High‐throughput phenotyping of canopy height in cool‐season crops using sensing techniques

2021 ◽  
Author(s):  
Chongyuan Zhang ◽  
Wilson A. Craine ◽  
Rebecca J. McGee ◽  
George J. Vandemark ◽  
James B. Davis ◽  
...  
Keyword(s):  
High Throughput ◽  
Canopy Height ◽  
Cool Season ◽  
High Throughput Phenotyping

scholarly journals High-Throughput Phenotyping of Indirect Traits for Early-Stage Selection in Sugarcane Breeding

2019 ◽  
Vol 11 (24) ◽  
pp. 2952 ◽  
Author(s):  
Sijesh Natarajan ◽  
Jayampathi Basnayake ◽  
Xianming Wei ◽  
Prakash Lakshmanan
Keyword(s):  
High Throughput ◽  
Early Stage ◽  
Selection Index ◽  
Canopy Cover ◽  
Indirect Selection ◽  
Canopy Height ◽  
Pure Stand ◽  
Single Row ◽  
Sugarcane Breeding ◽  
High Throughput Phenotyping

One of the major limitations for sugarcane genetic improvement is the low heritability of yield in the early stages of breeding, mainly due to confounding inter-plot competition effects. In this study, we investigate an indirect selection index (Si), developed based on traits correlated to yield (indirect traits) that were measured using an unmanned aerial vehicle (UAV), to improve clonal assessment in early stages of sugarcane breeding. A single-row early-stage clonal assessment trial, involving 2134 progenies derived from 245 crosses, and a multi-row experiment representative of pure-stand conditions, with an unrelated population of 40 genotypes, were used in this study. Both experiments were screened at several stages using visual, multispectral, and thermal sensors mounted on a UAV for indirect traits, including canopy cover, canopy height, canopy temperature, and normalised difference vegetation index (NDVI). To construct the indirect selection index, phenotypic and genotypic variance-covariances were estimated in the single-row and multi-row experiment, respectively. Clonal selection from the indirect selection index was compared to single-row yield-based selection. Ground observations of stalk number and plant height at six months after planting made from a subset of 75 clones within the single-row experiment were highly correlated to canopy cover (rg = 0.72) and canopy height (rg = 0.69), respectively. The indirect traits had high heritability and strong genetic correlation with cane yield in both the single-row and multi-row experiments. Only 45% of the clones were common between the indirect selection index and single-row yield based selection, and the expected efficiency of correlated response to selection for pure-stand yield based on indirect traits (44%–73%) was higher than that based on single-row yield (45%). These results highlight the potential of high-throughput phenotyping of indirect traits combined in an indirect selection index for improving early-stage clonal selections in sugarcane breeding.

scholarly journals Combining High-Throughput Phenotyping with Overall Growth Measurements of Indica Rice (Oryza Sativa L Spp. Indica) Cultivars over the Whole Life Cycle

2021 ◽  
Author(s):  
Cattarin Theerawitaya ◽  
Cattleya Chutteang ◽  
Anuruck Arunyanark ◽  
Narubodin Kwangern ◽  
Nattapol Rachsapa ◽  
...  
Keyword(s):  
Life Cycle ◽  
Leaf Area ◽  
High Throughput ◽  
Positive Relationship ◽  
Canopy Height ◽  
Area Measurement ◽  
Rice Cultivars ◽  
High Throughput Phenotyping ◽  
Whole Life Cycle ◽  
Non Destructive

Abstract Background: High-throughput phenotyping systems containing non-destructive and non-invasive characterizations of phenotypic traits throughout the whole life cycle of plant development have prevailed over the conventional method. The aim of this investigation was to evaluate the phenotypic characteristics of indica rice genotypes using RGB high-throughput phenotyping over the whole life cycle in relation to biomass and yield components. Results: Plant canopy width, canopy height and leaf area values of the rice cultivars RD41, Pathumthani1 (PT1), Homchonlasit, IR64, Riceberry and RD43 were measured using RGB imagery estimation together with actual measurements at 45, 60, 75, 90, 105 and 120 DAP. Canopy width and canopy height values obtained from actual measurements were linearly related to RGB-estimated values in all rice cultivars with r = 0.87-0.93 and r = 0.90-0.99, respectively. Interestingly, a positive relationship between plant projected area from RGB imagery and leaf area measurement was observed, especially at the vegetative stage (r = 0.93- 0.99). At harvest, a positive relationship between aboveground biomass and total yield was also found (R2 = 0.44). Conclusion: The agronomical traits and plant characterizations of RD41, PT1, Homchonlasit, IR64, Riceberry and RD43 were validated over the whole life cycle of rice crops in the present investigation. Based on this study, we confirm that high-throughput phenotyping data collection should overcome conventional measurements due to its non-destructive, rapid, and automated production of big data and high accuracy in indica rice crops.

