Secretory Tissues and Volatile Components of Disc Florets in Several Wild Helianthus L. Species.

Although flower pollinator interactions are known to be mediated by floral traits, not enough attention has been paid to the research of secretory tissues and volatile components of sunflower disc florets as potentially important parameters in breeding programs. (1) To our knowledge, this is the first integrated study aimed at better understanding the attractiveness of sunflower capitula to insects. In the study, we have made a very detailed comparative analysis of secretory tissues and the characterization of the volatile components (VOCs) of disc florets in 10 wild perennial Helianthus species. (2) For anatomical analyses, cross-sections were obtained from the nectary zone of disc florets using a cryotechnique procedure. Micromorphological observation and morphological and anatomical analysis of disc florets were performed using light and scanning electron microscopy. For VOCs, we applied headspace, GC-FID, and GC/MS analyses. (3) The obtained results indicate that there is a difference between the analyzed traits among studied species. H. eggertii, H. hirsutus, H. mollis, H. resinosus, and H. tuberosus had high disc diameter values, a high cross-section area and disc floret corolla length, as well as the largest cross-section area and thickness of the disc florets nectary. In the analyzed VOCs, 30 different compounds were detected. The highest yield and quantity of α-Pinene was observed in H. mollis. (4) Inflorescence features, such as receptacle diameter, corolla and secretory tissue properties, and floret VOCs production and characterization, provided valuable information that can be used as guidelines in sunflower breeding programs to maximize pollinator attractiveness and increase seed yield.

Oil yield prediction for sunflower hybrid selection using different machine learning algorithms.

Due to the increased demand for sunflower production, its breeding assignment is the intensification of the development of highly productive oil seed hybrids to satisfy the edible oil industry. Sunflower Oil Yield Prediction (SOYP) can help breeders to identify desirable new hybrids with high oil yield and their characteristics using machine learning (ML) algorithms. In this study, we developed ML models to predict oil yield using two sets of features. Moreover, we evaluated the most relevant features for accurate SOYP. ML algorithms that were used and compared were Artificial Neural Network (ANN), Support Vector Regression, K-Nearest Neighbour, and Random Forest Regressor (RFR). The dataset consisted of samples for 1250 hybrids of which 70% were randomly selected and were used to train the model and 30% were used to test the model and assess its performance. Employing MAE, MSE, RMSE and R2 evaluation metrics, RFR consistently outperformed in all datasets, achieving a peak of 0.92 for R2 in 2019. In contrast, ANN recorded the lowest MAE, reaching 65 in 2018 The paper revealed that in addition to seed yield, the following characteristics of hybrids were important for SOYP: resistance to broomrape (Or) and downy mildew (Pl) and maturity. It was also disclosed that the locality feature could be used for the estimation of sunflower oil yield but it is highly dependable on weather conditions that affect the oil content and seed yield. Up to our knowledge, this is the first study in which ML was used for sunflower oil yield prediction. The obtained results indicate that ML has great potential for application in oil yield prediction, but also selection of parental lines for hybrid production, RFR algorithm was found to be the most effective and along with locality feature is going to be further evaluated as an alternative method for genotypic selection.

Investigation of oxidative characteristics, fatty acid composition and bioactive compounds content in cold pressed oils of sunflower grown in Serbia and Argentina.

Background: In this work, the chemical composition analysis was performed for cold pressed oils obtained from the 15 sunflower hybrids grown in Serbia and Argentina, as well as the determination of their oxidative quality. The fatty acid composition and bioactive compounds including total tocopherols, phenols, carotenoids, and chlorophyll contents were investigated. The oxidation products were monitored through the peroxide value (PV), anisidine value (AnV), conjugated dienes (CD) and conjugated trienes (CT) content, and total oxidation index (TOTOX) under accelerated oxidation conditions by the oven method. Results: Linoleic acid was the most abundant fatty acid in investigated oil samples, followed by oleic and palmitic acids. The mean contents of total tocopherols, phenols, carotenoids, and chlorophyll were 518.24, 9.42, 7.54 and 0.99 mg/kg, respectively. In order to obtain an overview of sample variations according to the tested parameters Principal Component Analysis (PCA) was applied. Conclusion: PCA indicated that phenols, chlorophyll, linoleic and oleic acid were the most effective variables for the differentiation of sunflower hybrids grown in Serbia and Argentina. Furthermore, based on the fatty acid composition and bioactive compounds content in the oils, a new Artificial Neural Network (ANN) model was developed to predict the oxidative stability parameters of cold pressed sunflower oil.

Crop breeding for a changing climate in the Pannonian region: towards integration of modern phenotyping tools.

