High-performing Cultivars Research Articles

Rapid In Situ Near-Infrared Assessment of Tetrahydrocannabinolic Acid in Cannabis Inflorescences before Harvest Using Machine Learning.

Cannabis is cultivated for therapeutic and recreational purposes where delta-9 tetrahydrocannabinol (THC) is a main target for its therapeutic effects. As the global cannabis industry and research into cannabinoids expands, more efficient and cost-effective analysis methods for determining cannabinoid concentrations will be beneficial to increase efficiencies and maximize productivity. The utilization of machine learning tools to develop near-infrared (NIR) spectroscopy-based prediction models, which have been validated from accurate and sensitive chemical analysis, such as gas chromatography (GC) or liquid chromatography mass spectroscopy (LCMS), is essential. Previous research on cannabinoid prediction models targeted decarboxylated cannabinoids, such as THC, rather than the naturally occurring precursor, tetrahydrocannabinolic acid (THCA), and utilize finely ground cannabis inflorescence. The current study focuses on building prediction models for THCA concentrations in whole cannabis inflorescences prior to harvest, by employing non-destructive screening techniques so cultivators may rapidly characterize high-performing cultivars for chemotype in real time, thus facilitating targeted optimization of crossbreeding efforts. Using NIR spectroscopy and LCMS to create prediction models we can differentiate between high-THCA and even ratio classes with 100% prediction accuracy. We have also developed prediction models for THCA concentration with a R2 = 0.78 with a prediction error average of 13%. This study demonstrates the viability of a portable handheld NIR device to predict THCA concentrations on whole cannabis samples before harvest, allowing the evaluation of cannabinoid profiles to be made earlier, therefore increasing high-throughput and rapid capabilities.

Comparison of field performance and fruit quality among newly released Italian June-bearing strawberry cultivars

The aim of this study was to compare newly released June-bearing strawberry cultivars (?Quicky?, ?Sandra?, ?Lofty?, ?Nadja? and ?Aprica?) in terms of their phenology, vegetative growth, productivity and fruit quality to identify their potential for wider cultivation. A field study was conducted in a strawberry plantation established in July 2020 in double rows on beds covered with black polyethylene foil (Sid, Serbia). The cultivars were evaluated in 2021-2022 for their flowering and ripening time, productivity, plant growth, biometrical and nutritional fruit traits (soluble solids content - SSC, total acids - TAs, vitamin C, total anthocyanins - TACY, total phenolics - TPC and total antioxidant capacity - TAC). The cultivar ?Quicky? started to ripen earliest, while ?Aprica? was the latest in both experimental years. The number of branch crowns per plant was significantly higher in ?Sandra? and ?Lofty?, whereby ?Sandra? had also the highest number of leaves per rosette (41.5) in comparison with the other tested cultivars. The cultivar ?Aprica? was superior in terms of productivity (1061 g/plant and 4.67 kg/m2), fruit weight (29.9 g) and fruit shape index (1.15). Contrary to this, ?Nadja? was the least productive cultivar (608 g/plant and 2.68 kg/m2). The cultivars ?Lofty? and ?Sandra? showed the highest SSC values and were also characterized by a considerably high level of TPC (1.29 mg GAE eq g-1 FW) and TACY (24.4 mg pg-3-g eq 100 g-1 FW), respectively. Variability among the tested cultivars could serve as an important criterion for the selection of new high-performing cultivars for a given growing region.

Metabolomics as a Prospective Tool for Soybean (Glycine max) Crop Improvement.

