Hot Coffee: The Identity, Climate Profiles, Agronomy, and Beverage Characteristics of Coffea racemosa and C. zanguebariae

Climate change poses a considerable challenge for coffee farming, due to increasing temperatures, worsening weather perturbations, and shifts in the quantity and timing of precipitation. Of the actions required for ensuring climate resilience for coffee, changing the crop itself is paramount, and this may have to include using alternative coffee crop species. In this study we use a multidisciplinary approach to elucidate the identity, distribution, and attributes, of two minor coffee crop species from East Africa: Coffea racemosa and C. zanguebariae. Using DNA sequencing and morphology, we elucidate their phylogenetic relationships and confirm that they represent two distinct but closely related species. Climate profiling is used to understand their basic climatic requirements, which are compared to those of Arabica (C. arabica) and robusta (C. canephora) coffee. Basic agronomic data (including yield) and sensory information are provided and evaluated. Coffea racemosa and C. zanguebariae possess useful traits for coffee crop plant development, particularly heat tolerance, low precipitation requirement, high precipitation seasonality (dry season tolerance) and rapid fruit development (c. 4 months flowering to mature fruit). These attributes would be best accessed via breeding programs, although these species also have niche-market potential, particularly after further pre-farm selection and post-harvest optimization.

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Combining metabolomic and transcriptomic approaches to assess and improve crop quality traits

CABI Agriculture and Bioscience ◽

10.1186/s43170-020-00021-8 ◽

2021 ◽

Vol 2 (1) ◽

Author(s):

Delphine M. Pott ◽

Sara Durán-Soria ◽

Sonia Osorio ◽

José G. Vallarino

Keyword(s):

Quality Trait ◽

Quality Traits ◽

Crop Species ◽

Breeding Programs ◽

Crop Quality ◽

Crop Varieties ◽

New Genes ◽

Technical Advances ◽

Health Promoting ◽

Selection Of

AbstractPlant quality trait improvement has become a global necessity due to the world overpopulation. In particular, producing crop species with enhanced nutrients and health-promoting compounds is one of the main aims of current breeding programs. However, breeders traditionally focused on characteristics such as yield or pest resistance, while breeding for crop quality, which largely depends on the presence and accumulation of highly valuable metabolites in the plant edible parts, was left out due to the complexity of plant metabolome and the impossibility to properly phenotype it. Recent technical advances in high throughput metabolomic, transcriptomic and genomic platforms have provided efficient approaches to identify new genes and pathways responsible for the extremely diverse plant metabolome. In addition, they allow to establish correlation between genotype and metabolite composition, and to clarify the genetic architecture of complex biochemical pathways, such as the accumulation of secondary metabolites in plants, many of them being highly valuable for the human diet. In this review, we focus on how the combination of metabolomic, transcriptomic and genomic approaches is a useful tool for the selection of crop varieties with improved nutritional value and quality traits.

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Wheat, Barley, and Oat Breeding for Health Benefit Components in Grain

Plants ◽

10.3390/plants10010086 ◽

2021 ◽

Vol 10 (1) ◽

pp. 86

Author(s):

Igor G. Loskutov ◽

Elena K. Khlestkina

Keyword(s):

