scholarly journals Identification of the QTL-allele System Underlying Two High-Throughput Physiological Traits in the Chinese Soybean Germplasm Population

2021 ◽  
Vol 12 ◽  
Author(s):  
Lei Wang ◽  
Fangdong Liu ◽  
Xiaoshuai Hao ◽  
Wubin Wang ◽  
Guangnan Xing ◽  
...  
Keyword(s):  
High Throughput ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Genome Wide Association Study ◽  
Agronomic Traits ◽  
Block Design ◽  
Physiological Traits ◽  
Growth And Yield ◽  
Genetic Changes ◽  
Soybean Germplasm

The QTL-allele system underlying two spectral reflectance physiological traits, NDVI (normalized difference vegetation index) and CHL (chlorophyll index), related to plant growth and yield was studied in the Chinese soybean germplasm population (CSGP), which consisted of 341 wild accessions (WA), farmer landraces (LR), and released cultivars (RC). Samples were evaluated in the Photosynthetic System II imaging platform at Nanjing Agricultural University. The NDVI and CHL data were obtained from hyperspectral reflectance images in a randomized incomplete block design experiment with two replicates. The NDVI and CHL ranged from 0.05–0.18 and 1.20–4.78, had averages of 0.11 and 3.57, and had heritabilities of 78.3% and 69.2%, respectively; the values of NDVI and CHL were both significantly higher in LR and RC than in WA. Using the RTM-GWAS (restricted two-stage multi-locus genome-wide association study) method, 38 and 32 QTLs with 89 and 82 alleles and 2–4 and 2–6 alleles per locus were identified for NDVI and CHL, respectively, which explained 48.36% and 51.35% of the phenotypic variation for NDVI and CHL, respectively. The QTL-allele matrices were established and separated into WA, LR, and RC submatrices. From WA to LR + RC, 4 alleles and 2 new loci emerged, and 1 allele was excluded for NDVI, whereas 6 alleles emerged, and no alleles were excluded, in LR + RC for CHL. Recombination was the major motivation of evolutionary differences. For NDVI and CHL, 39 and 32 candidate genes were annotated and assigned to GO groups, respectively, indicating a complex gene network. The NDVI and CHL were upstream traits that were relatively conservative in their genetic changes compared with those of downstream agronomic traits. High-throughput phenotyping integrated with RTM-GWAS provides an efficient procedure for studying the population genetics of traits.

scholarly journals Identification of QTL hotspots affecting agronomic traits and high-throughput vegetation indices in rainfed wheat

2021 ◽  
Author(s):  
Ruben Rufo ◽  
Andrea Lopez ◽  
Marta S. Lopes ◽  
Joaquim Bellvert ◽  
Jose Miguel Soriano
Keyword(s):  
Abiotic Stress ◽  
Grain Yield ◽  
Candidate Gene ◽  
High Throughput ◽  
Complex Traits ◽  
Vegetation Index ◽  
Genome Wide Association Study ◽  
Agronomic Traits ◽  
Wheat Breeding ◽  
A Genome

Understanding the genetic basis of agronomic traits is essential for wheat breeding programmes to develop new cultivars with enhanced grain yield under climate change conditions. The use of high-throughput phenotyping (HTP) technologies for the assessment of agronomic performance through drought-adaptive traits opens new possibilities in plant breeding. HTP together with a genome-wide association study (GWAS) mapping approach can become a useful method to dissect the genetic control of complex traits in wheat to enhance grain yield under drought stress. This study aimed to identify molecular markers associated with agronomic and remotely sensed vegetation index (VI)-related traits under rainfed conditions in bread wheat and to use an in silico candidate gene (CG) approach to search for upregulated CGs under abiotic stress. The plant material consisted of 170 landraces and 184 modern cultivars from the Mediterranean basin that were phenotyped for agronomic and VI traits derived from multispectral images over three and two years, respectively. GWAS identified 2579 marker-trait associations (MTAs). The QTL overview index statistic detected 11 QTL hotspots involving more than one trait in at least two years. A candidate gene analysis detected 12 CGs upregulated under abiotic stress in 6 QTL hotspots. The current study highlights the utility of VI to identify chromosome regions that contribute to yield and drought tolerance under rainfed Mediterranean conditions.