Towards high-throughput phenotyping of complex patterned behaviors: Lessons from mouse self-grooming

2011 ◽  
Author(s):  
E. Kyzar ◽  
S. Gaikwad ◽  
M. Pham ◽  
J. Green ◽  
A. Roth ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Phenotyping

scholarly journals High-throughput phenotyping: breaking through the bottleneck in future crop breeding

2021 ◽  
Author(s):  
Peng Song ◽  
Jinglu Wang ◽  
Xinyu Guo ◽  
Wanneng Yang ◽  
Chunjiang Zhao
Keyword(s):  
High Throughput ◽  
Crop Breeding ◽  
High Throughput Phenotyping

scholarly journals High-Throughput Phenotyping Methods for Breeding Drought-Tolerant Crops

2021 ◽  
Vol 22 (15) ◽  
pp. 8266
Author(s):  
Minsu Kim ◽  
Chaewon Lee ◽  
Subin Hong ◽  
Song Lim Kim ◽  
Jeong-Ho Baek ◽  
...  
Keyword(s):  
Drought Stress ◽  
High Throughput ◽  
Large Scale ◽  
Crop Yields ◽  
Plant Traits ◽  
Rapid Development ◽  
Plant Responses ◽  
Phenotypic Data ◽  
Agricultural Technologies ◽  
High Throughput Phenotyping

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.

scholarly journals High-throughput phenotyping of two plant-size traits of Eucalyptus species using neural networks

2021 ◽  
Author(s):  
Marcus Vinicius Vieira Borges ◽  
Janielle de Oliveira Garcia ◽  
Tays Silva Batista ◽  
Alexsandra Nogueira Martins Silva ◽  
Fabio Henrique Rojo Baio ◽  
...  
Keyword(s):  
Neural Networks ◽  
High Throughput ◽  
Mean Squared Error ◽  
Vegetation Indices ◽  
Plant Size ◽  
Eucalyptus Species ◽  
Forest Inventories ◽  
Spectral Bands ◽  
High Throughput Phenotyping ◽  
Input Variables

AbstractIn forest modeling to estimate the volume of wood, artificial intelligence has been shown to be quite efficient, especially using artificial neural networks (ANNs). Here we tested whether diameter at breast height (DBH) and the total plant height (Ht) of eucalyptus can be predicted at the stand level using spectral bands measured by an unmanned aerial vehicle (UAV) multispectral sensor and vegetation indices. To do so, using the data obtained by the UAV as input variables, we tested different configurations (number of hidden layers and number of neurons in each layer) of ANNs for predicting DBH and Ht at stand level for different Eucalyptus species. The experimental design was randomized blocks with four replicates, with 20 trees in each experimental plot. The treatments comprised five Eucalyptus species (E. camaldulensis, E. uroplylla, E. saligna, E. grandis, and E. urograndis) and Corymbria citriodora. DBH and Ht for each plot at the stand level were measured seven times in separate overflights by the UAV, so that the multispectral sensor could obtain spectral bands to calculate vegetation indices (VIs). ANNs were then constructed using spectral bands and VIs as input layers, in addition to the categorical variable (species), to predict DBH and Ht at the stand level simultaneously. This report represents one of the first applications of high-throughput phenotyping for plant size traits in Eucalyptus species. In general, ANNs containing three hidden layers gave better statistical performance (higher estimated r, lower estimated root mean squared error–RMSE) due to their greater capacity for self-learning. Among these ANNs, the best contained eight neurons in the first layer, seven in the second, and five in the third (8 − 7 − 5). The results reported here reveal the potential of using the generated models to perform accurate forest inventories based on spectral bands and VIs obtained with a UAV multispectral sensor and ANNs, reducing labor and time.

scholarly journals High-throughput phenotyping (HTP) identifies seedling root traits linked to variation in seed yield and nutrient capture in field-grown oilseed rape (Brassica napusL.)

2016 ◽  
Vol 118 (4) ◽  
pp. 655-665 ◽  
Author(s):  
C. L. Thomas ◽  
N. S. Graham ◽  
R. Hayden ◽  
M. C. Meacham ◽  
K. Neugebauer ◽  
...  
Keyword(s):  
Oilseed Rape ◽  
Seed Yield ◽  
High Throughput ◽  
Root Traits ◽  
Seedling Root ◽  
High Throughput Phenotyping
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