Plant Breeding Research Articles

Application of machine learning for identification of heterotic groups in sunflower through combined approach of phenotyping, genotyping and protein profiling

Application of machine learning in plant breeding is a recent concept, that has to be optimized for precise utilization in the breeding program of high yielding crop plants. Identification and efficient utilization of heterotic grouping pattern aided with machine learning approaches is of utmost importance in hybrid cultivar breeding as it can save time and resources required to breed a new plant hybrid/variety. In the present study, 109 genotypes of sunflower were investigated at morphological, biochemical (SDS-PAGE) and molecular levels (through micro-satellites (SSR) markers) for heterotic grouping. All the three datasets were combined, scaled, and subjected to unsupervised machine learning algorithms, i.e., Hierarchical clustering, K-means clustering and hybrid clustering algorithm (hierarchical + K-means) for assessment of efficiency and resolution power of these algorithms in practical plant breeding for heterotic grouping identification. Following the application of machine learning unsupervised clustering approach, two major groups were identified in the studied sunflower germplasm, and further classification revealed six smaller classes in each major group through hierarchical and hybrid clustering approach. Due to high resolution, obtained in hierarchical clustering, classification achieved through this algorithm was further used for selection of potential parents. One genotype from each smaller group was selected based on the maximum seed yield potential and hybridized in a line × tester mating design producing 36 F1 cross combinations. These F1s along with their parents were studied in open field conditions for validating the efficacy of identified heterotic groups in sunflowers genetic material under study. Data for 11 agronomic and qualitative traits were recorded. These 36 F1 combinations were tested for their combining ability (General/Specific), heterosis, genotypic and phenotypic correlation and path analysis. Results suggested that F1 hybrids performed better for all the traits under investigation than their respective parents. Findings of the study validated the use of machine learning approaches in practical plant breeding; however, more accurate and robust clustering algorithms need to be developed to handle the data noisiness of open field experiments.

Phytosulfokine alpha enhances regeneration of transformed and untransformed protoplasts of Brassica oleracea.

Phytosulfokine-α (PSK-α) is a disulfated pentapeptide (YIYTQ) acting as an intercellular signal peptide and growth factor. It was originally isolated from conditioned medium of asparagus mesophyll cell cultures in 1996 and later characterized as a hormone-like signal molecule with important roles in numerous processes of in vivo plant growth and development. It is currently becoming a valuable mitogenic factor in plant breeding and biotechnology due to its stimulatory effect on in vitro cell elongation, proliferation and differentiation. The focus of our work was to review current knowledge about the roles of PSK-α in plant biotechnology and to evaluate its influence on the regeneration of protoplasts of four Brassica oleracea cultivars (two cauliflower and two cabbage) cultured under two distinctive protocols and with different protoplast densities. Protoplast regeneration was studied due to its high value for plant genome editing, which is generally limited by the inefficient regeneration of treated protoplasts of numerous important plant genotypes. Our hypothesis was that the stress related to PEG-mediated protoplast transformation and the following decrease in viable protoplast density in culture could be alleviated by the addition of PSK-α to the culture medium. We therefore tested whether PSK-α could increase cell division at the early stages of culture (5 and 15 days after protoplast isolation) and stimulate the formation of microcallus colonies up to the 30st day of culture and to evaluate its influence on callus organogenesis leading to shoot regeneration. The PSK-α showed a strong stimulatory effect on untransformed protoplast regeneration already during the first days of culture, accelerating cell division up to 5.3-fold and the formation of multicellular microcallus colonies up to 37.0-fold. The beneficial influence was retained at later stages of regeneration, when PSK improved shoot organogenesis even if it was present only during the first 10 days of culture. The highest numbers of shoots, however, were regenerated when PSK was present during the first days of culture and later in solid shoot regeneration medium. Finally, the addition of PSK-α to PEG-transformed protoplasts significantly enhanced their division rate and the formation of microcallus colonies in selection media, up to 44.0-fold.

AGC kinases OXI1 and AGC2-2 regulate camalexin secretion and disease resistance by phosphorylating transporter PDR6.