Bioactive Compounds ◽

Plant Genetic Resources ◽

Health Benefit ◽

Cultivated Plants ◽

Crop Species ◽

Breeding Programs ◽

Cereal Grain ◽

Staple Foods ◽

Functional Components ◽

Oat Breeding

Cereal grains provide half of the calories consumed by humans. In addition, they contain important compounds beneficial for health. During the last years, a broad spectrum of new cereal grain-derived products for dietary purposes emerged on the global food market. Special breeding programs aimed at cultivars utilizable for these new products have been launched for both the main sources of staple foods (such as rice, wheat, and maize) and other cereal crops (oat, barley, sorghum, millet, etc.). The breeding paradigm has been switched from traditional grain quality indicators (for example, high breadmaking quality and protein content for common wheat or content of protein, lysine, and starch for barley and oat) to more specialized ones (high content of bioactive compounds, vitamins, dietary fibers, and oils, etc.). To enrich cereal grain with functional components while growing plants in contrast to the post-harvesting improvement of staple foods with natural and synthetic additives, the new breeding programs need a source of genes for the improvement of the content of health benefit components in grain. The current review aims to consider current trends and achievements in wheat, barley, and oat breeding for health-benefiting components. The sources of these valuable genes are plant genetic resources deposited in genebanks: landraces, rare crop species, or even wild relatives of cultivated plants. Traditional plant breeding approaches supplemented with marker-assisted selection and genetic editing, as well as high-throughput chemotyping techniques, are exploited to speed up the breeding for the desired genotуpes. Biochemical and genetic bases for the enrichment of the grain of modern cereal crop cultivars with micronutrients, oils, phenolics, and other compounds are discussed, and certain cases of contributions to special health-improving diets are summarized. Correlations between the content of certain bioactive compounds and the resistance to diseases or tolerance to certain abiotic stressors suggest that breeding programs aimed at raising the levels of health-benefiting components in cereal grain might at the same time match the task of developing cultivars adapted to unfavorable environmental conditions.

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Abundant Mitochondrial Genome Diversity, Population Differentiation and Convergent Evolution in Pines

Genetics ◽

10.1093/genetics/150.4.1605 ◽

1998 ◽

Vol 150 (4) ◽

pp. 1605-1614

Author(s):

Junyuan Wu ◽

Konstantin V Krutovskii ◽

Steven H Strauss

Keyword(s):

Mitochondrial Dna ◽

Population Differentiation ◽

Mitochondrial Gene ◽

Dna Polymorphisms ◽

Neighbor Joining ◽

Closely Related Species ◽

Breeding Programs ◽

Length Polymorphisms ◽

Polymerase Chain ◽

Mitochondrial Genome Diversity

Abstract We examined mitochondrial DNA polymorphisms via the analysis of restriction fragment length polymorphisms in three closely related species of pines from western North America: knobcone (Pinus attenuata Lemm.), Monterey (P. radiata D. Don), and bishop (P. muricata D. Don). A total of 343 trees derived from 13 populations were analyzed using 13 homologous mitochondrial gene probes amplified from three species by polymerase chain reaction. Twenty-eight distinct mitochondrial DNA haplotypes were detected and no common haplotypes were found among the species. All three species showed limited variability within populations, but strong differentiation among populations. Based on haplotype frequencies, genetic diversity within populations (HS) averaged 0.22, and population differentiation (GST and θ) exceeded 0.78. Analysis of molecular variance also revealed that >90% of the variation resided among populations. For the purposes of genetic conservation and breeding programs, species and populations could be readily distinguished by unique haplotypes, often using the combination of only a few probes. Neighbor-joining phenograms, however, strongly disagreed with those based on allozymes, chloroplast DNA, and morphological traits. Thus, despite its diagnostic haplotypes, the genome appears to evolve via the rearrangement of multiple, convergent subgenomic domains.

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Development of microsatellite markers at the National Agrobiodiversity Center in Korea for the genetic assessment of underutilized crops

Plant Genetic Resources ◽

10.1017/s1479262114000525 ◽

2014 ◽

Vol 12 (S1) ◽

pp. S125-S129

Author(s):

Gi-An Lee ◽

Sok-Young Lee ◽

Ho-Sun Lee ◽

Kyung-Ho Ma ◽

Jae-Gyun Gwag ◽

...