Global demand for soybean and its products has stimulated research into the production of novel genotypes with higher yields, greater drought and disease tolerance, and shorter growth times. Genetic research may be the most effective way to continue developing high-performing cultivars with desirable agronomic features and improved nutritional content and seed performance. Metabolomics, which predicts the metabolic marker for plant performance under stressful conditions, is rapidly gaining interest in plant breeding and has emerged as a powerful tool for driving crop improvement. The development of increasingly sensitive, automated, and high-throughput analytical technologies, paired with improved bioinformatics and other omics techniques, has paved the way for wide characterization of genetic characteristics for crop improvement. The combination of chromatography (liquid and gas-based) with mass spectrometry has also proven to be an indisputable efficient platform for metabolomic studies, notably plant metabolic fingerprinting investigations. Nevertheless, there has been significant progress in the use of nuclear magnetic resonance (NMR), capillary electrophoresis, and Fourier-transform infrared spectroscopy (FTIR), each with its own set of benefits and drawbacks. Furthermore, utilizing multivariate analysis, principal components analysis (PCA), discriminant analysis, and projection to latent structures (PLS), it is possible to identify and differentiate various groups. The researched soybean varieties may be correctly classified by using the PCA and PLS multivariate analyses. As metabolomics is an effective method for evaluating and selecting wild specimens with desirable features for the breeding of improved new cultivars, plant breeders can benefit from the identification of metabolite biomarkers and key metabolic pathways to develop new genotypes with value-added features.

Artificial Neural Network for Discrimination and Classification of Tropical Soybean Genotypes of Different Relative Maturity Groups

Soybean has a recognized narrow genetic base that often makes it difficult to visualize available genetic and phenotypic variability and identify superior genotypes during the selection process. However, the phenotypic expression of soybean plants is highly affected by photoperiod and the cultivation of a given variety is performed in the latitude range that presents ideal conditions for its development based on its relative maturity group (RMG) for the optimization of the phenotypic expression of its genotype. Based on the above, this study aimed to evaluate the efficiency of artificial neural networks (ANNs) as a tool for the correct discrimination and classification of tropical soybean genotypes according to their relative maturity group during the population selection process with the aim of optimizing the phenotypic performance of these selected genotypes. For this purpose, three biparental populations were synthesized, one with a wide genetic variability for the RMG character obtained from the hybridization between genitors of maturity groups RMG 5 (Sub-tropical 23° LS) × RMG 9.4 (Tropical 0° LS) and two populations with a narrow variability obtained between genitors RMG 7.3 (Tropical 20° LS) × RMG 9.4 and RMG 5.3 × RMG 6.7, respectively. Criteria for comparing the developed ANN architecture with Fisher’s linear and Anderson’s quadratic parametric discriminant methodologies were applied to the data for the discrimination and classification of the genotypes. ANN showed an apparent error rate of less than 8.16% as well as a low influence of environmental factors, correctly classifying the genotypes in the populations even in cases of reduced genetic variability such as in the RMG 5 × RMG 6 population. In contrast, the discriminant functions were inefficient in correctly classifying the genotypes in the populations with genealogical similarity (RMG 5 × RMG 6) and wide genetic variability, with an error rate of more than 50%. Based on the results of this study, ANN can be used for the discrimination of genotypes in the initial generations of selection in breeding programs for the development of high performance cultivars for wide and reduced photoperiod amplitudes, even with fewer selection environments, more efficiently, and with fewer time and resources applied. As a result of similarity between the parents, ANN can correctly classify genotypes from populations with a narrow genetic base, in addition to pure lines and genotypes with a high degree of inbreeding.

Assessment of some sesame mutants under normal and water-stress conditions

ABSTRACT Sesame (Sesamum indicum L.) is a tropical oilseed crop that is also cultivated in arid and semi-arid environments, where drought occurs frequently. The objective of this study was to assess the performance of some sesame mutants, developed by our team through EMS-mutagenesis in 2020, under well-watered conditions and restricted irrigation by analyzing certain morphological, physiological, and agronomic attributes. The experiment was conducted in pots under field conditions according to a completely randomized design with three replications. The stress was simulated by suspending and reducing irrigation to 50% of the control, from the beginning of flowering until the appearance of the first capsule. The results showed variation attributable to genotypes, water regimes and their interaction was significant for all parameters studied, except the number of seeds per capsule. The mutants “ML2-5”, “ML2-72” and “ML2-37” were found to be the most tolerant to drought, exhibiting lowest stress sensitivity index and highest seed yield were associated with higher proline content in the leaves, more developed root system, higher chlorophyll content, and higher stomatal conductance than the rest of the mutants studied. This is the first report of sesame mutant lines with such high tolerance to drought during flowering. They could be used for developing high-performing cultivars with tolerance to drought during the flowering stage. The number of capsules per plant and stomatal conductance can be considered selection criteria to improve water-stress tolerance in sesame.