scholarly journals Validation of UAV-based alfalfa biomass predictability using photogrammetry with fully automatic plot segmentation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhou Tang ◽  
Atit Parajuli ◽  
Chunpeng James Chen ◽  
Yang Hu ◽  
Samuel Revolinski ◽  
...  
Keyword(s):  
Prediction Model ◽  
High Throughput ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Selection Process ◽  
Forage Legume ◽  
Breeding Programs ◽  
High Throughput Phenotyping ◽  
Fully Automatic ◽  
Uav Images

AbstractAlfalfa is the most widely cultivated forage legume, with approximately 30 million hectares planted worldwide. Genetic improvements in alfalfa have been highly successful in developing cultivars with exceptional winter hardiness and disease resistance traits. However, genetic improvements have been limited for complex economically important traits such as biomass. One of the major bottlenecks is the labor-intensive phenotyping burden for biomass selection. In this study, we employed two alfalfa fields to pave a path to overcome the challenge by using UAV images with fully automatic field plot segmentation for high-throughput phenotyping. The first field was used to develop the prediction model and the second field to validate the predictions. The first and second fields had 808 and 1025 plots, respectively. The first field had three harvests with biomass measured in May, July, and September of 2019. The second had one harvest with biomass measured in September of 2019. These two fields were imaged one day before harvesting with a DJI Phantom 4 pro UAV carrying an additional Sentera multispectral camera. Alfalfa plot images were extracted by GRID software to quantify vegetative area based on the Normalized Difference Vegetation Index. The prediction model developed from the first field explained 50–70% (R Square) of biomass variation in the second field by incorporating four features from UAV images: vegetative area, plant height, Normalized Green–Red Difference Index, and Normalized Difference Red Edge Index. This result suggests that UAV-based, high-throughput phenotyping could be used to improve the efficiency of the biomass selection process in alfalfa breeding programs.

scholarly journals The Effect of Irrigation Intervals on the Growth and Yield of Quinoa Crop and Its Components

2017 ◽  
Vol 9 (9) ◽  
pp. 182
Author(s):  
Abdullah M. Algosaibi ◽  
Ayman E. Badran ◽  
Abdulrahman M. Almadini ◽  
Mohammed M. El-Garawany
Keyword(s):  
Irrigation Water ◽  
Harvest Index ◽  
Agronomic Traits ◽  
Block Design ◽  
Irrigation Management ◽  
Growth Yield ◽  
Moisture Stress ◽  
Growth And Yield ◽  
Growth Stages ◽  
Index Number

This experiment was conducted to study the effect of irrigation intervals on growth, yield and its components and some of the chemical characteristics of the soil after the harvest of quinoa (Chenopodium quinoa willd) plant. Three treatments were used as follow: T1 (twice irrigation every week, which is the common in the region), T2 (once irrigation every week) and T3 (twice irrigation every two weeks) using in a randomized complete block design with four replicates. The crop coefficient (Kc) value differed according to the stage of growth where the results showed that the T2 treatment gave the highest mean in all the studied traits followed by the T3 treatment in all traits except the number of seed/m2. The results also confirmed that the increase in water reduced the agronomic traits such as harvest index, number of seeds and yield of seeds and straw/m2. Also it showed that the pH values in soils were not significantly affected by irrigation, while Ec significantly affected. Correlation coefficient was negative with the most traits and low with the number of grain (0.34) under overall studied treatments which confirms that quinoa is a plant that needs limited amounts of irrigation water. On the other hand there was positive strong correlation between the harvest index and grain yield (0.92). The results showed that moisture stress treatments increased the concentration of the ionic, NH4-N and NO3-N significantly compared to soils which do not have moisture stress (T1, T2). We assume that the development based on Kc during growth-stages helps in irrigation management and provides precise water applications for quinoa plant. These results indicate that the water requirements of quinoa plant are limited and that quinoa plant growth is not affected by the lack of irrigation water on the crop and its qualities.

scholarly journals Effect of Seed Distribution and Population on Maize (Zea maysL.) Grain Yield