Keyword(s):

Genetic Diversity ◽

Microsatellite Markers ◽

Germplasm Management ◽

Underutilized Crops ◽

Crop Species ◽

Closely Related Species ◽

Polymorphic Loci ◽

Allele Number ◽

The Mean ◽

Genetic Assessment

The RDA Genebank at the National Agrobiodiversity Center (NAAS, RDA, Republic of Korea) has conserved about 182,000 accessions in 1777 species and is working at preserving agricultural genetic resources for the conservation and sustainable utilization of genetic diversity. The detection of genetic variability in conserved resources is important for germplasm management, but the molecular evaluation tools providing genetic information are insufficient for underutilized crops, unlike those for major crops. In this regard, the Korean National Agrobiodiversity Center has been developing microsatellite markers for several underutilized crops. We designed 3640 primer pairs flanking simple sequence repeat (SSR) motifs for 6310 SSR clones in 21 crop species. Polymorphic loci were revealed in each species (7–36), and the mean ratio of polymorphic loci to all the loci tested was 12%. The average allele number was 5.1 (2.8–10.3) and the expected heterozygosity 0.51 (0.31–0.74). Some SSRs were transferable to closely related species, such as within the genera Fagopyrum and Allium. These SSR markers might be used for studying the genetic diversity of conserved underutilized crops.

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Pollen, vegetation change and climate at Lake Barombi Mbo (Cameroon) during the last ca. 33 000 cal yr BP: a numerical approach

Climate of the Past ◽

10.5194/cp-8-59-2012 ◽

2012 ◽

Vol 8 (1) ◽

pp. 59-78 ◽

Cited By ~ 30

Author(s):

J. Lebamba ◽

A. Vincens ◽

J. Maley

Keyword(s):

Vegetation Change ◽

Potential Evapotranspiration ◽

Numerical Approach ◽

Annual Precipitation ◽

Mean Annual Precipitation ◽

Climate Reconstructions ◽

Precipitation Seasonality ◽

Successional Stages ◽

Artificial Neural ◽

High Precipitation

Abstract. This paper presents quantitative reconstructions of vegetation and climate along the pollen sequence of Lake Barombi Mbo, southwestern Cameroon (4°39'45.75" N, 9°23'51.63" E, 303 m a.s.l.) during the last 33 000 cal yr BP, improving previous empirical interpretations. The biomisation method was applied to reconstruct potential biomes and forest successional stages. Mean annual precipitation, mean annual potential evapotranspiration and an index of moisture availability were reconstructed using modern analogues and an artificial neural network technique. The results show a dense forested environment around Lake Barombi Mbo of mixed evergreen/semi-deciduous type during the most humid phases (highest precipitation and lowest evapotranspiration), but with a more pronounced semi-deciduous type from ca. 6500 cal yr BP to the present day, related to increased seasonality. This forest displays a mature character until ca. 2800 cal yr BP, then becomes of secondary type during the last millennium, probably due to increased human activity. Two episodes of forest fragmentation are shown, which are synchronous with the lowest reconstructed precipitation and highest potential evapotranspiration values. The first of these occurs during the LGM, and the second one from ca. 3000 to ca. 1200 cal yr BP, mainly linked to high precipitation seasonality. Savanna were, however, never extensive within the Barombi Mbo basin, existing instead inside the forest in form of savanna patches. The climate reconstructions at Lake Barombi Mbo suggest that the artificial neural networks technique would be more reliable in this region, although the annual precipitation values are likely under-estimated through the whole sequence.

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How Population Structure Impacts Genomic Selection Accuracy in Cross-Validation: Implications for Practical Breeding

Frontiers in Plant Science ◽

10.3389/fpls.2020.592977 ◽

2020 ◽

Vol 11 ◽

Author(s):

Christian R. Werner ◽

R. Chris Gaynor ◽

Gregor Gorjanc ◽

John M. Hickey ◽

Tobias Kox ◽

...

Keyword(s):