Speed breeding to accelerate crop improvement

Global food security has become a major issue as the human population grows and the environment changes, with the current rate of improvement of several important crops inadequate to meet future demand. Crop plants have extended generation times, which contributes to the slow rate of progress. However, speed breeding has revolutionized the entire world by reducing generation time and speeding up breeding and research programs to improve crop varieties. In the absence of an integrated pre-breeding program, breeding new and high-performing cultivars with market-preferred traits can take more than ten years. After the first cross with parental genotypes, a large amount of time, space, and resources are committed to the selection and genetic advancement stages during the early stages of breeding. Speed breeding has the ability to shorten the time it takes to develop, market, and commercialize cultivars. Crop improvement in the face of a fast-changing environment and an ever-increasing human population is a major concern for scientists around the world. Current crop enhancement projects are progressing at a rate that is insufficient to meet food demand. Crop redesign is urgently needed for climate resilience, as well as long-term yield and nutrition. Crop progress is slowed significantly by the long generation time required by crop plants during the breeding process. Speed breeding is now being used on a large scale to shorten generation time and support multiple crop generations per year as a solution in this approach. Researchers are now using an integrated approach to improve breeding efficiency, combining speed breeding with current plant breeding and genetic engineering methods. Speed breeding is a promising approach for achieving nutritional security and sustainable agriculture by shortening breeding cycles for food and industrial crop enhancement. Speed breeding is a methodology that allows plant breeders to improve crop production by adjusting temperature, light duration, and intensity to boost plant development. It uses an artificial source of light, which is kept on continuously, to activate the photosynthetic process, which leads to growth and reproduction much earlier than normal. This will assist in meeting the demands of the future’s rising population. This can be accomplished using a variety of technologies, including genotyping, marker-assisted selection, high throughput phenotyping; gene editing, genomic selection, and re-domestication, all of which can be combined with speed breeding to allow plant breeders to keep up with a changing climate and growing human population.

The Performance of Representative Asian Vegetables in Different Production Systems in Texas

Demand for Asian vegetables is rising rapidly due to changing demographics and increasing consumer awareness of their health benefits. However, growers are not familiar with growing these “foreign” crops due to insufficient technical information regarding suitable cultivars for different regions, production schedules, disease and pest susceptibility, and postharvest management. The objective of this study was to conduct trials in different production systems and climate regions to demonstrate the potential of growing Asian vegetables in Texas. We conducted preliminary trials of nine leafy greens in the open field, high tunnel, and greenhouse (container and hydroponic production) to explore the suitability and potential for year-round production. We also conducted field trials for warm season crops in the open field in different climate zones. Results indicated that for cool season leafy greens, open field production has a limited growing season, high tunnel has the potential to extend the growing season, while greenhouse may provide year-round production using soilless substrate container culture or hydroponic system. For warm season crops, early planting is recommended for high yield. Additional research is warranted in different regions to test more species and cultivars and optimize the production system of high-performing cultivars to maximize production and profitability.

AGRONOMIC PERFORMANCE OF IMPROVED MAIZE (Zea mays) CULTIVARS IN SOUTHERN CHAD

This study was carried out to identify high-performing maize cultivars adapted to the environmental conditions of Southern Chad. Twelve new cultivars associated with two local cultivars often used by farmers in Southern Chad were evaluated in three different environments in a randomized complete block design (RCBD) with three replications. The analysis of variance showed significant differences (p<0.001) between cultivars for the measured traits except for plant height (p=0.157) and ear height (p=0.624). Genotype × environment interaction was also reported significant among cultivars only for days to flowering and number of kernels per row, but yield did not show any statistical difference, although assessed cultivars differed in their relative main performance across the three sites. Potential grain yield showed a negative correlation with days to flowering, ear height, and days to silking. The study revealed different yield performances for the assessed cultivars across different environments. The cultivar 2013 TZEE WPOP DT STR was the highest yield producing cultivars at the combined sites. The cultivars IWD C2 SYN, TZEE WPOP DT C5 STR C5, 2011 TZE YDT STR SYN, and DTE STR YSYN POP C4 showed high-performance cultivars across the different environments and can be therefore recommended for release as new cultivars to farmers of Southern Chad.

