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Kanaabi M, Namakula FB, Nuwamanya E, Kayondo IS, Muhumuza N, Wembabazi E, Iragaba P, Nandudu L, Nanyonjo AR, Baguma J, Esuma W, Ozimati A, Settumba M, Alicai T, Ibanda A, Kawuki RS. Rapid analysis of hydrogen cyanide in fresh cassava roots using NIRSand machine learning algorithms: Meeting end user demand for low cyanogenic cassava. THE PLANT GENOME 2024; 17:e20403. [PMID: 37938872 DOI: 10.1002/tpg2.20403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 10/02/2023] [Accepted: 10/07/2023] [Indexed: 11/10/2023]
Abstract
This study focuses on meeting end-users' demand for cassava (Manihot esculenta Crantz) varieties with low cyanogenic potential (hydrogen cyanide potential [HCN]) by using near-infrared spectrometry (NIRS). This technology provides a fast, accurate, and reliable way to determine sample constituents with minimal sample preparation. The study aims to evaluate the effectiveness of machine learning (ML) algorithms such as logistic regression (LR), support vector machine (SVM), and partial least squares discriminant analysis (PLS-DA) in distinguishing between low and high HCN accessions. Low HCN accessions averagely scored 1-5.9, while high HCN accessions scored 6-9 on a 1-9 categorical scale. The researchers used 1164 root samples to test different NIRS prediction models and six spectral pretreatments. The wavelengths 961, 1165, 1403-1505, 1913-1981, and 2491 nm were influential in discrimination of low and high HCN accessions. Using selected wavelengths, LR achieved 100% classification accuracy and PLS-DA achieved 99% classification accuracy. Using the full spectrum, the best model for discriminating low and high HCN accessions was the PLS-DA combined with standard normal variate with second derivative, which produced an accuracy of 99.6%. The SVM and LR had moderate classification accuracies of 75% and 74%, respectively. This study demonstrates that NIRS coupled with ML algorithms can be used to identify low and high HCN accessions, which can help cassava breeding programs to select for low HCN accessions.
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Affiliation(s)
- Michael Kanaabi
- School of Agricultural Sciences, Makerere University, Kampala, Uganda
- National Crops Resources Research Institute (NaCRRI), Kampala, Uganda
| | | | - Ephraim Nuwamanya
- School of Agricultural Sciences, Makerere University, Kampala, Uganda
- National Crops Resources Research Institute (NaCRRI), Kampala, Uganda
| | - Ismail S Kayondo
- International Institute for Tropical Agriculture (IITA), Ibadan, Nigeria
| | - Nicholas Muhumuza
- School of Agricultural Sciences, Makerere University, Kampala, Uganda
- National Crops Resources Research Institute (NaCRRI), Kampala, Uganda
| | - Enoch Wembabazi
- National Crops Resources Research Institute (NaCRRI), Kampala, Uganda
| | - Paula Iragaba
- National Crops Resources Research Institute (NaCRRI), Kampala, Uganda
| | - Leah Nandudu
- National Crops Resources Research Institute (NaCRRI), Kampala, Uganda
- Plant Breeding and Genetics section, Cornell University, Ithaca, New York, USA
| | | | - Julius Baguma
- National Crops Resources Research Institute (NaCRRI), Kampala, Uganda
| | - Williams Esuma
- National Crops Resources Research Institute (NaCRRI), Kampala, Uganda
| | - Alfred Ozimati
- School of Agricultural Sciences, Makerere University, Kampala, Uganda
- National Crops Resources Research Institute (NaCRRI), Kampala, Uganda
| | - Mukasa Settumba
- School of Agricultural Sciences, Makerere University, Kampala, Uganda
| | - Titus Alicai
- National Crops Resources Research Institute (NaCRRI), Kampala, Uganda
| | - Angele Ibanda
- National Crops Resources Research Institute (NaCRRI), Kampala, Uganda
| | - Robert S Kawuki
- National Crops Resources Research Institute (NaCRRI), Kampala, Uganda
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Zhu L, Li G, Guo D, Li X, Xue M, Jiang H, Yan Q, Xie F, Ning X, Xie L. Genome-wide association study and genomic selection of flax powdery mildew in Xinjiang Province. FRONTIERS IN PLANT SCIENCE 2024; 15:1403276. [PMID: 38863531 PMCID: PMC11165360 DOI: 10.3389/fpls.2024.1403276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Accepted: 05/10/2024] [Indexed: 06/13/2024]
Abstract
Flax powdery mildew (PM), caused by Oidium lini, is a globally distributed fungal disease of flax, and seriously impairs its yield and quality. To data, only three resistance genes and a few putative quantitative trait loci (QTL) have been reported for flax PM resistance. To dissect the resistance mechanism against PM and identify resistant genetic regions, based on four years of phenotypic datasets (2017, 2019 to 2021), a genome-wide association study (GWAS) was performed on 200 flax core accessions using 674,074 SNPs and 7 models. A total of 434 unique quantitative trait nucleotides (QTNs) associated with 331 QTL were detected. Sixty-four loci shared in at least two datasets were found to be significant in haplotype analyses, and 20 of these sites were shared by multiple models. Simultaneously, a large-effect locus (qDI 11.2) was detected repeatedly, which was present in the mapping study of flax pasmo resistance loci. Oil flax had more QTL with positive-effect or favorable alleles (PQTL) and showed higher PM resistance than fiber flax, indicating that effects of these QTL were mainly additive. Furthermore, an excellent resistant variety C120 was identified and can be used to promote planting. Based on 331 QTLs identified through GWAS and the statistical model GBLUP, a genomic selection (GS) model related to flax PM resistance was constructed, and the prediction accuracy rate was 0.96. Our results provide valuable insights into the genetic basis of resistance and contribute to the advancement of breeding programs.