The Pannonian Plain, as the most productive region of Southeast Europe, has a long tradition of agronomic production as well as agronomic research and plant breeding. Many research institutions from the agri-food sector of this region have a significant impact on agriculture. Their well-developed and fruitful breeding programmes resulted in productive crop varieties highly adapted to the specific regional environmental conditions. Rapid climatic changes that occurred during the last decades led to even more investigations of complex interactions between plants and their environments and the creation of climate-smart and resilient crops. Plant phenotyping is an essential part of botanical, biological, agronomic, physiological, biochemical, genetic, and other omics approaches. Phenotyping tools and applied methods differ among these disciplines, but all of them are used to evaluate and measure complex traits related to growth, yield, quality, and adaptation to different environmental stresses (biotic and abiotic). During almost a century-long period of plant breeding in the Pannonian region, plant phenotyping methods have changed, from simple measurements in the field to modern plant phenotyping and high-throughput non-invasive and digital technologies. In this review, we present a short historical background and the most recent developments in the field of plant phenotyping, as well as the results accomplished so far in Croatia, Hungary, and Serbia. Current status and perspectives for further simultaneous regional development and modernization of plant phenotyping are also discussed.

Genetic Improvement in Sunflower Breeding-Integrated Omics Approach.

Foresight in climate change and the challenges ahead requires a systematic approach to sunflower breeding that will encompass all available technologies. There is a great scarcity of desirable genetic variation, which is in fact undiscovered because it has not been sufficiently researched as detection and designing favorable genetic variation largely depends on thorough genome sequencing through broad and deep resequencing. Basic exploration of genomes is insufficient to find insight about important physiological and molecular mechanisms unique to crops. That is why integrating information from genomics, epigenomics, transcriptomics, proteomics, metabolomics and phenomics enables a comprehensive understanding of the molecular mechanisms in the background of architecture of many important quantitative traits. Omics technologies offer novel possibilities for deciphering the complex pathways and molecular profiling through the level of systems biology and can provide important answers that can be utilized for more efficient breeding of sunflower. In this review, we present omics profiling approaches in order to address their possibilities and usefulness as a potential breeding tools in sunflower genetic improvement.

Prediction of mechanical extraction oil yield of new sunflower hybrids: artificial neural network model.

BACKGROUND: Sunflower seeds are in the top five most abundant oilseeds in the world, as well as sunflower oil in the edible oils group. Recently, increasing attention has been paid to cold-pressed sunflower oil because less processing is involved and no solvent is used. The present study was carried out to investigate dimensions (length, width, thickness), firmness, general (moisture content and hull content, mass of 1000 seeds), gravimetric (true and bulk density, porosity) and geometric characteristics (equivalent diameter, surface area, seed volume, sphericity) of 20 new sunflower hybrid seeds. Steps to determine most of these parameters are quite simple and easy since the process does not require long time or special equipment. RESULTS: Principal component analysis and cluster analysis confirmed differences in the mentioned characteristics between oily and confectionary sunflower hybrid seeds. One of the major differences between two groups of samples was in extraction oil yield. Mechanical extraction oil yield of the oily hybrid seeds was significantly (P Ë‚ 0.05) higher (from 68.72 ± 4.21% to 75.61 ± 1.99%) compared to confectionary hybrids (from 20.10 ± 2.82% to 39.91 ± 6.23%). Extraction oil yield values are known only after oil extraction. CONCLUSION: Knowledge of the extraction oil yield value before the mechanical extraction enables better management of the process. By application of the artificial neural network approach, an optimal neural network model was developed. The developed model showed a good generalization capability to predict the mechanical extraction oil yield of new sunflower hybrids based on the experimental data, which was a main goal of this paper. © 2021 Society of Chemical Industry.

Targeted plant improvement through genome editing: from laboratory to field.

KEY MESSAGE: This review illustrates how far we have come since the emergence of GE technologies and how they could be applied to obtain superior and sustainable crop production. The main challenges of today's agriculture are maintaining and raising productivity, reducing its negative impact on the environment, and adapting to climate change. Efficient plant breeding can generate elite varieties that will rapidly replace obsolete ones and address ongoing challenges in an efficient and sustainable manner. Site-specific genome editing in plants is a rapidly evolving field with tangible results. The technology is equipped with a powerful toolbox of molecular scissors to cut DNA at a pre-determined site with different efficiencies for designing an approach that best suits the objectives of each plant breeding strategy. Genome editing (GE) not only revolutionizes plant biology, but provides the means to solve challenges related to plant architecture, food security, nutrient content, adaptation to the environment, resistance to diseases and production of plant-based materials. This review illustrates how far we have come since the emergence of these technologies and how these technologies could be applied to obtain superior, safe and sustainable crop production. Synergies of genome editing with other technological platforms that are gaining significance in plants lead to an exciting new, post-genomic era for plant research and production. In previous months, we have seen what global changes might arise from one new virus, reminding us of what drastic effects such events could have on food production. This demonstrates how important science, technology, and tools are to meet the current time and the future. Plant GE can make a real difference to future sustainable food production to the benefit of both mankind and our environment.

Digital Image Analysis Using FloCIA Software for Ornamental Sunflower Ray Floret Color Evaluation.