Plant transporters regulating the distribution of secondary metabolites play critical roles in defending against pathogens, insects, and interacting with beneficial microbes. The phosphorylation of these transporters can alter their activity, stability, and intracellular protein trafficking. However, the regulatory mechanism underlying this modification remains elusive. In this study, we discovered two Orthologs of mammalian PKA, PKG, and PKC (AGC) kinases, Oxidative signal-inducible 1 (OXI1) and its closest homologue, AGC subclass 2 member 2 (AGC2-2; 75% amino acid sequence identity with OXI1), associated with the extracellular secretion of camalexin and Arabidopsis (Arabidopsis thaliana) resistance to Pseudomonas syringae and Botrytis cinerea. These kinases can undergo in vitro kinase reactions with three Pleiotropic drug resistance (PDR) transporters: PDR6, PDR8, and PDR12. Moreover, our investigation confirmed PDR6 interaction with OXI1 and AGC2-2. By performing LC-MS/MS and parallel reaction monitoring, we identified the phosphorylation sites on PDR6 targeted by these kinases. Notably, chitin induced PDR6 phosphorylation at specific residues, namely S31, S33, S827, and T832. Additional insights emerged by expressing dephosphorylated PDR6 variants in a pdr6 mutant background, revealing that the target residues S31, S33, and S827 promote PDR6 efflux activity, while T832 potentially contributes to PDR6 stability within the plasma membrane. The findings of this study elucidate partial mechanisms involved in the activity regulation of PDR-type transporters, providing valuable insights for their potential application in future plant breeding endeavors.

Genetic diversity of Guava varieties (Psidium guajava L.) based on morphology and ISSR molecular markers

Abstract. Hien PTT, Cham LTT, Hang VTT. 2024. Genetic diversity of Guava varieties (Psidium guajava L.) based on morphology and ISSR molecular markers. Biodiversitas 25: 1037-1045. Guava (Psidium guajava L.) is a fleshy-fruited representative belonging to the Myrtaceae family that has attracted attention due to its economic benefits. In this study, seventeen guava varieties in the Mekong Delta and Hanoi were collected and genetically validated by both morphology and DNA markers. The results revealed that fruit shape is a powerful indicator of guava discrimination. There are 12 out of 15 Inter Simple Sequence Repeats (ISSR) markers that show informative band patterns and 93 amplicons are generated with the size in length 200-2000 bp. The average polymorphic band and PIC value are 97.85% and 36%, respectively. Based on the dendrogram constructed by the Unweighted Pair Group Method using arithmetic Averages (UPGMA) method, samples were grouped into two main groups and the similarity level ranged from 55-98%. Group 2 contains Oi Tim (Purple guava), a special variety that showed high differences in terms of morphology and DNA profiles. Such information reflects the diversity of guava germplasm in Viet Nam, which is useful for conservation, and breeding strategies. The result revealed that 11 varieties expressed genetic diversity through both phenotypic traits and DNA profiles. Such information illustrates the genetic diversity among Psidium guajava, contributing to germplasm resources and plant breeding programs.

Does Ecological Planting–Breeding Mix Pattern Improve Farmers’ Subjective Well-Being? Evidence from the Middle and Lower Reaches of the Yangtze River

The Chinese government is making vigorous efforts to control agricultural pollution. The promotion of an ecological planting–breeding mix pattern is one of them. Farmers’ mode of production will affect their subjective well-being. Thus, this paper aims to analyze the impact of adopting the ecological planting–breeding mix pattern on farmers’ subjective well-being based on 895 pieces of survey data from the provinces of Hubei, Hunan, and Jiangxi in the middle and lower reaches of the Yangtze River. Using the endogenous switching regression model, we find that the adoption of the ecological planting–breeding mix pattern has a significant positive effect on farmers’ subjective well-being. Based on this counterfactual hypothesis, if the farmers who actually adopted the ecological planting–breeding mix pattern did not adopt it, their subjective well-being would decrease from 4.006 to 3.669. Further examination indicates that self-worth identification, income increase, and neighborhood communication could be potential mechanisms. Additionally, the effect of the ecological planting–breeding mix pattern on subjective well-being is stronger in the group with low financial support. The technical support provided by the government does not have a significant regulatory effect on the adoption of the ecological planting–breeding mix pattern on subjective well-being. Our results suggest that farmers’ ecological production behavior can affect their subjective well-being. This may be relevant to many developing countries today that are attempting to adopt ecological agriculture patterns.