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Affiliation(s)
- Leilei Zhu
- Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, Urumqi, China
| | - Gongze Li
- Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, Urumqi, China
- State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Zhengzhou, China
| | - Dongliang Guo
- Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, Urumqi, China
| | - Xiao Li
- Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, Urumqi, China
- Department of Basic Medicine, Xinjiang Second Medical College, Karamay, China
| | - Min Xue
- Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, Urumqi, China
| | - Haixia Jiang
- Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, Urumqi, China
- Key Laboratory of Plant Stress Biology in Arid Land, College of Life Science, Xinjiang Normal University, Urumqi, China
| | - Qingcheng Yan
- Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, Urumqi, China
| | - Fang Xie
- Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, Urumqi, China
| | - Xuefei Ning
- Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, Urumqi, China
| | - Liqiong Xie
- Xinjiang Key Laboratory of Biological Resources and Genetic Engineering, College of Life Science and Technology, Xinjiang University, Urumqi, China
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Baguma JK, Mukasa SB, Nuwamanya E, Alicai T, Omongo CA, Ochwo-Ssemakula M, Ozimati A, Esuma W, Kanaabi M, Wembabazi E, Baguma Y, Kawuki RS. Identification of Genomic Regions for Traits Associated with Flowering in Cassava ( Manihot esculenta Crantz). PLANTS (BASEL, SWITZERLAND) 2024; 13:796. [PMID: 38592820 PMCID: PMC10974989 DOI: 10.3390/plants13060796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 01/25/2024] [Accepted: 01/26/2024] [Indexed: 04/11/2024]
Abstract
Flowering in cassava (Manihot esculenta Crantz) is crucial for the generation of botanical seed for breeding. However, genotypes preferred by most farmers are erect and poor at flowering or never flower. To elucidate the genetic basis of flowering, 293 diverse cassava accessions were evaluated for flowering-associated traits at two locations and seasons in Uganda. Genotyping using the Diversity Array Technology Pty Ltd. (DArTseq) platform identified 24,040 single-nucleotide polymorphisms (SNPs) distributed on the 18 cassava chromosomes. Population structure analysis using principal components (PCs) and kinships showed three clusters; the first five PCs accounted for 49.2% of the observed genetic variation. Linkage disequilibrium (LD) estimation averaged 0.32 at a distance of ~2850 kb (kilo base pairs). Polymorphism information content (PIC) and minor allele frequency (MAF) were 0.25 and 0.23, respectively. A genome-wide association study (GWAS) analysis uncovered 53 significant marker-trait associations (MTAs) with flowering-associated traits involving 27 loci. Two loci, SNPs S5_29309724 and S15_11747301, were associated with all the traits. Using five of the 27 SNPs with a Phenotype_Variance_Explained (PVE) ≥ 5%, 44 candidate genes were identified in the peak SNP sites located within 50 kb upstream or downstream, with most associated with branching traits. Eight of the genes, orthologous to Arabidopsis and other plant species, had known functional annotations related to flowering, e.g., eukaryotic translation initiation factor and myb family transcription factor. This study identified genomic regions associated with flowering-associated traits in cassava, and the identified SNPs can be useful in marker-assisted selection to overcome hybridization challenges, like unsynchronized flowering, and candidate gene validation.
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Affiliation(s)
- Julius K. Baguma
- School of Agricultural Sciences, Makerere University, Kampala P.O. Box 7062, Uganda; (S.B.M.); (E.N.); (M.O.-S.)
- National Crops Resources Research Institute, Namulonge (NaCRRI), Kampala P.O. Box 7084, Uganda; (T.A.); (C.A.O.); (A.O.); (W.E.); (M.K.); (E.W.); (R.S.K.)
| | - Settumba B. Mukasa
- School of Agricultural Sciences, Makerere University, Kampala P.O. Box 7062, Uganda; (S.B.M.); (E.N.); (M.O.-S.)
| | - Ephraim Nuwamanya
- School of Agricultural Sciences, Makerere University, Kampala P.O. Box 7062, Uganda; (S.B.M.); (E.N.); (M.O.-S.)
- National Crops Resources Research Institute, Namulonge (NaCRRI), Kampala P.O. Box 7084, Uganda; (T.A.); (C.A.O.); (A.O.); (W.E.); (M.K.); (E.W.); (R.S.K.)
| | - Titus Alicai
- National Crops Resources Research Institute, Namulonge (NaCRRI), Kampala P.O. Box 7084, Uganda; (T.A.); (C.A.O.); (A.O.); (W.E.); (M.K.); (E.W.); (R.S.K.)
| | - Christopher Abu Omongo
- National Crops Resources Research Institute, Namulonge (NaCRRI), Kampala P.O. Box 7084, Uganda; (T.A.); (C.A.O.); (A.O.); (W.E.); (M.K.); (E.W.); (R.S.K.)
- National Agricultural Research Organisation (NARO), Entebbe P.O. Box 295, Uganda;
| | - Mildred Ochwo-Ssemakula
- School of Agricultural Sciences, Makerere University, Kampala P.O. Box 7062, Uganda; (S.B.M.); (E.N.); (M.O.-S.)
| | - Alfred Ozimati
- National Crops Resources Research Institute, Namulonge (NaCRRI), Kampala P.O. Box 7084, Uganda; (T.A.); (C.A.O.); (A.O.); (W.E.); (M.K.); (E.W.); (R.S.K.)
- School of Biological Sciences, Makerere University, Kampala P.O. Box 7062, Uganda
| | - Williams Esuma
- National Crops Resources Research Institute, Namulonge (NaCRRI), Kampala P.O. Box 7084, Uganda; (T.A.); (C.A.O.); (A.O.); (W.E.); (M.K.); (E.W.); (R.S.K.)
- National Agricultural Research Organisation (NARO), Entebbe P.O. Box 295, Uganda;
| | - Michael Kanaabi
- National Crops Resources Research Institute, Namulonge (NaCRRI), Kampala P.O. Box 7084, Uganda; (T.A.); (C.A.O.); (A.O.); (W.E.); (M.K.); (E.W.); (R.S.K.)
| | - Enoch Wembabazi
- National Crops Resources Research Institute, Namulonge (NaCRRI), Kampala P.O. Box 7084, Uganda; (T.A.); (C.A.O.); (A.O.); (W.E.); (M.K.); (E.W.); (R.S.K.)
| | - Yona Baguma
- National Agricultural Research Organisation (NARO), Entebbe P.O. Box 295, Uganda;
| | - Robert S. Kawuki
- National Crops Resources Research Institute, Namulonge (NaCRRI), Kampala P.O. Box 7084, Uganda; (T.A.); (C.A.O.); (A.O.); (W.E.); (M.K.); (E.W.); (R.S.K.)