Family Structure ◽

Genomic Selection ◽

Genomic Prediction ◽

Prediction Accuracy ◽

Cross Validation ◽

Careful Analysis ◽

Critical Approach ◽

Crop Species ◽

Breeding Programs ◽

Mendelian Sampling

Over the last two decades, the application of genomic selection has been extensively studied in various crop species, and it has become a common practice to report prediction accuracies using cross validation. However, genomic prediction accuracies obtained from random cross validation can be strongly inflated due to population or family structure, a characteristic shared by many breeding populations. An understanding of the effect of population and family structure on prediction accuracy is essential for the successful application of genomic selection in plant breeding programs. The objective of this study was to make this effect and its implications for practical breeding programs comprehensible for breeders and scientists with a limited background in quantitative genetics and genomic selection theory. We, therefore, compared genomic prediction accuracies obtained from different random cross validation approaches and within-family prediction in three different prediction scenarios. We used a highly structured population of 940 Brassica napus hybrids coming from 46 testcross families and two subpopulations. Our demonstrations show how genomic prediction accuracies obtained from among-family predictions in random cross validation and within-family predictions capture different measures of prediction accuracy. While among-family prediction accuracy measures prediction accuracy of both the parent average component and the Mendelian sampling term, within-family prediction only measures how accurately the Mendelian sampling term can be predicted. With this paper we aim to foster a critical approach to different measures of genomic prediction accuracy and a careful analysis of values observed in genomic selection experiments and reported in literature.

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Insight into the correlation between biochar amendment and shifts in bacterial community 4 years after a single incorporation in soybean- and maize-planted soils in northeastern China

Canadian Journal of Microbiology ◽

10.1139/cjm-2018-0366 ◽

2019 ◽

Vol 65 (5) ◽

pp. 353-364

Author(s):

Huixue Liu ◽

Yafang Wang ◽

Haizhu Jiang ◽

Dayu Sun ◽

Fan Yang

Keyword(s):

Bacterial Community ◽

Bacterial Abundance ◽

Bacterial Community Composition ◽

Soil Microbiome ◽

Crop Species ◽

Composition And Structure ◽

Soil Bacterial ◽

And Shifts ◽

Insight Into ◽

Biochar Amendment

To date, there have been few reports examining the correlation between biochar treatments, crop species, and microbiome shifts. In this study, shifts in the soil bacterial community were investigated 4 years after a single incorporation of biochar in soils planted with soybeans and maize. Clear changes in the bacterial community composition and structure were detected in the soybean-planted soil amended with low-titer biochar (7.89 t/ha), whereas such changes in the maize-planted soil were not observed at the same biochar amendment rate, suggesting a more sensitive influence on the bacterial community in the soybean-planted soil than that in the maize-planted soil. Bacterial abundance in the maize-planted soil was reduced significantly with increasing biochar addition (15.78 and 47.34 t/ha), which was probably due to the inhibitory substances originating from biochar. Both the bacterial community and biomarkers in soil under biochar amendment varied with planted crops, bacterial communities responding differently to biochar amendment. All these results suggested that biochar might influence the bacterial community in maize- and soybean-growing soils under different mechanisms. Our findings should be valuable for an in-depth understanding of the potential mechanism of soil microbiome changes following biochar incorporation and for biochar application in agriculture.

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Relationships among durum wheat accessions. I. Comparative analysis of SSR, AFLP, and phenotypic data

Genome ◽

10.1139/g06-151 ◽

2007 ◽

Vol 50 (4) ◽

pp. 373-384 ◽

Cited By ~ 23

Author(s):

M. Maccaferri ◽

S. Stefanelli ◽

F. Rotondo ◽

R. Tuberosa ◽

M.C. Sanguineti

Keyword(s):

Durum Wheat ◽

Genetic Relatedness ◽

Morphological Characteristics ◽

Morphological Data ◽

Phenotypic Traits ◽

Pedigree Data ◽

Crop Species ◽

Phenotypic Data ◽

Breeding Programs ◽

Triticum Durum Desf

The determination of genetic relatedness among elite materials of crop species allows for more efficient management of breeding programs and for the protection of breeders’ rights. Seventy simple sequence repeats (SSRs) and 234 amplified fragment length polymorphisms (AFLPs) were used to profile a collection of 58 durum wheat ( Triticum durum Desf.) accessions, representing the most important extant breeding programs. In addition, 42 phenotypic traits, including the morphological characteristics recommended for the official distinctness, uniformity, and stability tests, were recorded. The correlation between the genetic similarities obtained with the 2 marker classes was high (r = 0.81), whereas lower values were observed between molecular and phenotypic data (r = 0.46 and 0.56 for AFLPs and SSRs, respectively). Morphological data, even if sampled in high numbers, largely failed to describe the pattern of genetic similarity, according to known pedigree data and the indications provided by molecular markers.