The selection index of S3 corn convergent breeding population based on multivariate analysis

Abstract. Makmur, Farid M, Ala A, Mandja K, Anshori MF, Fadhilah AN. 2024. The selection index of S3 corn convergent breeding population based on multivariate analysis. Biodiversitas 25: 1097-1103. Corn is one of the most important and strategic food crops in the world, including Indonesia. Increasing corn production through a plant breeding program by assembling hybrid varieties begins with developing a convergent breeding population and index selection. The research aims to identify genetic variance and the effectiveness of selection indices in selecting high-yield S3 cross populations. The research was carried out in Rea Village, Binuang Sub-District, Polewali Mandar District, West Sulawesi from July to November 2022. The research used an augmented design with four blocks. Sixty-six lines were derived from 4 double cross populations and 8 populations of the S3 generation multiple-cross population, as well as 9 check varieties (NK7328, Pioneer 36, Bisi 18, Bisi 2, NK99, Nasa 29, JH45, Bisi 9, and NK212) were used in this study. The results indicate that the length of cobs (5.98;73.59%), length of seed cobs (7.06; 79.46%), weight of 100 seeds (7.75; 89.30%), and weight of seeds per cob (7.84; 65.59%) have moderate genetic variance and high heritability. The characteristics of stem diameter, yield percentage, and weight of seed per cob were effectively used in the selection index formulation. Based on the index selection, there were 14 potential corn lines with a good performance, recommended for the next hybridization stage.

Deciphering the Genetic Basis of Allelopathy in japonica Rice Cultivated in Temperate Regions Using a Genome-Wide Association Study

Allelopathy has been considered as a natural method of weed control. Despite the nature of allelochemical compounds has been studied, little is known about the genetic basis underlying allelopathy. However, it is known that rice exhibits diverse allelopathic potentials across varieties, and breeding for rice plants exhibiting allelopathic potential conferring an advantage against weeds in paddy fields would be highly desirable. Knowledge of the gene factors and the identification of the genomic regions responsible for allelopathy would facilitate breeding programs. Taking advantage of the existing genetic diversity in rice, particularly in temperate japonica rice, we conducted a comprehensive investigation into the genetic determinants that contribute to rice allelopathy. Employing Genome-Wide Association Study, we identified four Quantitative Trait Loci, with the most promising loci situated on chromosome 2 and 5. Subsequent inspection of the genes located within these QTLs revealed genes associated with the biosynthesis of secondary metabolites such as Phenylalanine Ammonia Lyase (PAL), a key enzyme in the synthesis of phenolic compounds, and two genes coding for R2R3-type MYB transcription factors. The identification of these two QTLs associated to allelopathy in rice provides a useful tool for further exploration and targeted breeding strategies.

Draft genome and SSR data mining of a Peruvian landrace of Capsicum chinense, the arnaucho chili pepper

AbstractThe Arnaucho chili pepper (ACP) is a traditional vegetable used in Peru because of its gastronomic properties. Due to its importance in the Peruvian diet and economy, this species is a resource that can be a candidate to plant breeding programs. In this study, the complete genome nucleotide sequence of this chili pepper was generated using the Illumina Hiseq 2500 sequencing technology. We sequenced the whole genome of the ACP using a paired-end 150 strategy, obtaining 330.46 GB of sequencing data. The genome size of the ACP was 2.98 Gb with a contig N50 of 237 Mb and 95.39% complete BUSCOs. Also, we identified 71.96% of repetitive DNA of the genome assembly, of which retroelements occupy 37.95% of the total genome. We downloaded genomes of the Solanoideae subfamily and conducted a comparative analysis of simple sequence repeats (SSRs) with our draft genome, and we identified lower number of SSRs in the ACP genome compared to other pepper species. This first ACP genome is expected to contribute to a better understanding of its genetics to adapt to the arid conditions of the Peruvian coastal ecosystem and evolution.