- National Agricultural Research Organisation (NARO), Entebbe P.O. Box 295, Uganda;
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Adesokan M, Alamu EO, Fawole S, Maziya-Dixon B. Prediction of functional characteristics of gari (cassava flakes) using near-infrared reflectance spectrometry. Front Chem 2023; 11:1156718. [PMID: 37234202 PMCID: PMC10206270 DOI: 10.3389/fchem.2023.1156718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 05/02/2023] [Indexed: 05/27/2023] Open
Abstract
Gari is a creamy, granular flour obtained from roasting fermented cassava mash. Its preparation involves several unit operations, including fermentation, which is essential in gari production. Fermentation brings about specific biochemical changes in cassava starch due to the actions of lactic acid bacteria. Consequently, it gives rise to organic acids and a significant reduction in the pH. Consumer preferences for gari are influenced by these changes and impact specific functional characteristics, which are often linked to cassava genotypes. Measurement of these functional characteristics is time-consuming and expensive. Therefore, this study aimed to develop high-throughput and less expensive prediction models for water absorption capacity, swelling power, bulk density, and dispersibility using Near-Infrared Reflectance Spectroscopy (NIRS). Gari was produced from 63 cassava genotypes using the standard method developed in the RTB foods project. The prediction model was developed by dividing the gari samples into two sets of 48 samples for calibration and 15 samples as the validation set. The gari samples were transferred into a ring cell cup and scanned on the NIRS machine within the Vis-NIR range of 400-2,498 nm wavelength, though only the NIR range of 800-2,400 nm was used to build the model. Calibration models were developed using partial least regression algorithms after spectra pre-processing. Also, the gari samples were analysed in the laboratory for their functional properties to generate reference data. Results showed an excellent coefficient of determination in calibrations (R2 Cal) of 0.99, 0.97, 0.97, and 0.89 for bulk density, swelling power, dispersibility, and water absorption capacity, respectively. Also, the performances of the prediction models were tested using an independent set of 15 gari samples. A good prediction coefficient (R2 pred) and low standard error of prediction (SEP) was obtained as follows: Bulk density (0.98), Swelling power (0.93), WAC (0.68), Dispersibility (0.65), and solubility index (0.62), respectively. Therefore, NIRS prediction models in this study could provide a rapid screening tool for cassava breeding programs and food scientists to determine the food quality of cassava granular products (Gari).
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Affiliation(s)
- Michael Adesokan
- Food and Nutrition Sciences Laboratory, International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria
| | - Emmanuel Oladeji Alamu
- Food and Nutrition Sciences Laboratory, International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria
- International Institute of Tropical Agriculture, Southern Africa Research and Administration Hub (SARAH) Campus, Lusaka, Zambia
| | - Segun Fawole
- Food and Nutrition Sciences Laboratory, International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria
| | - Busie Maziya-Dixon
- Food and Nutrition Sciences Laboratory, International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria
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Che S, Du G, Zhong X, Mo Z, Wang Z, Mao Y. Quantification of Photosynthetic Pigments in Neopyropia yezoensis Using Hyperspectral Imagery. PLANT PHENOMICS (WASHINGTON, D.C.) 2023; 5:0012. [PMID: 37040513 PMCID: PMC10076050 DOI: 10.34133/plantphenomics.0012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 11/17/2022] [Indexed: 06/19/2023]
Abstract
Phycobilisomes and chlorophyll-a (Chla) play important roles in the photosynthetic physiology of red macroalgae and serve as the primary light-harvesting antennae and reaction center for photosystem II. Neopyropia is an economically important red macroalga widely cultivated in East Asian countries. The contents and ratios of 3 main phycobiliproteins and Chla are visible traits to evaluate its commercial quality. The traditional analytical methods used for measuring these components have several limitations. Therefore, a high-throughput, nondestructive, optical method based on hyperspectral imaging technology was developed for phenotyping the pigments phycoerythrin (PE), phycocyanin (PC), allophycocyanin (APC), and Chla in Neopyropia thalli in this study. The average spectra from the region of interest were collected at wavelengths ranging from 400 to 1000 nm using a hyperspectral camera. Following different preprocessing methods, 2 machine learning methods, partial least squares regression (PLSR) and support vector machine regression (SVR), were performed to establish the best prediction models for PE, PC, APC, and Chla contents. The prediction results showed that the PLSR model performed the best for PE (R Test 2 = 0.96, MAPE = 8.31%, RPD = 5.21) and the SVR model performed the best for PC (R Test 2 = 0.94, MAPE = 7.18%, RPD = 4.16) and APC (R Test 2 = 0.84, MAPE = 18.25%, RPD = 2.53). Two models (PLSR and SVR) performed almost the same for Chla (PLSR: R Test 2 = 0.92, MAPE = 12.77%, RPD = 3.61; SVR: R Test 2 = 0.93, MAPE = 13.51%, RPD =3.60). Further validation of the optimal models was performed using field-collected samples, and the result demonstrated satisfactory robustness and accuracy. The distribution of PE, PC, APC, and Chla contents within a thallus was visualized according to the optimal prediction models. The results showed that hyperspectral imaging technology was effective for fast, accurate, and noninvasive phenotyping of the PE, PC, APC, and Chla contents of Neopyropia in situ. This could benefit the efficiency of macroalgae breeding, phenomics research, and other related applications.