As an esthetic trait, ray floret color has a high importance in the development of new sunflower genotypes and their market value. Standard methodology for the evaluation of sunflower ray florets is based on International Union for the Protection of New Varieties of Plants (UPOV) guidelines for sunflower. The major deficiency of this methodology is the necessity of high expertise from evaluators and its high subjectivity. To test the hypothesis that humans cannot distinguish colors equally, six commercial sunflower genotypes were evaluated by 100 agriculture experts, using UPOV guidelines. Moreover, the paper proposes a new methodology for sunflower ray floret color classification - digital UPOV (dUPOV), that relies on software image analysis but still leaves the final decision to the evaluator. For this purpose, we created a new Flower Color Image Analysis (FloCIA) software for sunflower ray floret digital image segmentation and automatic classification into one of the categories given by the UPOV guidelines. To assess the benefits and relevance of this method, accuracy of the newly developed software was studied by comparing 153 digital photographs of F2 genotypes with expert evaluator answers which were used as the ground truth. The FloCIA enabled visualizations of segmentation of ray floret images of sunflower genotypes used in the study, as well as two dominant color clusters, percentages of pixels belonging to each UPOV color category with graphical representation in the CIE (International Commission on Illumination) L∗a∗b∗ (or simply Lab) color space in relation to the mean vectors of the UPOV category. Precision (repeatability) of ray flower color determination was greater between dUPOV based expert color evaluation and software evaluation than between two UPOV based evaluations performed by the same expert. The accuracy of FloCIA software used for unsupervised (automatic) classification was 91.50% on the image dataset containing 153 photographs of F2 genotypes. In this case, the software and the experts had classified 140 out of 153 of images in the same color categories. This visual presentation can serve as a guideline for evaluators to determine the dominant color and to conclude if more than one significant color exists in the examined genotype.

Genetic and Genomic Tools in Sunflower Breeding for Broomrape Resistance.

Broomrape is a root parasitic plant causing yield losses in sunflower production. Since sunflower is an important oil crop, the development of broomrape-resistant hybrids is the prime breeding objective. Using conventional plant breeding methods, breeders have identified resistant genes and developed a number of hybrids resistant to broomrape, adapted to different growing regions worldwide. However, the spread of broomrape into new countries and the development of new and more virulent races have been noted intensively. Recent advances in sunflower genomics provide additional tools for plant breeders to improve resistance and find durable solutions for broomrape spread and virulence. This review describes the structure and distribution of new, virulent physiological broomrape races, sources of resistance for introduction into susceptible cultivated sunflower, qualitative and quantitative resistance genes along with gene pyramiding and marker assisted selection (MAS) strategies applied in the process of increasing sunflower resistance. In addition, it presents an overview of underutilized biotechnological tools, such as phenotyping, -omics, and genome editing techniques, which need to be introduced in the study of sunflower resistance to broomrape in order to achieve durable resistance.

Sunflower Genetics from Ancestors to Modern Hybrids-A Review.

Domestication and the first steps of sunflower breeding date back more than 4000 years. As an interesting crop to humans, sunflower underwent significant changes in the past to finally find its place as one of the most significant oil crops today. Substantial progress has already been made in understanding how sunflower was domesticated. Recent advances in molecular techniques with improved experimental designs contributed to further understanding of the genetic and molecular basis underlying the architectural and phenotypic changes that occurred during domestication and improvements in sunflower breeding. Understanding the domestication process and assessing the current situation concerning available genotypic variations are essential in order for breeders to face future challenges. A review of the tools that are used for exploring the genetic and genome changes associated with sunflower domestication is given in the paper, along with a discussion of their possible implications on classical sunflower breeding techniques and goals.

Potential of Legume-Brassica Intercrops for Forage Production and Green Manure: Encouragements from a Temperate Southeast European Environment.

Legumes and brassicas have much in common: importance in agricultural history, rich biodiversity, numerous forms of use, high adaptability to diverse farming designs, and various non-food applications. Rare available resources demonstrate intercropping legumes and brassicas as beneficial to both, especially for the latter, profiting from better nitrogen nutrition. Our team aimed at designing a scheme of the intercrops of autumn- and spring-sown annual legumes with brassicas for ruminant feeding and green manure, and has carried out a set of field trials in a temperate Southeast European environment and during the past decade, aimed at assessing their potential for yields of forage dry matter and aboveground biomass nitrogen and their economic reliability via land equivalent ratio. This review provides a cross-view of the most important deliverables of our applied research, including eight annual legume crops and six brassica species, demonstrating that nearly all the intercrops were economically reliable, as well as that those involving hairy vetch, Hungarian vetch, Narbonne vetch and pea on one side, and fodder kale and rapeseed on the other, were most productive in both manners. Feeling encouraged that this pioneering study may stimulate similar analyses in other environments and that intercropping annual legume and brassicas may play a large-scale role in diverse cropping systems, our team is heading a detailed examination of various extended research.