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Bee Khim Chim ◽  
Peter Omara ◽  
Natasha Macnack ◽  
Jeremiah Mullock ◽  
Sulochana Dhital ◽  
...  
Keyword(s):  
Grain Yield ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Block Design ◽  
N Uptake ◽  
Plant Spacing ◽  
Randomized Complete Block Design ◽  
Seed Distribution ◽  
Treatment Structure ◽  
Number Of Seeds

Maize planting is normally accomplished by hand in the developing world where two or more seeds are placed per hill with a heterogeneous plant spacing and density. To understand the interaction between seed distribution and distance between hills, experiments were established in 2012 and 2013 at Lake Carl Blackwell (LCB) and Efaw Agronomy Research Stations, near Stillwater, OK. A randomized complete block design was used with three replications and 9 treatments and a factorial treatment structure of 1, 2, and 3 seeds per hill using interrow spacing of 0.16, 0.32, and 0.48 m. Data for normalized difference vegetation index (NDVI), intercepted photosynthetically active radiation (IPAR), grain yield, and grain N uptake were collected. Results showed that, on average, NDVI and IPAR increased with number of seeds per hill and decreased with increasing plant spacing. In three of four site-years, planting 1 or 2 seeds per hill, 0.16 m apart, increased grain yield and N uptake. Over sites, planting 1 seed, every 0.16 m, increased yields by an average of 1.15 Mg ha−1(range: 0.33 to 2.46 Mg ha−1) when compared to the farmer practice of placing 2 to 3 seeds per hill, every 0.48 m.

scholarly journals Genome-Wide Detection of SNP Markers Associated with Four Physiological Traits in Groundnut (Arachis hypogaea L.) Mini Core Collection

Agronomy ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 192 ◽  
Author(s):  
Abdulwahab S. Shaibu ◽  
Clay Sneller ◽  
Babu N. Motagi ◽  
Jackline Chepkoech ◽  
Mercy Chepngetich ◽  
...  
Keyword(s):  
Core Collection ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Canopy Temperature ◽  
Snp Markers ◽  
Physiological Traits ◽  
Area Index ◽  
Trait Association ◽  
Mini Core Collection ◽  
Genome Wide

In order to integrate genomics in breeding and development of drought-tolerant groundnut genotypes, identification of genomic regions/genetic markers for drought surrogate traits is essential. We used 3249 diversity array technology sequencing (DArTSeq) markers for a genetic analysis of 125 ICRISAT groundnut mini core collection evaluated in 2015 and 2017 for genome-wide marker-trait association for some physiological traits and to determine the magnitude of linkage disequilibrium (LD). Marker-trait association (MTA) analysis, probability values, and percent variation modelled by the markers were calculated using the GAPIT package via the KDCompute interface. The LD analysis showed that about 36% of loci pairs were in significant LD (p < 0.05 and r2 > 0.2) and 3.14% of the pairs were in complete LD. The MTAs studies revealed 20 significant MTAs (p < 0.001) with 11 markers. Four MTAs were identified for leaf area index, 13 for canopy temperature, one for chlorophyll content and two for normalized difference vegetation index. The markers explained 20.8% to 6.6% of the phenotypic variation observed. Most of the MTAs identified on the A subgenome were also identified on the respective homeologous chromosome on the B subgenome. This could be due to a common ancestor of the A and B genome which explains the linkage detected between markers lying on different chromosomes. The markers identified in this study can serve as useful genomic resources to initiate marker-assisted selection and trait introgression of groundnut for drought tolerance after further validation.

scholarly journals Prediction of Maize Yields from In-Season GreenSeeker Normalized Difference Vegetation Index and Dry Biomass as Influenced by Different Nutrient Combinations

2020 ◽  
Vol 13 (1) ◽  
pp. 165
Author(s):  
Hillary M. O. Otieno ◽  
George N. Chemining’wa ◽  
Shamie Zingore
Keyword(s):  
Grain Yield ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Nutrient Management ◽  
Fertilizer Application ◽  
Growth And Yield ◽  
Yield Prediction ◽  
Maize Productivity ◽  
Dry Biomass ◽  
The Right