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Affiliation(s)
- Shuai Che
- Key Laboratory of Marine Genetics and Breeding (Ministry of Education), College of Marine Life Sciences, Ocean University of China, Qingdao, 266003, China
| | - Guoying Du
- Key Laboratory of Marine Genetics and Breeding (Ministry of Education), College of Marine Life Sciences, Ocean University of China, Qingdao, 266003, China
| | - Xuefeng Zhong
- Key Laboratory of Marine Genetics and Breeding (Ministry of Education), College of Marine Life Sciences, Ocean University of China, Qingdao, 266003, China
| | - Zhaolan Mo
- Key Laboratory of Marine Genetics and Breeding (Ministry of Education), College of Marine Life Sciences, Ocean University of China, Qingdao, 266003, China
| | - Zhendong Wang
- Key Laboratory of Marine Genetics and Breeding (Ministry of Education), College of Marine Life Sciences, Ocean University of China, Qingdao, 266003, China
| | - Yunxiang Mao
- Key Laboratory of Utilization and Conservation of Tropical Marine Bioresource (Ministry of Education), College of Fisheries and Life Science, Hainan Tropical Ocean University, Sanya, 572002, China
- Yazhou Bay Innovation Institute, Hainan Tropical Ocean University, Sanya, 572025, China
- Laboratory for Marine Biology and Biotechnology, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao, 266073, China
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Ige AD, Olasanmi B, Bauchet GJ, Kayondo IS, Mbanjo EGN, Uwugiaren R, Motomura-Wages S, Norton J, Egesi C, Parkes EY, Kulakow P, Ceballos H, Dieng I, Rabbi IY. Validation of KASP-SNP markers in cassava germplasm for marker-assisted selection of increased carotenoid content and dry matter content. FRONTIERS IN PLANT SCIENCE 2022; 13:1016170. [PMID: 36311140 PMCID: PMC9597466 DOI: 10.3389/fpls.2022.1016170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 09/15/2022] [Indexed: 06/16/2023]
Abstract
Provitamin A biofortification and increased dry matter content are important breeding targets in cassava improvement programs worldwide. Biofortified varieties contribute to the alleviation of provitamin A deficiency, a leading cause of preventable blindness common among pre-school children and pregnant women in developing countries particularly Africa. Dry matter content is a major component of dry yield and thus underlies overall variety performance and acceptability by growers, processors, and consumers. Single nucleotide polymorphism (SNP) markers linked to these traits have recently been discovered through several genome-wide association studies but have not been deployed for routine marker-assisted selection (MAS). This is due to the lack of useful information on markers' performances in diverse genetic backgrounds. To overcome this bottleneck, technical and biological validation of the loci associated with increased carotenoid content and dry matter content were carried out using populations independent of the marker discovery population. In the present study, seven previously identified markers for these traits were converted to a robust set of uniplex allele-specific polymerase chain reaction (PCR) assays and validated in two independent pre-breeding and breeding populations. These assays were efficient in discriminating marker genotypic classes and had an average call rate greater than 98%. A high correlation was observed between the predicted and observed carotenoid content as inferred by root yellowness intensity in the breeding (r = 0.92) and pre-breeding (r = 0.95) populations. On the other hand, dry matter content-markers had moderately low predictive accuracy in both populations (r< 0.40) due to the more quantitative nature of the trait. This work confirmed the markers' effectiveness in multiple backgrounds, therefore, further strengthening their value in cassava biofortification to ensure nutritional security as well as dry matter content productivity. Our study provides a framework to guide future marker validation, thus leading to the more routine use of markers in MAS in cassava improvement programs.
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Affiliation(s)
- Adenike D. Ige
- International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria
- Pan African University Life and Earth Sciences Institute (including Health and Agriculture), University of Ibadan, Ibadan, Nigeria
| | - Bunmi Olasanmi
- Department of Crop and Horticultural Sciences, University of Ibadan, Ibadan, Nigeria
| | | | - Ismail S. Kayondo
- International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria
| | | | - Ruth Uwugiaren
- International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria
- Molecular Plant Sciences program, Washington State University, Pullman, WA, United States
| | - Sharon Motomura-Wages
- College of Tropical Agriculture and Human Resources, University of Hawaii at Manoa, Hilo, HI, United States
| | - Joanna Norton
- College of Tropical Agriculture and Human Resources, University of Hawaii at Manoa, Hilo, HI, United States
| | - Chiedozie Egesi
- International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria
- Cornell University, Ithaca, NY, United States
| | - Elizabeth Y. Parkes
- International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria
| | - Peter Kulakow
- International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria
| | - Hernán Ceballos
- The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT), Cali, Colombia
| | - Ibnou Dieng
- International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria
| | - Ismail Y. Rabbi
- International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria
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Rabbi IY, Kayondo SI, Bauchet G, Yusuf M, Aghogho CI, Ogunpaimo K, Uwugiaren R, Smith IA, Peteti P, Agbona A, Parkes E, Lydia E, Wolfe M, Jannink JL, Egesi C, Kulakow P. Genome-wide association analysis reveals new insights into the genetic architecture of defensive, agro-morphological and quality-related traits in cassava. PLANT MOLECULAR BIOLOGY 2022; 109:195-213. [PMID: 32734418 PMCID: PMC9162993 DOI: 10.1007/s11103-020-01038-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Accepted: 07/20/2020] [Indexed: 05/05/2023]
Abstract
More than 40 QTLs associated with 14 stress-related, quality and agro-morphological traits were identified. A catalogue of favourable SNP markers for MAS and a list of candidate genes are provided. Cassava (Manihot esculenta) is one of the most important starchy root crops in the tropics due to its adaptation to marginal environments. Genetic progress in this clonally propagated crop can be accelerated through the discovery of markers and candidate genes that could be used in cassava breeding programs. We carried out a genome-wide association study (GWAS) using a panel of 5130 clones developed at the International Institute of Tropical Agriculture-Nigeria. The population was genotyped at more than 100,000 SNP markers via genotyping-by-sequencing (GBS). Genomic regions underlying genetic variation for 14 traits classified broadly into four categories: biotic stress (cassava mosaic disease and cassava green mite severity); quality (dry matter content and carotenoid content) and plant agronomy (harvest index and plant type) were investigated. We also included several agro-morphological traits related to leaves, stems and roots with high heritability. In total, 41 significant associations were uncovered. While some of the identified loci matched with those previously reported, we present additional association signals for the traits. We provide a catalogue of favourable alleles at the most significant SNP for each trait-locus combination and candidate genes occurring within the GWAS hits. These resources provide a foundation for the development of markers that could be used in cassava breeding programs and candidate genes for functional validation.