Fertilizer regime and cultivar affect barley growth and rhizobiome composition

To combat climate change and environmental pollution, agriculture must reduce mineral fertilizer use and adopt sustainable, low-input, and organic practices. In such systems, plants depend on the soil microbiome for nutrient acquisition and growth. Thus, enhancing plant-microbiome interactions is vital for maintaining or even increasing production sustainably. Modern plant breeding has led to barley cultivars that yield high under substantial mineral fertilizer application. However, this selective breeding may have diminished traits essential for plant-microbiome interactions, making these cultivars less suitable for sustainable agriculture. In contrast, older cultivars might have preserved traits from their common wild ancestor, enabling them to prosper under low nutrient conditions. This study evaluated four modern elite barley cultivars and three older (pre-1980). Grown under various fertilizer regimes, we assessed their root microbiome using 16S rRNA amplicon sequencing. Our objectives were: i) to determine the impact of nutrient availability on plant nutrient uptake and biomass production, and ii) to understand how the time since domestication (domestication age), individual cultivar, and fertilizer regime influence the root microbiome. We found that without fertilizer, old cultivars had superior biomass production and higher leaf concentrations of nitrogen, potassium, sulfur, iron, zinc, and copper than modern cultivars. This indicates that older barley cultivars may have retained their wild ancestors' capability to synergize with the soil microbiome, enhancing nutrient acquisition in low-input systems. Notably, the diversity of the rhizo-microbiome was not significantly affected by domestication age but varied with individual cultivar and fertilizer treatment.

A Review on Seed Storage Technology: Recent Trends and Advances in Sustainable Techniques for Global Food Security

Seed storage innovation assumes an essential part in guaranteeing worldwide food security by safeguarding genetic variety and preserving seed feasibility over time. This review article gives a complete outline of ongoing patterns and advances in supportable seed stockpiling strategies. Starting with an investigation of the significance of seed storage about food security challenges, the audit digs into conventional seed storing strategies and their obstacles. Additionally review also provides a comprehensive analysis of maintainable methodologies like controlled air capacity, cryopreservation, and seed preparing, featuring their adequacy in dragging out seed suitability while diminishing energy utilization and natural effect. Moreover, the review discusses the incorporation of digital technologies, for example, artificial intelligence and blockchain, in seed storage management to enhance the traceability and convenience of seed collections. Additionally, the role of community-based seed banks and participatory plant breeding in promoting seed resilience against climate change is explored. By discussing current research findings and practical applications, this review aims to inform policymakers, researchers, and practitioners about the diverse range of sustainable seed storage solutions available to safeguard global agricultural biodiversity and ensure food security in the face of evolving ecological challenges.

The effectiveness of breeding work on the improvement of the main economically important traits of traditional variety population Banannaya in Primorsky kray

Relevance. Although there is notable success in breeding vegetable crops to obtain heterotic F1 hybrids, traditional selection methods have been gaining in popularity as a means of improving the economically important traits of local traditional varieties in Russia today. These varieties suffered the reduction in their valuable starting parameters (yield, the uniformity of marketable produce and biochemical composition) over the many years of reproduction. The Department of Potato Breeding and Horticulture (FSBSI “FSC of Agricultural Biotechnology of the Far East named after A. K. Chaiki”) have been working on the creation of new squash variety-populations with large fruits using the variety-population Banannaya 42, bred by V. Ya. Smolei at the Far Eastern experimental station of the All-Union Scientific Research Institute of Plant Breeding in the 1940s, as the starting material. We carried out a multi-year research on the selection of promising families belonging to this variety to increase yield, improve the uniformity of fruits and the main biochemical parameters. Results. The breeding work conducted on the families of variety-population 945 in 2011-2022 resulted in the improvement of some economically important traits (the uniformity of fruit shape, yield, and biochemical parameters) compared to the started form. The eleven years of research allowed us to achieve high uniformity of fruit shape in the selection of the ninth year (PIP 2) – 90.0-90.7 % (increased by 34.9-36.0 %). The yield increased from 28.4 t/ha to 38.2-45.3 t/ha or by 34.5-59.5 %. The following biochemical parameters were improved through selection: the content of dry mater from 8.5 to 12.9 % or by 51.8 % on average, the content of sugars from 6.1 to 9.1 or by 49.2 %, the content of carotene from 1.7 to 3.8 or by 123.5 %, and the content of vitamin C from 9.6 to 21.1 or by 119.8 %. We selected the families of the same type from variety-population 945 (variety-population Banata) with improved and uniform economically important traits for submission to the State variety testing. The yield was 38.2-45.3 t/ha, fruits were heart-shaped, skin was greyish green, pulp was orange, and the content of sugars was 9.0-13.2 %. Large-fruited variety population Banata was included in the State register of breeding achievements admitted to use in the Russian Federation in 2024.