To mitigate low maize productivity, improve on-farm planning and policy implementation, the right fertilizer combinations and yield forecasting should be prioritized. Therefore, this research aimed at assessing the effect of applying different nutrient combinations on maize growth and yield and in-season grain yield prediction from biomass and normalized difference vegetation index (NDVI) readings. The research was done in Embu and Kirinyaga counties, in Central Kenya. Nutrient combinations tested were P+K, N+K, N+P, N+P+K, and N+P+K+Ca+Mg+Zn+B+S. The results showed consistently lowest and highest NDVI reading, dry biomass, and grain yields due to P+K and N+P+K+Ca+Mg+Zn+B+S treatments, respectively. Positive NDVI responses of 56%, 14%, 15%, and 15% were recorded with N, P, K, and combined Ca+Mg+Zn+B+S, respectively. These nutrients, in the same order, recorded 54%, 20%, 8%, and 18% positive responses with biomass. The GreenSeeker NDVI reading with grain yield and aboveground dry biomass with grain yield recorded R2 ranging from 0.23-0.53 and 0.30-0.61 (in Embu), and 0.31-0.64 and 0.30-0.50 (in Kirinyaga), respectively. When data were pooled, the prediction strength increased, reaching a maximum of 67% and 58% with NDVI and biomass, respectively. Yield prediction was even more robust when the independent variables were combined through multiple linear model at both 85 and 105 days after emergence. From this research, it is evident that the effects of balanced fertilizer application are detectable from NDVI readings&mdash;providing a tool for tracking and monitoring nutrient management effects&mdash;not just from the nitrogen perspective as commonly studied but from the combined effects of multiple nutrients. Also, grain yield could be accurately predicted early before harvesting by combining NDVI and biomass yields.

scholarly journals Assessment of Juvenile Growth and Yield Relationship Among Dwarf Cashew Types in Ghana

2020 ◽  
Vol 12 (10) ◽  
pp. 116
Author(s):  
A. M. Dadzie ◽  
P. K. K. Adu-Gyamfi ◽  
A. Akpertey ◽  
A. Ofori ◽  
S. Y. Opoku ◽  
...  
Keyword(s):  
Agronomic Traits ◽  
Environmental Influence ◽  
Block Design ◽  
Growth And Yield ◽  
Agronomic Performance ◽  
Juvenile Growth ◽  
Genetic Advance ◽  
Randomized Complete Block Design ◽  
High Heritability ◽  
The Relationship

Cashew (Anacardium occidentale L.) is an important tropical cash crop cultivated in Ghana. It provides livelihood for about 200,000 people and contributes 6.1% to Ghana&rsquo;s gross domestic product (GDP). Four Brazilian dwarf accessions were introduced to improve nut yield. Objectives of this study were to (1) assess the agronomic performance of the accessions across two contrasting ecologies, (2) determine environmental influence on juvenile growth, (3) determine the relationship between early vegetative growth and yield and (4) explore heritability and genetic advance for the measured agronomic traits. The experiment was laid out in a randomized complete block design with 3 replications. Results revealed significant (p &lt; 0.05) environmental influence on growth and yield of cashew. Transitional savanna agro-ecology is more suitable for cashew growth and development. Crop year, location and crop year &times; location interactions also influenced most of the agronomic traits. Early growth characteristics alone were not enough to predict yield. Genotype B2 ranked highest yielding across the agro-ecologies. Moderate to high heritability and genetic advance estimates were observed for nut yield, plant height and girth, an indication of variability among accessions needed for cashew improvement in Ghana.

scholarly journals Evaluation of Organic Camelina Crop Under Different Tillage Systems and Fertilization Types Using Proximal Remote Sensing

2020 ◽  
Vol 77 (1) ◽  
pp. 1
Author(s):  
Foteini ANGELOPOULOU ◽  
Evangelos ANASTASIOU ◽  
Spyros FOUNTAS ◽  
Dimitrios BILALIS
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Crop Growth ◽  
Growth And Yield ◽  
Tillage Systems ◽  
Minimum Tillage ◽  
Spectral Vegetation Indices ◽  
Crop Parameters