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Affiliation(s)
- Ismail Yusuf Rabbi
- International Institute of Tropical Agriculture (IITA), Ibadan, 200001, Oyo State, Nigeria.
| | - Siraj Ismail Kayondo
- International Institute of Tropical Agriculture (IITA), Ibadan, 200001, Oyo State, Nigeria
| | | | - Muyideen Yusuf
- International Institute of Tropical Agriculture (IITA), Ibadan, 200001, Oyo State, Nigeria
| | - Cynthia Idhigu Aghogho
- International Institute of Tropical Agriculture (IITA), Ibadan, 200001, Oyo State, Nigeria
| | - Kayode Ogunpaimo
- International Institute of Tropical Agriculture (IITA), Ibadan, 200001, Oyo State, Nigeria
| | - Ruth Uwugiaren
- International Institute of Tropical Agriculture (IITA), Ibadan, 200001, Oyo State, Nigeria
| | - Ikpan Andrew Smith
- International Institute of Tropical Agriculture (IITA), Ibadan, 200001, Oyo State, Nigeria
| | - Prasad Peteti
- International Institute of Tropical Agriculture (IITA), Ibadan, 200001, Oyo State, Nigeria
| | - Afolabi Agbona
- International Institute of Tropical Agriculture (IITA), Ibadan, 200001, Oyo State, Nigeria
| | - Elizabeth Parkes
- International Institute of Tropical Agriculture (IITA), Ibadan, 200001, Oyo State, Nigeria
| | - Ezenwaka Lydia
- National Root Crops Research Institute (NRCRI), PMB 7006, Umudike, 440221, Nigeria
| | - Marnin Wolfe
- Section on Plant Breeding and Genetics, School of Integrative Plant Sciences, Cornell University, Ithaca, NY, 14850, USA
| | - Jean-Luc Jannink
- Section on Plant Breeding and Genetics, School of Integrative Plant Sciences, Cornell University, Ithaca, NY, 14850, USA
- United States Department of Agriculture - Agriculture Research Service, Ithaca, NY, 14850, USA
| | - Chiedozie Egesi
- International Institute of Tropical Agriculture (IITA), Ibadan, 200001, Oyo State, Nigeria
- National Root Crops Research Institute (NRCRI), PMB 7006, Umudike, 440221, Nigeria
- Global Development Department, College of Agriculture and Life Sciences, Cornell University, Ithaca, NY, 14850, USA
| | - Peter Kulakow
- International Institute of Tropical Agriculture (IITA), Ibadan, 200001, Oyo State, Nigeria
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de Carvalho RRB, Marmolejo Cortes DF, Bandeira e Sousa M, de Oliveira LA, de Oliveira EJ. Image-based phenotyping of cassava roots for diversity studies and carotenoids prediction. PLoS One 2022; 17:e0263326. [PMID: 35100324 PMCID: PMC8803208 DOI: 10.1371/journal.pone.0263326] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 01/16/2022] [Indexed: 12/12/2022] Open
Abstract
Phenotyping to quantify the total carotenoids content (TCC) is sensitive, time-consuming, tedious, and costly. The development of high-throughput phenotyping tools is essential for screening hundreds of cassava genotypes in a short period of time in the biofortification program. This study aimed to (i) use digital images to extract information on the pulp color of cassava roots and estimate correlations with TCC, and (ii) select predictive models for TCC using colorimetric indices. Red, green and blue images were captured in root samples from 228 biofortified genotypes and the difference in color was analyzed using L*, a*, b*, hue and chroma indices from the International Commission on Illumination (CIELAB) color system and lightness. Colorimetric data were used for principal component analysis (PCA), correlation and for developing prediction models for TCC based on regression and machine learning. A high positive correlation between TCC and the variables b* (r = 0.90) and chroma (r = 0.89) was identified, while the other correlations were median and negative, and the L* parameter did not present a significant correlation with TCC. In general, the accuracy of most prediction models (with all variables and only the most important ones) was high (R2 ranging from 0.81 to 0.94). However, the artificial neural network prediction model presented the best predictive ability (R2 = 0.94), associated with the smallest error in the TCC estimates (root-mean-square error of 0.24). The structure of the studied population revealed five groups and high genetic variability based on PCA regarding colorimetric indices and TCC. Our results demonstrated that the use of data obtained from digital image analysis is an economical, fast, and effective alternative for the development of TCC phenotyping tools in cassava roots with high predictive ability.
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Affiliation(s)
- Ravena Rocha Bessa de Carvalho
- Centro de Ciências Agrárias, Ambientais e Biológicas, Universidade Federal do Recôncavo da Bahia, Rua Rui Barbosa, Cruz das Almas, BA, Brazil
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9
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Nkouaya Mbanjo EG, Hershberger J, Peteti P, Agbona A, Ikpan A, Ogunpaimo K, Kayondo SI, Abioye RS, Nafiu K, Alamu EO, Adesokan M, Maziya-Dixon B, Parkes E, Kulakow P, Gore MA, Egesi C, Rabbi IY. Predicting starch content in cassava fresh roots using near-infrared spectroscopy. FRONTIERS IN PLANT SCIENCE 2022; 13:990250. [PMID: 36426140 PMCID: PMC9679500 DOI: 10.3389/fpls.2022.990250] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Accepted: 09/14/2022] [Indexed: 05/20/2023]
Abstract
The cassava starch market is promising in sub-Saharan Africa and increasing rapidly due to the numerous uses of starch in food industries. More accurate, high-throughput, and cost-effective phenotyping approaches could hasten the development of cassava varieties with high starch content to meet the growing market demand. This study investigated the effectiveness of a pocket-sized SCiO™ molecular sensor (SCiO) (740-1070 nm) to predict starch content in freshly ground cassava roots. A set of 344 unique genotypes from 11 field trials were evaluated. The predictive ability of individual trials was compared using partial least squares regression (PLSR). The 11 trials were aggregated to capture more variability, and the performance of the combined data was evaluated using two additional algorithms, random forest (RF) and support vector machine (SVM). The effect of pretreatment on model performance was examined. The predictive ability of SCiO was compared to that of two commercially available near-infrared (NIR) spectrometers, the portable ASD QualitySpec® Trek (QST) (350-2500 nm) and the benchtop FOSS XDS Rapid Content™ Analyzer (BT) (400-2490 nm). The heritability of NIR spectra was investigated, and important spectral wavelengths were identified. Model performance varied across trials and was related to the amount of genetic diversity captured in the trial. Regardless of the chemometric approach, a satisfactory and consistent estimate of starch content was obtained across pretreatments with the SCiO (correlation between the predicted and the observed test set, (R2 P): 0.84-0.90; ratio of performance deviation (RPD): 2.49-3.11, ratio of performance to interquartile distance (RPIQ): 3.24-4.08, concordance correlation coefficient (CCC): 0.91-0.94). While PLSR and SVM showed comparable prediction abilities, the RF model yielded the lowest performance. The heritability of the 331 NIRS spectra varied across trials and spectral regions but was highest (H2 > 0.5) between 871-1070 nm in most trials. Important wavelengths corresponding to absorption bands associated with starch and water were identified from 815 to 980 nm. Despite its limited spectral range, SCiO provided satisfactory prediction, as did BT, whereas QST showed less optimal calibration models. The SCiO spectrometer may be a cost-effective solution for phenotyping the starch content of fresh roots in resource-limited cassava breeding programs.