Combining perennial ryegrass cultivars in seed mixtures confers limited and situation-specific benefits for dairy pasture productivity

ABSTRACT Combining several cultivars within species in seed mixtures is often advocated as a means for improving crop or pasture performance. Herbage accumulation (HA) of perennial ryegrass-white clover pastures sown with a single cultivar representing different functional types of perennial ryegrass was compared with the HA of cultivar mixtures over three years in two contrasting environments (Waikato, dryland; Canterbury, irrigated) under dairy cattle grazing. Functional types were: mid-season flowering diploid, late-season diploid, and late-season tetraploid. Mixture treatments (n = 4 at each site) included all binary combinations plus the three-way combination. Mixture HA and the mean HA of the constituent cultivars did not differ for any of the mixture combinations in either environment, apart from winter in Waikato where the mid-diploid plus tetraploid mix out-yielded the mean of the individual cultivars and tended to increase total annual HA. The total annual HA of the mixtures was between 1.0 and 2.3 t DM/ha/year less than the HA of the highest-yielding individual cultivar included in the mixture in six of the eight mixture-environment combinations. While some benefits of mixtures for controlling grazing outcomes were observed, sowing individual high-performing cultivars is a better overall strategy than mixing cultivars to cover a spectrum of traits.

Peculiarities of morpho-biological and valuable economic features in spring barley lines and cultivars

Purpose and objectives - to determine the breeding value of spring barley cultivars and lines.Materials and methods: Twenty-two cultivars and 3 lines of spring barley were taken as the test material. The field experiments were carried out in the competitive variety trial nursery in compliance with the method of state variety trials. The forecrop was grain pea. The plot area was 10 m2; the experiments were carried out in 4 replications. Barley was sown with a breeding seeder SSFK-7. The yield, growing period length, lodging resistance, performance and its structural elements were determined. Calculus of variations analysis of variance were performed in STATISTICA 10 and EXCEL as BA Dospekhov described.Results and discussion: The peculiarities of 22 cultivars and 3 lines of spring barley were described by expression levels of the following quantitative traits: morpho-biological (performance, total and productive tillering capacity, spikelet and grain number per spike, spike length, grain weight from the main ear and lateral stalks) and economic (yield, growing period length, lodging resistance) ones.The variability of quantitative traits of the accessions under investigation was determined. In particular, the plant height variability was low (9.5%), the spike length and grain weight from the main spike variabilities were medium (15.6 and 19.5%, respectively), and the variability of other traits were high.The analysis distinguished intensive high-yielding cultivars Margret, Grace, Avhur, Datcha, Khors, and Troian and the line 14-561 (5.07–4.84 t/ha); lodging-resistant cultivars Amil, Troian (Lider), Datcha, and Grace and line 15-139; and high performance cultivars Amil, Khors, Hatunok, Akhiles, and Krasen.Conclusions. As a result of determining the characteristics of the spring barley accessions with high levels of expression of quantitative morpho-biological and economic traits, the breeding value of cultivars and lines suitable for combination breeding was evaluated.

Artificial neural networks and multiple linear regression as potential methods for modeling seed yield of safflower (Carthamus tinctorius L.)