Tomato breeding for open ground in the south of Russia

Relevance. Tomato is the most widespread vegetable crop in the southern regions of Russia and one of the most popular with the population in all natural and climatic zones of the country. The majority of products is produced in large vegetable-growing, farming and private household farms. One of the most important tasks is to improve the assortment taking into account natural and climatic conditions of cultivation and directions of use. In this regard, the selection of industrial tomato with a high level of flexibility and resistance to biotic and abiotic stressors for the south of Russia is an urgent task. The aim of the study is to evaluate economically valuable features of perspective lines and new hybrids of tomato of industrial type, adapted to the conditions of southern Russia. Material and methodology. The work was carried out in the open field conditions of experimental production farm of the Federal Scientific Center of Vegetable Industry (Moscow region) and Biryuchekutskaya vegetable breeding experimental station – branch of the FSBSI FSVC (Rostov region). The objects of research were breeding material and 6 perspective new hybrid combinations of tomato of selection of the Federal State Budgetary Scientific and Scientific Institution of the Russian Federation. Results and discussion. As a result of step-by-step study and selection, the most promising samples were identified for further use as source material for practical breeding: B-6-C-2014, VS-B-№7, VS-B-18, VS-B-20, VS-B-35, VS-B-38. As a result of the competitive testing, the best hybrid combinations were identified: F1 B-1, F1 B-2, F1 B-4, meeting the requirements of commercial production in the south of Russia. It is shown that the hybrid combination F1 B-2 exceeds both standard samples F1 Meteor and F1 Perfectpeel both in terms of total yield (by 10.9 t/ha and 9.6 t/ha), marketability of fruits, and dry matter content in fruits (6.1 % vs. 5.1% and 5.2 %). Taking into account the complex of economic characteristics, a precocious F1 hybrid of tomato F1 B-2 called F1 Profy has been submitted to the State Variety Testing, as it shows stable economic characteristics over several years of study.

Korelasi antar Karakter Hasil Lima Varietas Tanaman Kacang Panjang (Vigna sinensis) di Lingkungan Organik

This study aims to determine the correlation between the yield characteristics of the yard long bean yield, and the superiority of one of the varieties in an organic environment. This research was conducted at the Integrated Field Laboratory and Seed and Plant Breeding Laboratory, Faculty of Agriculture, University of Lampung in July 2021 – November 2021. This experiment was arranged in a Completely Randomized Design (CRD) with 3 replications and then continued with data analysis in the form of linear analysis, analysis of diversity , and significance test. The observed variables included flowering age, pod color, pod harvesting age, pod length, pod diameter, number of seeds per pod, sugar content, number of productive branches, number of good pods, total number of seeds, and distance between locules. The results showed that the pod length and the number of seeds per pod (r = 0.66). Total pod weight was positively correlated with the number of productive branches (r = 0.83), the number of good pods (r = 0.96), and the total number of pods (r = 0.96). The number of productive branches correlated positively with the number of good pods (r = 0.87) and the total number of pods (r = 0.86). The number of good pods variable has a positive correlation with the total number of pods (r = 0.98). The Cantonese Tavi variety has an advantage in the number of good pods produced in an organic environment. Keywords: Correlation, Organic Environment.

Formation of biometric parameters of sowings of soybean variety ‘Sirelia’ on typical chernozems depending on the nutrition area