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Affiliation(s)
- Edwige Gaby Nkouaya Mbanjo
- International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria
- *Correspondence: Edwige Gaby Nkouaya Mbanjo,
| | - Jenna Hershberger
- Department of Plant and Environmental Sciences, Pee Dee Research and Education Center, Clemson University, Florence, SC, United States
| | - Prasad Peteti
- International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria
| | - Afolabi Agbona
- International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria
- Molecular & Environmental Plant Sciences, Texas A&M University, College Station, TX, United States
| | - Andrew Ikpan
- International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria
| | - Kayode Ogunpaimo
- International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria
| | - Siraj Ismail Kayondo
- International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria
| | - Racheal Smart Abioye
- International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria
| | - Kehinde Nafiu
- International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria
| | | | - Michael Adesokan
- International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria
| | - Busie Maziya-Dixon
- International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria
| | - Elizabeth Parkes
- International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria
| | - Peter Kulakow
- International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria
| | - Michael A. Gore
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, United States
| | - Chiedozie Egesi
- International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, United States
- National Root Crops Research Institute (NRCRI), Umuahia, Nigeria
| | - Ismail Yusuf Rabbi
- International Institute of Tropical Agriculture (IITA), Ibadan, Oyo State, Nigeria
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10
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Phumichai C, Aiemnaka P, Nathaisong P, Hunsawattanakul S, Fungfoo P, Rojanaridpiched C, Vichukit V, Kongsil P, Kittipadakul P, Wannarat W, Chunwongse J, Tongyoo P, Kijkhunasatian C, Chotineeranat S, Piyachomkwan K, Wolfe MD, Jannink JL, Sorrells ME. Genome-wide association mapping and genomic prediction of yield-related traits and starch pasting properties in cassava. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:145-171. [PMID: 34661695 DOI: 10.1007/s00122-021-03956-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/06/2021] [Accepted: 09/25/2021] [Indexed: 06/13/2023]
Abstract
GWAS identified eight yield-related, peak starch type of waxy and wild-type starch and 21 starch pasting property-related traits (QTLs). Prediction ability of eight GS models resulted in low to high predictability, depending on trait, heritability, and genetic architecture. Cassava is both a food and an industrial crop in Africa, South America, and Asia, but knowledge of the genes that control yield and starch pasting properties remains limited. We carried out a genome-wide association study to clarify the molecular mechanisms underlying these traits and to explore marker-based breeding approaches. We estimated the predictive ability of genomic selection (GS) using parametric, semi-parametric, and nonparametric GS models with a panel of 276 cassava genotypes from Thai Tapioca Development Institute, International Center for Tropical Agriculture, International Institute of Tropical Agriculture, and other breeding programs. The cassava panel was genotyped via genotyping-by-sequencing, and 89,934 single-nucleotide polymorphism (SNP) markers were identified. A total of 31 SNPs associated with yield, starch type, and starch properties traits were detected by the fixed and random model circulating probability unification (FarmCPU), Bayesian-information and linkage-disequilibrium iteratively nested keyway and compressed mixed linear model, respectively. GS models were developed, and forward predictabilities using all the prediction methods resulted in values of - 0.001-0.71 for the four yield-related traits and 0.33-0.82 for the seven starch pasting property traits. This study provides additional insight into the genetic architecture of these important traits for the development of markers that could be used in cassava breeding programs.
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Affiliation(s)
- Chalermpol Phumichai
- Department of Agronomy, Faculty of Agriculture, Kasetsart University, Bangkok, 10900, Thailand.
- Center for Agricultural Biotechnology, Kasetsart University, Kamphaeng Saen Campus, Nakhon Pathom, 73140, Thailand.
- Center of Excellence On Agricultural Biotechnology: (AG-BIO/MHESI), Bangkok, 10900, Thailand.
| | - Pornsak Aiemnaka
- Thai Tapioca Development Institute, Lumpini Tower, 1168/26 Rama IV Road, Bangkok, 10120, Thailand
| | - Piyaporn Nathaisong
- Thai Tapioca Development Institute, Lumpini Tower, 1168/26 Rama IV Road, Bangkok, 10120, Thailand
| | - Sirikan Hunsawattanakul
- Department of Agronomy, Faculty of Agriculture, Kasetsart University, Bangkok, 10900, Thailand
- Center for Agricultural Biotechnology, Kasetsart University, Kamphaeng Saen Campus, Nakhon Pathom, 73140, Thailand
- Center of Excellence On Agricultural Biotechnology: (AG-BIO/MHESI), Bangkok, 10900, Thailand
| | - Phasakorn Fungfoo
- Department of Agronomy, Faculty of Agriculture, Kasetsart University, Bangkok, 10900, Thailand
| | | | - Vichan Vichukit
- Thai Tapioca Development Institute, Lumpini Tower, 1168/26 Rama IV Road, Bangkok, 10120, Thailand
| | - Pasajee Kongsil
- Department of Agronomy, Faculty of Agriculture, Kasetsart University, Bangkok, 10900, Thailand
| | - Piya Kittipadakul
- Department of Agronomy, Faculty of Agriculture, Kasetsart University, Bangkok, 10900, Thailand
| | - Wannasiri Wannarat
- Department of Agronomy, Faculty of Agriculture, Kasetsart University, Bangkok, 10900, Thailand
| | - Julapark Chunwongse
- Department of Horticulture, Faculty of Agriculture Kamphaeng Saen, Kasetsart University, Nakhon Pathom, 73140, Thailand
| | - Pumipat Tongyoo
- Center for Agricultural Biotechnology, Kasetsart University, Kamphaeng Saen Campus, Nakhon Pathom, 73140, Thailand
| | - Chookiat Kijkhunasatian
- Cassava and Starch Technology Research Team, National Center for Genetic Engineering and Biotechnology, Pathumthani, 12120, Thailand
| | - Sunee Chotineeranat
- Cassava and Starch Technology Research Team, National Center for Genetic Engineering and Biotechnology, Pathumthani, 12120, Thailand
| | - Kuakoon Piyachomkwan
- Cassava and Starch Technology Research Team, National Center for Genetic Engineering and Biotechnology, Pathumthani, 12120, Thailand
| | - Marnin D Wolfe
- Plant Breeding and Genetics Section, Cornell University, Ithaca, NY, 14850, USA