Modeling relationships between safflower seed yield (SY) and its components would be helpful to understand the most important trait-(s) with significant effects on seed yield, which in turn helps safflower breeders in the indirect selection of high-performance cultivars. For this purpose, we evaluated performance of five different artificial neural network (ANN) models, including Generalized feed forward (GFF), multilayer perceptron (MLP), Jordan/Elman (JE), Principal component analysis (PCA), and Radial basis function (RBF) with different learning algorithms, transfer functions, hidden layers and neuron in each layer, along with multi-linear regression model to predict seed yield of safflower. A panel of 25 lines/cultivars was used during two years (2012–2014) to evaluate some of the important traits related to seed yield. PCA was used to perform feature extraction in the first stage of modeling. Based on PCA and first two components that incorporated approximately 79% of the total variability, five agro morphological and phenological traits, including plant height (PH), number of branches per plant (NBP), number of capsules per plant (NCP), thousand seed weight (TSW), and number of seeds per capsule (NSC), due to high values of Eigen vectors were selected as input. The performance of the models in predicting seed yield was determined using some of the statistical quality parameters, including coefficient of determination (R2), root mean square error (RMSE) and mean absolute error (MAE). The MLP model with the Levenberg–Marquardt learning algorithm, sigmoid axon transfer function, two hidden layers (i.e. topology 5-5-4-1) and 1500 training epochs was selected as the best model to predict seed yield of safflower. Sensitivity analysis indicated that the NCP is the most influential trait to predict SY in the MLP/ANN model.

Prescreening in large populations as a tool for identifying elevated CO2-responsive genotypes in plants.

Elevated atmospheric CO2 concentration (e[CO2]) can stimulate the photosynthesis and productivity of C3 species including food and forest crops. Intraspecific variation in responsiveness to e[CO2] can be exploited to increase productivity under e[CO2]. However, active selection of genotypes to increase productivity under e[CO2] is rarely performed across a wide range of germplasm, because of constraints of space and the cost of CO2 fumigation facilities. If we are to capitalise on recent advances in whole genome sequencing, approaches are required to help overcome these issues of space and cost. Here, we discuss the advantage of applying prescreening as a tool in large genome×e[CO2] experiments, where a surrogate for e[CO2] was used to select cultivars for more detailed analysis under e[CO2] conditions. We discuss why phenotypic prescreening in population-wide screening for e[CO2] responsiveness is necessary, what approaches could be used for prescreening for e[CO2] responsiveness, and how the data can be used to improve genetic selection of high-performing cultivars. We do this within the framework of understanding the strengths and limitations of genotype-phenotype mapping.

Red bayberry – the journey to its commercialisation in Australia

Red or Chinese bayberry (Morella rubra Sieb. and Zucc.) is a fruit tree native to China where it is typically known as Yang Mei. This summer season crop has been cultivated for centuries in the warm and humid south-eastern Provinces. The ‘lychee-sized’ fruit are usually deep red in colour when ripe, have a unique flavour and impart a soft and juicy mouthfeel considered ‘refreshing’. Red bayberry is highly prized in China for its flavour and also for its perceived health benefits. However, the fruit is virtually unknown elsewhere. The crop was introduced into Australia over a decade ago. Its introduction offered the prospect of counter-seasonal production for the rapidly expanding Chinese market as well as introducing a novel fruit to Australian consumers. Trial plantings ranging from Far North Queensland to Victoria and across to Western Australia, have shown that red bayberry can be successfully cultivated in this country. These trials have supported the selection of unique high-performing cultivars. Nonetheless, commercial production of red bayberry in Australia still faces challenges. Vegetative propagation of this woody species proved difficult. Accordingly, efficient protocols that work in commercial nursery practice had to be developed. Also, refinement of agronomic practices for Australian conditions was necessary to ensure consistent yields of high quality fruit. In addition, the inherent high perishability of the fresh fruit required investigation of novel postharvest treatments to extend shelf life. This paper overviews the research undertaken by The University of Queensland to address these issues. Progress entailed close collaboration with research and industry partners. Positive outcomes to date have established the potential for Australia to become a leading producer of red bayberry outside China.

Genetic diversity of high performance cultivars of upland and irrigated Brazilian rice.

The objective of this study was to analyze the diversity and discrimination of high-performance Brazilian rice cultivars using microsatellite markers. Twenty-nine rice cultivars belonging to EMBRAPA Arroz e Feijão germplasm bank in Brazil were genotyped by 24 SSR markers to establish their structure and genetic discrimination. It was demonstrated that the analyzed germplasm of rice presents an expressive and significant genetic diversity with low heterogeneity among the cultivars. All 29 cultivars were differentiated genetically, and were organized into two groups related to their upland and irrigated cultivation systems. These groups showed a high genetic differentiation, with greater diversity within the group that includes the cultivars for irrigated system. The genotyping data of these cultivars, with the morphological e phenotypical data, are valuable information to be used by rice breeding programs to develop new improved cultivars.