Purpose. To determine the effect of row width and seeding rate on the biometric parameters of sowings of the early-ripening soybean variety 'Sirelia'. Methods. The research was carried out in 2021–2023 in the stationary crop rotation of the Plant Breeding Department in the fields of the Agronomic Research Station of the National University of Life and Environmental Sciences of Ukraine (Pshenychne, Vasylkiv district, Kyiv region). Scheme of the experiment: factor A – sowing method: ordinary row with a row spacing of 19 cm; strip with a row spacing of 19 × 38 × 12 cm; wide-row with a row spacing of 38 cm; factor B – seeding rate: 450, 600 and 750 thousand seeds/ha. Recordings were carried out in the main phases of crop development: budding, flowering and grain filling. Results. The thickening of crops with an increase in the seeding rate from 450 to 750 thousand seeds/ha contributed to a significant increase in the height of soybean plants: by 3.5 cm for row spacings of 19 cm and by 5.9 cm for row spacing of 38 cm. Seeding rate of 450,000 seeds/ha led to a decrease in plant height by 4.1 cm, or 5.2%. Thus, from the given data it can be concluded that the height of soybean plants increased with an increase in the seeding rate. The influence of the sowing rate on the growth of plants at a row width of 38 cm was particularly significant. The absolute dry mass of plants in the budding phase was within the range of 2.87–4.00 g, in the flowering stage 4.81–6.93 g, and in the seed filling stage 11.6–21.5 g. During the last period, the mass of plants in the case of increasing the seeding rate from 450 to 750 thousand seeds/ha decreased by 8.9 g, for a row spacing of 19 cm, and for a row spacing 38 cm by 7.3 g. The highest mass of plants was for the row width of 38 cm and the sowing rate of 450,000 seeds/ha. Conclusions. The height of soybean plants increases with an increase in the seeding rate. This is explained by the fact that the thickening of crops causes shading and elongation of plants. Soybean plants were the highest (81.9 cm) at a row spacing of 38 cm and a seeding rate of 750,000 seeds/ha. The highest absolute dry weight of one soybean plant was formed at a seeding rate of 450,000 seeds/ha, and significantly decreases in case of its increase to 750 thousand seeds/ha for all methods of sowing. That is, the thickening of crops with an increase in the seeding rate from 450 to 750 thousand units/ha led to a significant decrease in the dry weight of plants, which is explained by the deterioration of the conditions for their growth and development, primarily due to high competition for life factors.

Ensemble learning for integrative prediction of genetic values with genomic variants

BackgroundWhole genome variants offer sufficient information for genetic prediction of human disease risk, and prediction of animal and plant breeding values. Many sophisticated statistical methods have been developed for enhancing the predictive ability. However, each method has its own advantages and disadvantages, so far, no one method can beat others.ResultsWe herein propose an Ensemble Learning method for Prediction of Genetic Values (ELPGV), which assembles predictions from several basic methods such as GBLUP, BayesA, BayesB and BayesCπ, to produce more accurate predictions. We validated ELPGV with a variety of well-known datasets and a serious of simulated datasets. All revealed that ELPGV was able to significantly enhance the predictive ability than any basic methods, for instance, the comparison p-value of ELPGV over basic methods were varied from 4.853E−118 to 9.640E−20 for WTCCC dataset.ConclusionsELPGV is able to integrate the merit of each method together to produce significantly higher predictive ability than any basic methods and it is simple to implement, fast to run, without using genotype data. is promising for wide application in genetic predictions.

Stem–Leaf segmentation and phenotypic trait extraction of individual plant using a precise and efficient point cloud segmentation network

Rapid and precise 3D organ segmentation is crucial for the automatic extraction of phenotypic traits, forming a fundamental prerequisite for intelligent plant breeding. The advancement of deep learning technology has replaced labor-intensive manual measurements and traditional computer vision methods, which are sensitive to parameters, in phenotypic trait extraction. However, current larger network structures not only require extensive point cloud data but also consume substantial computational resources, rendering them unsuitable for agricultural tasks with limited plant samples. Therefore, this study developed a lightweight 3D deep learning network (PEPNet) that achieves precise plant organ segmentation and stem-leaf phenotypic trait extraction. The adopted simple-but-effective network architecture and innovative modern operations, including a high-dimensional feature mapping strategy for preprocessing input points, a local feature extraction module based on inverted residual bottleneck block, and a cost-free attention block for spatial feature fusion, effectively implement multi-scale hierarchies and adaptively reduce computational overheads. Experimental results from cotton stem-leaf segmentation demonstrated that PEPNet not only presented approximately 2 × faster inference speed (9.59 ms) and throughput (146.32 plants per second) but also achieved competitive segmentation performance compared to other six state-of-the-art deep learning networks, namely PointNet++, DGCNN, CurveNet, Point Cloud Transformer, PointMLP, and SPoTr, achieving 95.99 %, 94.66 %, 95.32 %, and 91.31 % in Precision, Recall, F1-score, and mIoU, respectively. In transferability experiments with tomato and soybean plants, PEPNet achieved almost all the best metrics and significantly outperformed the second-best model (CurveNet). Furthermore, ablation study verified the optimal trade-off between efficiency and accuracy in this network. Any modifications to the modules could potentially disrupt the optimal trade-off. This work could contribute to reducing computational resources and annotation costs for applying segmentation methods in high-throughput phenotyping tasks.