| | - Jean-Luc Jannink
- United States Department of Agriculture - Agriculture Research Service, Ithaca, NY, 14850, USA
| | - Mark E Sorrells
- Plant Breeding and Genetics Section, Cornell University, Ithaca, NY, 14850, USA
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11
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Uchendu K, Njoku DN, Paterne A, Rabbi IY, Dzidzienyo D, Tongoona P, Offei S, Egesi C. Genome-Wide Association Study of Root Mealiness and Other Texture-Associated Traits in Cassava. FRONTIERS IN PLANT SCIENCE 2021; 12:770434. [PMID: 34975953 PMCID: PMC8719520 DOI: 10.3389/fpls.2021.770434] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 11/25/2021] [Indexed: 06/14/2023]
Abstract
Cassava breeders have made significant progress in developing new genotypes with improved agronomic characteristics such as improved root yield and resistance against biotic and abiotic stresses. However, these new and improved cassava (Manihot esculenta Crantz) varieties in cultivation in Nigeria have undergone little or no improvement in their culinary qualities; hence, there is a paucity of genetic information regarding the texture of boiled cassava, particularly with respect to its mealiness, the principal sensory quality attribute of boiled cassava roots. The current study aimed at identifying genomic regions and polymorphisms associated with natural variation for root mealiness and other texture-related attributes of boiled cassava roots, which includes fibre, adhesiveness (ADH), taste, aroma, colour, and firmness. We performed a genome-wide association (GWAS) analysis using phenotypic data from a panel of 142 accessions obtained from the National Root Crops Research Institute (NRCRI), Umudike, Nigeria, and a set of 59,792 high-quality single nucleotide polymorphisms (SNPs) distributed across the cassava genome. Through genome-wide association mapping, we identified 80 SNPs that were significantly associated with root mealiness, fibre, adhesiveness, taste, aroma, colour and firmness on chromosomes 1, 4, 5, 6, 10, 13, 17 and 18. We also identified relevant candidate genes that are co-located with peak SNPs linked to these traits in M. esculenta. A survey of the cassava reference genome v6.1 positioned the SNPs on chromosome 13 in the vicinity of Manes.13G026900, a gene recognized as being responsible for cell adhesion and for the mealiness or crispness of vegetables and fruits, and also known to play an important role in cooked potato texture. This study provides the first insights into understanding the underlying genetic basis of boiled cassava root texture. After validation, the markers and candidate genes identified in this novel work could provide important genomic resources for use in marker-assisted selection (MAS) and genomic selection (GS) to accelerate genetic improvement of root mealiness and other culinary qualities in cassava breeding programmes in West Africa, especially in Nigeria, where the consumption of boiled and pounded cassava is low.
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Affiliation(s)
- Kelechi Uchendu
- West Africa Centre for Crop Improvement (WACCI), University of Ghana, Accra, Ghana
- National Root Crops Research Institute (NRCRI), Umudike, Nigeria
| | | | - Agre Paterne
- International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria
| | | | - Daniel Dzidzienyo
- West Africa Centre for Crop Improvement (WACCI), University of Ghana, Accra, Ghana
| | - Pangirayi Tongoona
- West Africa Centre for Crop Improvement (WACCI), University of Ghana, Accra, Ghana
| | - Samuel Offei
- West Africa Centre for Crop Improvement (WACCI), University of Ghana, Accra, Ghana
| | - Chiedozie Egesi
- National Root Crops Research Institute (NRCRI), Umudike, Nigeria
- International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria
- Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY, United States
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12
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Torres LG, de Oliveira EJ, Ogbonna AC, Bauchet GJ, Mueller LA, Azevedo CF, Fonseca e Silva F, Simiqueli GF, de Resende MDV. Can Cross-Country Genomic Predictions Be a Reasonable Strategy to Support Germplasm Exchange? - A Case Study With Hydrogen Cyanide in Cassava. FRONTIERS IN PLANT SCIENCE 2021; 12:742638. [PMID: 34956254 PMCID: PMC8692580 DOI: 10.3389/fpls.2021.742638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 11/08/2021] [Indexed: 06/14/2023]
Abstract
Genomic prediction (GP) offers great opportunities for accelerated genetic gains by optimizing the breeding pipeline. One of the key factors to be considered is how the training populations (TP) are composed in terms of genetic improvement, kinship/origin, and their impacts on GP. Hydrogen cyanide content (HCN) is a determinant trait to guide cassava's products usage and processing. This work aimed to achieve the following objectives: (i) evaluate the feasibility of using cross-country (CC) GP between germplasm's of Embrapa Mandioca e Fruticultura (Embrapa, Brazil) and The International Institute of Tropical Agriculture (IITA, Nigeria) for HCN; (ii) provide an assessment of population structure for the joint dataset; (iii) estimate the genetic parameters based on single nucleotide polymorphisms (SNPs) and a haplotype-approach. Datasets of HCN from Embrapa and IITA breeding programs were analyzed, separately and jointly, with 1,230, 590, and 1,820 clones, respectively. After quality control, ∼14K SNPs were used for GP. The genomic estimated breeding values (GEBVs) were predicted based on SNP effects from analyses with TP composed of the following: (i) Embrapa genotypic and phenotypic data, (ii) IITA genotypic and phenotypic data, and (iii) the joint datasets. Comparisons on GEBVs' estimation were made considering the hypothetical situation of not having the phenotypic characterization for a set of clones for a certain research institute/country and might need to use the markers' effects that were trained with data from other research institutes/country's germplasm to estimate their clones' GEBV. Fixation index (FST) among the genetic groups identified within the joint dataset ranged from 0.002 to 0.091. The joint dataset provided an improved accuracy (0.8-0.85) compared to the prediction accuracy of either germplasm's sources individually (0.51-0.67). CC GP proved to have potential use under the present study's scenario, the correlation between GEBVs predicted with TP from Embrapa and IITA was 0.55 for Embrapa's germplasm, whereas for IITA's it was 0.1. This seems to be among the first attempts to evaluate the CC GP in plants. As such, a lot of useful new information was provided on the subject, which can guide new research on this very important and emerging field.