A descriptor list of Silybum marianum (L.) Gaertner – morphological and biological characters

Silybum marianum (L.) Gaertn (Milk thistle) is an important medicinal plant which fruits are used for treatment of various liver diseases. In an effort to utilize the genetic potential of cultivated plants in the best way, the breeding of new high-performance cultivars is underway all over the world. Genetic improvement in Silybum can only be, as with all other plants, achieved through a clear understanding of the plant´s behaviour and the amount of variability presented in wild populations. Surprisingly no descriptor list has been compiled up to now, which would permit an objective and easily repeatable description an evaluation of the different Silybum genotypes. The first part of such a descriptor list, which is intended mainly for evaluation of genotypes perspective for fruit production, is presented here and it contains both the morphological and biological characters.

Breeding signatures of rice improvement revealed by a genomic variation map from a large germplasm collection

Intensive rice breeding over the past 50 y has dramatically increased productivity especially in the indica subspecies, but our knowledge of the genomic changes associated with such improvement has been limited. In this study, we analyzed low-coverage sequencing data of 1,479 rice accessions from 73 countries, including landraces and modern cultivars. We identified two major subpopulations, indica I (IndI) and indica II (IndII), in the indica subspecies, which corresponded to the two putative heterotic groups resulting from independent breeding efforts. We detected 200 regions spanning 7.8% of the rice genome that had been differentially selected between IndI and IndII, and thus referred to as breeding signatures. These regions included large numbers of known functional genes and loci associated with important agronomic traits revealed by genome-wide association studies. Grain yield was positively correlated with the number of breeding signatures in a variety, suggesting that the number of breeding signatures in a line may be useful for predicting agronomic potential and the selected loci may provide targets for rice improvement.

Brassica napus L. cultivars show a broad variability in their morphology, physiology and metabolite levels in response to sulfur limitations and to pathogen attack

Under adequate sulfur supply, plants accumulate sulfate in the vacuoles and use sulfur-containing metabolites as storage compounds. Under sulfur-limiting conditions, these pools of stored sulfur-compounds are depleted in order to balance the nitrogen to sulfur ratio for protein synthesis. Stress conditions like sulfur limitation and/or pathogen attack induce changes in the sulfate pool and the levels of sulfur-containing metabolites, which often depend on the ecotypes or cultivars. We are interested in investigating the influence of the genetic background of canola (Brassica napus) cultivars in sulfur-limiting conditions on the resistance against Verticillium longisporum. Therefore, four commercially available B. napus cultivars were analyzed. These high-performing cultivars differ in some characteristics described in their cultivar pass, such as several agronomic traits, differences in the size of the root system, and resistance to certain pathogens, such as Phoma and Verticillium. The objectives of the study were to examine and explore the patterns of morphological, physiological and metabolic diversity in these B. napus cultivars at different sulfur concentrations and in the context of plant defense. Results indicate that the root systems are influenced differently by sulfur deficiency in the cultivars. Total root dry mass and length of root hairs differ not only among the cultivars but also vary in their reaction to sulfur limitation and pathogen attack. As a sensitive indicator of stress, several parameters of photosynthetic activity determined by PAM imaging showed a broad variability among the treatments. These results were supported by thermographic analysis. Levels of sulfur-containing metabolites also showed large variations. The data were interrelated to predict the specific behavior during sulfur limitation and/or pathogen attack. Advice for farming are discussed.