A field experiment was conducted in Southern Greece to assess Normalized Difference Vegetation Index (NDVI) and Red-Edge Normalized Difference Vegetation Index (NDRE) in estimating Camelina’s crop growth and yield parameters under different tillage systems (conventional and minimum tillage) and organic fertilization types (compost, vermicompost and untreated control). A proximal canopy sensor was used to measure the aforementioned Spectral Vegetation Indices (SVIs) at different days after sowing (DAS). Camelina presented the highest values of NDVI and NDRE under compost fertilization (0.63 and 0.22 accordingly) and minimum tillage system (0.50 and 0.18 accordingly). Additionally, the highest correlations between the measured crop parameters and NDVI, NDRE were achieved at leaf development to early flowering stage. Moreover, NDRE presented the highest correlation with seed yield (R2=0.60, p<0.05) and thus it is suggested for estimating Camelina’s productivity instead of NDVI. Finally, further research is needed for adopting the use of remote sensing technologies on predicting Camelina’s crop growth and yield.

scholarly journals Dissecting Bread Wheat Heterosis through the Integration of Agronomic and Physiological Traits

Biology ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 907
Author(s):  
Kevin Gimenez ◽  
Pierre Blanc ◽  
Odile Argillier ◽  
Jean-Baptiste Pierre ◽  
Jacques Le Le Gouis ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Agronomic Traits ◽  
Wheat Yield ◽  
Grain Filling ◽  
Kernel Weight ◽  
Hybrid Vigor ◽  
Delayed Senescence ◽  
Yield Increase ◽  
Wheat Hybrids

To meet the challenge of feeding almost 10 billion people by 2050, wheat yield has to double by 2050. However, over the past 20 years, yield increase has slowed down and even stagnated in the main producing countries. Following the example of maize, hybrids have been suggested as a solution to overcome yield stagnation in wheat. However, wheat heterosis is still limited and poorly understood. Gaining a better understanding of hybrid vigor holds the key to breed for better varieties. To this aim, we have developed and phenotyped for physiological and agronomic traits an incomplete factorial design consisting of 91 hybrids and their nineteen female and sixteen male parents. Monitoring the plant development with normalized difference vegetation index revealed that 89% of the hybrids including the five higher yielding hybrids had a longer grain filling phase with a delayed senescence that results in larger grain size. This average increase of 7.7% in thousand kernel weight translated to a positive mid-parent heterosis for grain yield for 86% of hybrids. In addition, hybrids displayed a positive grain protein deviation leading to a +4.7% heterosis in protein yield. These results shed light on the physiological bases underlying yield heterosis in wheat, paving new ways to breed for better wheat hybrids.

scholarly journals CANOPY REFLECTANCE MEASUREMENTS USED TO ESTIMATE LATE BLIGHT (PHYTOPHTHORA INFESTANS) INFLUENCE ON POTATO YIELD CANOPY REFLECTANCE MEASUREMENTS USED TO ESTIMATE LATE BLIGHT (PHYTOPHTHORA INFESTANS) INFLUENCE ON POTATO YIELD

2020 ◽  
Vol 13 ◽  
pp. 21-27
Author(s):  
Manuela Hermeziu
Keyword(s):  
Late Blight ◽  
Phytophthora Infestans ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Field Experiments ◽  
Block Design ◽  
Potato Yield ◽  
Planting Density ◽  
Canopy Reflectance ◽  
Reflectance Measurements

"The present study was conducted to investigate potato late blight (Phytophtora infestans) influence on leaf chlorophyll level using datasets extracted from multispectral data captured at the canopy level. Field experiments were carried out to the National Institute of Research and Development for Potato and Sugar Beet Brasov, Romania in 2014-2016 period. It was used a complete randomized block design with four replicates, two planting distances between plants on row (25 and 30cm) and different fungicides, control technologies. Normalized Difference Vegetation Index (NDVI) was introduced to achieve a spectral vegetation index that can separate the vegetation from the uncovered ground. It is defined as the ratio between the infrared bands-red differences and sum them. Due to the different growth conditions, the effects of resulting variants from combinations of factors -varieties-planting density-late blight control technology-on the tubers yield have manifested with different intensity. In two of three years, the average NDVI value of plants grown at a density of 53.3 thousands hill/ha was significantly lower than the values determined at a density of 44.4 thousands hill/ha (NDVI 0.817 compared to 0.859 in 2014 and 0.905 compared to 0.895 in 2015). The correlation between the average values of NDVI yields and tubers were positive."

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