Genetic Variation of Foxtail Millet (Setaria italica (L.) P. Beauv.) Germplasm From Polewali Mandar West Sulawesi Based On Morphological Characters

Foxtail millet (Setaria italica (L.) P. Beauv.) is a cereal crop that has long been domesticated worldwide and has been adopted as a model crop to provide a deeper understanding of plant biology. This plant has long been a mainstay of indigenous Indonesian people, especially in Polewali Mandar, West Sulawesi Province. This study aims to evaluate the genetic variation of foxtail millet germplasm from Polewali Mandar, West Sulawesi based on morphological characters. Three germplasm populations were collected from Polewali Mandar to assess genetic variation in millet germplasm. The observations of morphological traits were carried out based on the IBPGR of Setaria italica. Genetic variation in foxtail millet populations was measured using 28 morphological traits with nine qualitative and 19 quantitative characters. The research showed that seed color, stem diameter, plant height, panicle stalk length, and panicle stalk diameter had diverse variations. Cluster analysis of morphological characters using the UPGMA method shows a similarity coefficient ranging from 0.15-0.2. At a genetic similarity coefficient of 0.2, the three populations were divided into Cluster A and Cluster B. Cluster A consists of two populations (Minna' and Lasse'). In contrast, Cluster B consists of one population (Bulawang). The millet population SLB.C.3-SLB.A.1 has the highest genetic distance and is a potential candidate to be selected as a parent cross to produce higher het-erosis. Intensification of millet plant breeding programs is expected to increase the genetic basis for determining specific characteristics.

Phenotyping in Rye Landrace and Regeneration Frequency Study in Wheat × Rye F1 Hybrid Seeds

The present research aimed to study the phenotyping characterization of a high-altitude Himalayan rye landrace and its crossability with wheat genotypes and investigate the regeneration frequency of wheat × rye F1 hybrid seeds. The study was conducted during the rabi season of 2022-2023 at the Agriculture Research Farm, Department of Plant Breeding and Genetics, Lovely Professional University, Phagwara, Punjab. The phenotypic characterization of the Himalayan rye landrace revealed several adaptive traits that were found suitable for cultivation in the northwest Indo-Gangetic plains. Furthermore, the study investigated the crossability of the Himalayan rye landrace with various wheat genotypes, including 4 genotypes of bread wheat HD2967, UNNAT 343, WH1105, and PBW502 and 4 genotypes of durum wheat PDW291, PDW274, PBW34, and WHD943. Among the germination percentage of all 8 genotypes, 4 in Bread wheat and 4 in Durum wheat was observed. Due to its self-incompatibility, Rye cannot be used to develop inbred lines directly. However, the doubled haploid approach can produce inbred lines in the rye, facilitating the extension of genetic bases and introducing alien chromatin to identify stress tolerances.

Exploitation of the microbiome for crop breeding.

Exploitation of the microbiome for crop breeding.

Cloning, Expression, and Functional Characterization of Two Highly Efficient Flavonoid-di-O-glycosyltransferases ZmUGT84A1 and ZmUGT84A2 from Maize (Zea mays L.).

The maize (Zea mays L.) glycosyltransferase family 1 comprises many uridine diphosphate glycosyltransferase (UGT) members. However, UGT activities and biochemical functions have seldom been revealed. In this study, the genes of two flavonoid di-O-glycosyltransferases ZmUGT84A1 and ZmUGT84A2 were cloned from maize plant and expressed in Escherichia coli. Phylogenetic analysis showed that the two enzymes were homologous to AtUGT84A1 and AtUGT84A3. The two recombinant enzymes showed a high conversion rate of luteolin to its glucosides, mainly 4',7-di-O-glucoside and minorly 3',7-di-O-glucoside in two-step glycosylation reactions in vitro. Moreover, the recombinant ZmUGT84A1 and ZmUGT84A2 had a broad substrate spectrum, converting eriodictyol, naringenin, apigenin, quercetin, and kaempferol to monoglucosides and diglucosides. The highly efficient ZmUGT84A1 and ZmUGT84A2 may be used as a tool for the effective synthesis of various flavonoid O-glycosides and as markers for crop breeding to increase O-glycosyl flavonoid content in food.