Persistence of dry matter yield among New Zealand perennial ryegrass (Lolium perenne L.) cultivars: insights from a long-term data set

Persistence of herbage yield is an important productivity trait of grass species and cultivars in New Zealand pastures. However, relatively little is known about genetic variation in this trait, principally because few studies comparing yield have continued beyond 3 years. This paper reports results from a comparison of 25 perennial ryegrass cultivars representing a wide range of functional types and genetic backgrounds conducted under sheep grazing in a summer-dry environment. Dry matter (DM) yield was measured for the first 3 years after sowing, then again in years seven and eight post-sowing, and in year ten post-sowing. Endophyte DNA fingerprinting conducted mid-way through year seven confirmed that, with one exception, ryegrass populations remained true-to-type in the cultivars sown with novel endophyte strains. The cultivar effect on DM yield was statistically significant in all measurement periods. Differences in yields among cultivars in years seven and eight were significantly and positively correlated with yield differences in years one to three (r=0.685 to 0.831 depending on which year contrasts were used). Thus, high-performing cultivars in the early years of the trial were also generally highperforming cultivars in years seven and eight, and vice-versa, indicating a high degree of yield stability in perennial ryegrass cultivars. Yield differences did not appear to be related to differences in cultivar heading date, ploidy, endophyte status, or genetic background. The relationship between yield in year ten and yields in years one to three was much weaker (r=0.392) than the relationship in years seven and eight. Possible reasons for this are discussed. Keywords: Perennial ryegrass; traits; persistence

Assessment of genetic diversity in 35 Pisum sativum accessions using microsatellite markers

Ahmad, S., Singh, M., Lamb-Palmer, N. D., Lefsrud, M. and Singh, J. 2012. Assessment of genetic diversity in 35 Pisum sativum accessions using microsatellite markers. Can. J. Plant Sci. 92: 1075–1081. Field pea is an important Canadian pulse crop and therefore developing high-performing cultivars is critical for Canadian pea growers. Information about genetic diversity is a key component for the creation of novel and desirable germplasm to develop elite pea breeding lines. The objective of the present study is to assess genetic diversity in 35 diverse Pisum accessions using 15 polymorphic microsatellites located on different pea chromosomes. Microsatellites were found to be polymorphic, amplifying a total of 41 alleles and were able to differentiate all 35 Pisum genotypes. These markers were scored by their polymorphic information content (PIC), ranging from 0.055 (AA206) to 0.660 (AB72) with an average of 0.460, and by their discriminating power (D), which varied from 0.057 (AA206) to 0.679 (AB 72) with an average of 0.475. Genetic similarity values ranged from 0.074 (between Maple pea NZ and Line 45760) to 0.875 (between Galena and Dakota) with an average of 0.336. Unweighted pair group method with arithmetic averages (UPGMA) cluster analysis grouped the 35 pea accessions into two major clusters and eight sub-clusters. The majority of Canadian and European genotypes were grouped separately, suggesting both these groups are from genetically distinct gene pools. The genetically diverse groups identified in this study can be used to derive parental lines for pea breeding.

POTENTIALS OF CALLUS CULTURE AS A BREEDING TOOL FOR POLYPLOIDISATION OF FRAGARIA VESCA L.

Tunnel effects in 250 years of strawberry breeding history resulted in high performance cultivars with reduction in quality traits connected with flavour and resistances. Genetic resources for important traits are found in wild species such as Fragaria vesca. Mutation breeding of F. vesca up to an octoploid chromosome set is necessary for cross-breeding on a balanced ploidy level with Fragaria ×ananassa Duch. Here, we report on the treatment of axillary seedling buds with amiprofos-methyl (APM) which resulted in sectorial, mericlinal and periclinal ploidy chimeras. Chimeral segregation was performed via callus culture as well as using the generative way (selfing). Callus development and shoot regeneration on selected leaf segments depended on the composition of the medium and varied among the repetitions. The regeneration of adventitious shoots started after six to eight weeks on the induction medium and lasted four to six months. Evaluation of ploidy level was done by e.g., phenotype evaluation, comparison of leaf morphology, stomata measurement, flow cytometry and chromosome counting. From the mutagen treatment to the first fruits of the homohistic regenerates, a period of 18 months was sufficient via callus culture. For generative segregation a time span of 30 months was needed. More tetraploid plants were gained from callus culture than from generative segregation. The auto-tetraploid mutants do not differ in fertility and were used in test crosses with F. ×ananassa resulting in hexaploid hybrids. A second mutagen treatment is being executed to obtain auto-octoploids via polyploidisation of the tetraploid F. vesca.