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Affiliation(s)
- Lívia Gomes Torres
- Department of Plant Science, Universidade Federal de Viçosa, Viçosa, Brazil
| | | | - Alex C. Ogbonna
- Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY, United States
- Boyce Thompson Institute, Ithaca, NY, United States
| | | | - Lukas A. Mueller
- Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY, United States
- Boyce Thompson Institute, Ithaca, NY, United States
| | | | | | | | - Marcos Deon Vilela de Resende
- Department of Forestry Engineering, Universidade Federal de Viçosa, Viçosa, Brazil
- Embrapa Café, Universidade Federal de Viçosa, Viçosa, Brazil
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13
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Alamu EO, Nuwamanya E, Cornet D, Meghar K, Adesokan M, Tran T, Belalcazar J, Desfontaines L, Davrieux F. Near-infrared spectroscopy applications for high-throughput phenotyping for cassava and yam: A review. Int J Food Sci Technol 2021; 56:1491-1501. [PMID: 33776247 PMCID: PMC7984172 DOI: 10.1111/ijfs.14773] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 08/06/2020] [Accepted: 08/10/2020] [Indexed: 01/20/2023]
Abstract
The review aimed to identify the different high‐throughput phenotyping (HTP) techniques that used for quality evaluation in cassava and yam breeding programmes, and this has provided insights towards the development of metrics and their application in cassava and yam improvements. A systematic review of the published research articles involved the use of NIRS in analysing the quality traits of cassava and yam was carried out, and Scopus, Science Direct, Web of Sciences and Google Scholar were searched. The results of the review established that NIRS could be used in understanding the chemical constituents (carbohydrate, protein, vitamins, minerals, carotenoids, moisture, starch, etc.) for high‐throughput phenotyping. This study provides preliminary evidence of the application of NIRS as an efficient and affordable procedure for HTP. However, the feasibility of using mid‐infrared spectroscopy (MIRS) and hyperspectral imaging (HSI) in combination with the NIRS could be further studied for quality traits phenotyping.
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Affiliation(s)
- Emmanuel Oladeji Alamu
- International Institute of Tropical Agriculture (IITA) Southern Africa Hub PO Box 310142 Chelstone, Lusaka Zambia.,International Institute of Tropical Agriculture (IITA) PMB 5320, Oyo Road Ibadan Oyo State Nigeria
| | - Ephraim Nuwamanya
- National Crops Resources Research Institute NaCRRI P.O Box 7084 Kampala Uganda
| | - Denis Cornet
- CIRAD UMR AGAP Montpellier F-34398 France.,Univ. Montpellier CIRAD INRA Montpellier SupAgro France
| | - Karima Meghar
- UMR Qualisud University of Montpellier CIRAD Montpellier SupAgro University of Avignon University of La Réunion 73 rue JF Breton Montpellier 34398 France
| | - Michael Adesokan
- International Institute of Tropical Agriculture (IITA) PMB 5320, Oyo Road Ibadan Oyo State Nigeria
| | - Thierry Tran
- UMR Qualisud University of Montpellier CIRAD Montpellier SupAgro University of Avignon University of La Réunion 73 rue JF Breton Montpellier 34398 France.,The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT) CGIAR Research Program on Roots Tubers and Bananas (RTB) Apartado Aéreo 6713 Cali Colombia
| | - John Belalcazar
- The Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT) CGIAR Research Program on Roots Tubers and Bananas (RTB) Apartado Aéreo 6713 Cali Colombia
| | - Lucienne Desfontaines
- Centre de recherche Antilles-Guyane INRAe UR 1321 ASTRO Agrosystèmes tropicaux Petit-Bourg France
| | - Fabrice Davrieux
- UMR Qualisud University of Montpellier CIRAD Montpellier SupAgro University of Avignon University of La Réunion 73 rue JF Breton Montpellier 34398 France
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14
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Mbanjo EGN, Rabbi IY, Ferguson ME, Kayondo SI, Eng NH, Tripathi L, Kulakow P, Egesi C. Technological Innovations for Improving Cassava Production in Sub-Saharan Africa. Front Genet 2021; 11:623736. [PMID: 33552138 PMCID: PMC7859516 DOI: 10.3389/fgene.2020.623736] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 12/23/2020] [Indexed: 11/17/2022] Open
Abstract
Cassava is crucial for food security of millions of people in sub-Saharan Africa. The crop has great potential to contribute to African development and is increasing its income-earning potential for small-scale farmers and related value chains on the continent. Therefore, it is critical to increase cassava production, as well as its quality attributes. Technological innovations offer great potential to drive this envisioned change. This paper highlights genomic tools and resources available in cassava. The paper also provides a glimpse of how these resources have been used to screen and understand the pattern of cassava genetic diversity on the continent. Here, we reviewed the approaches currently used for phenotyping cassava traits, highlighting the methodologies used to link genotypic and phenotypic information, dissect the genetics architecture of key cassava traits, and identify quantitative trait loci/markers significantly associated with those traits. Additionally, we examined how knowledge acquired is utilized to contribute to crop improvement. We explored major approaches applied in the field of molecular breeding for cassava, their promises, and limitations. We also examined the role of national agricultural research systems as key partners for sustainable cassava production.
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Affiliation(s)
| | | | | | | | - Ng Hwa Eng
- CGIAR Excellence in Breeding Platform, El Batan, Mexico
| | - Leena Tripathi
- International Institute of Tropical Agriculture, Nairobi, Kenya
| | - Peter Kulakow
- International Institute of Tropical Agriculture, Ibadan, Nigeria
| | - Chiedozie Egesi
- International Institute of Tropical Agriculture, Ibadan, Nigeria
- National Root Crops Research Institute, Umudike, Nigeria
- Department of Global Development, College of Agriculture and Life Sciences, Cornell University, Ithaca, NY, United States
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