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Development of Optimized Phenomic Predictors for Efficient Plant Breeding Decisions Using Phenomic-Assisted Selection in Soybean

Plant Phenomics ◽

10.34133/2019/5809404 ◽

2019 ◽

Vol 2019 ◽

pp. 1-15 ◽

Cited By ~ 7

Author(s):

Kyle Parmley ◽

Koushik Nagasubramanian ◽

Soumik Sarkar ◽

Baskar Ganapathysubramanian ◽

Asheesh K. Singh

Keyword(s):

Seed Yield ◽

Optimization Techniques ◽

Phenotypic Traits ◽

Yield Data ◽

Crop Species ◽

Breeding Programs ◽

High Throughput Phenotyping ◽

Complex Relationships ◽

Sensor Package ◽

Made In

The rate of advancement made in phenomic-assisted breeding methodologies has lagged those of genomic-assisted techniques, which is now a critical component of mainstream cultivar development pipelines. However, advancements made in phenotyping technologies have empowered plant scientists with affordable high-dimensional datasets to optimize the operational efficiencies of breeding programs. Phenomic and seed yield data was collected across six environments for a panel of 292 soybean accessions with varying genetic improvements. Random forest, a machine learning (ML) algorithm, was used to map complex relationships between phenomic traits and seed yield and prediction performance assessed using two cross-validation (CV) scenarios consistent with breeding challenges. To develop a prescriptive sensor package for future high-throughput phenotyping deployment to meet breeding objectives, feature importance in tandem with a genetic algorithm (GA) technique allowed selection of a subset of phenotypic traits, specifically optimal wavebands. The results illuminated the capability of fusing ML and optimization techniques to identify a suite of in-season phenomic traits that will allow breeding programs to decrease the dependence on resource-intensive end-season phenotyping (e.g., seed yield harvest). While we illustrate with soybean, this study establishes a template for deploying multitrait phenomic prediction that is easily amendable to any crop species and any breeding objective.

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Genetic Variation Within and Among Lowland Switchgrass Cultivars as Revealed With AFLP Polymorphisms

Global Journal of Agricultural and Allied Sciences ◽

10.35251/gjaas.2020.002 ◽

2020 ◽

Vol 2 (1) ◽

pp. 11-17

Author(s):

Shiva Makaju ◽

Yanqi Wu ◽

Michael Anderson ◽

Vijaya Kakani ◽

Michael Smith ◽

...

Keyword(s):

Genetic Diversity ◽

Genetic Variation ◽

Length Polymorphism ◽

Panicum Virgatum ◽

Fragment Length Polymorphism ◽

Hybrid Vigor ◽

The Other ◽

Crop Species ◽

Breeding Programs ◽

Panicum Virgatum L

Switchgrass (Panicum virgatum L.) has gained wider attention due to its recognition and use as a model herbaceous crop species for bioenergy production. Genetic diversity information in lowland switchgrass cultivars can help to specify cultivars to be used in the breeding programs aiming for hybrid vigor. The objective of this research was to analyze genetic variation within and among five lowland switchgrass cultivars using amplified fragment length polymorphism (AFLP) markers. AFLP polymorphisms indicated the presence of high genetic variation within lowland switchgrass cultivars with ‘Alamo’ exhibiting the highest genetic variation and ‘Performer’ the lowest. The Nei’s genetic diversity parameters revealed the lowest genetic distance between cultivars ‘Alamo’ and ‘Cimarron’ and the highest value between cultivars ‘Alamo’ and ‘Kanlow’. ‘Alamo’ and ‘Cimarron’ were clustered together while ‘BoMaster’, ‘Kanlow’, and ‘Performer’ were grouped into the other cluster. In addition, there were clusters with mixed genotypes. The findings of this study can be used to select diverse lines as parents for heterosis and inbreeding studies.

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