease pressure ( Table 5), but also demonstrated that imaging techniques could help reduce the time and cost required for the development of improved maize germplasm.…”

Section: Phenotyping For Abiotic Stress Tolerance and Resource Use-efmentioning

confidence: 99%

Advancing Bromegrass Breeding Through Imaging Phenotyping and Genomic Selection: A Review

et al. 2020

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Breeding forage crops for high yields of digestible biomass along with improved resourceuse efficiency and wide adaptation is essential to meet future challenges in forage production imposed by growing demand, declining resources, and changing climate. Bromegrasses (Bromus spp.) are economically important forage species in the temperate regions of world, but genetic gain in forage yield of bromegrass is relatively low. In particular, limited breeding efforts have been made in improving abiotic stress tolerance and resource-use efficiency. We conducted a literature review on bromegrass breeding achievements and challenges, global climate change impacts on bromegrass species, and explored the feasibility of applying high-throughput imaging phenotyping techniques and genomic selection for further advances in forage yield and quality selection. Overall genetic gain in forage yield of bromegrass has been low, but genetic improvement in forage yield of smooth bromegrass (Bromus inermis Leyss) is somewhat higher than that of meadow bromegrass (Bromus riparius Rehm). This low genetic gain in bromegrass yield is due to a few factors such as its genetic complexity, lack of long-term breeding effort, and inadequate plant adaptation to changing climate. Studies examining the impacts of global climate change on bromegrass species show that global warming, heat stress, and drought have negative effects on forage yield. A number of useful physiological traits have been identified for genetic improvement to minimize yield loss. Available reports suggest that high-throughput imaging phenotyping techniques, including visual and infrared thermal imaging, imaging hyperspectral spectroscopy, and imaging chlorophyll fluorescence, are capable of capturing images of morphological, physiological, and biochemical traits related to plant growth, yield, and adaptation to abiotic stresses at different scales of organization. The more complex traits such as photosynthetic radiation-use efficiency, water-use efficiency, and nitrogen-use efficiency can be effectively assessed by utilizing combinations of imaging hyperspectral spectroscopy, infrared thermal imaging, and imaging chlorophyll fluorescence techniques in a breeding program. Genomic selection has been applied in the breeding of forage species and the applications show its potential in high ploidy, outcrossing species like bromegrass to improve the accuracy of parental selection and improve

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Application of Remote Sensing for Phenotyping Tar Spot Complex Resistance in Maize

Cited by 33 publications

References 51 publications

Beat the stress: breeding for climate resilience in maize for the tropical rainfed environments

Beat the stress: breeding for climate resilience in maize for the tropical rainfed environments

Estimation of Maize (Zea mays L.) Yield Per Harvest Area: Appropriate Methods

Advancing Bromegrass Breeding Through Imaging Phenotyping and Genomic Selection: A Review

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