Applications In Plant Breeding Research Articles

Identification and functional analysis of floral terpene synthase genes in Curcuma alismatifolia.

CaTPS2 and CaTPS3 were significantly expressed in flowers of Curcuma alismatifolia 'Shadow' and demonstrated bifunctional enzyme activity, CaTPS2 generated linalool and nerolidol as products, and CaTPS3 catalyzed β-myrcene and β-farnesene formation. This study presents the discovery and functional characterization of floral terpene synthase (TPS) genes in Curcuma alismatifolia 'Shadow', a cultivar renowned for its unique fragrance. Addressing the gap in understanding the genetic basis of floral scent in this species, we identified eight TPS genes through comprehensive transcriptome sequencing. Among these, CaTPS2 and CaTPS3 were significantly expressed in floral tissues and demonstrated bifunctional enzyme activity corresponding to the major volatile compounds detected in 'Shadow'. Functional analyses, including in vitro assays complemented with rigorous controls and alternative identification methods, elucidated the roles of these TPS genes in terpenoid biosynthesis. In vitro studies were conducted via heterologous expression in E. coli, followed by purification of the recombinant protein using affinity chromatography, enzyme assays were performed with GPP/FPP as the substrate, and volatile products were inserted into the GC-MS for analysis. Partially purified recombinant protein of CaTPS2 catalyzed GPP and FPP to produce linalool and nerolidol, respectively, while partially purified recombinant protein of CaTPS3 generated β-myrcene and β-farnesene with GPP and FPP as substrates, respectively. Real-time quantitative PCR further validated the expression patterns of these genes, correlating with terpenoid accumulation in different plant tissues. Our findings illuminate the molecular mechanisms underpinning floral fragrance in C. alismatifolia and provide a foundation for future genetic enhancements of floral scent in ornamental plants. This study, therefore, contributes to the broader understanding of terpenoid biosynthesis in plant fragrances, paving the way for biotechnological applications in horticulture plant breeding.

KASP: a high-throughput genotyping system and its applications in major crop plants for biotic and abiotic stress tolerance.

Advances in plant molecular breeding have resulted in the development of new varieties with superior traits, thus improving the crop germplasm. Breeders can screen a large number of accessions without rigorous and time-consuming phenotyping by marker-assisted selection (MAS). Molecular markers are one of the most imperative tools in plant breeding programmes for MAS to develop new cultivars possessing multiple superior traits. Single nucleotide polymorphisms (SNPs) are ideal for MAS due to their low cost, low genotyping error rates, and reproducibility. Kompetitive Allele Specific PCR (KASP) is a globally recognized technology for SNP genotyping. KASP is an allele-specific oligo extension-based PCR assay that uses fluorescence resonance energy transfer (FRET) to detect genetic variations such as SNPs and insertions/deletions (InDels) at a specific locus. Additionally, KASP allows greater flexibility in assay design, which leads to a higher success rate and the capability to genotype a large population. Its versatility and ease of use make it a valuable tool in various fields, including genetics, agriculture, and medical research. KASP has been extensively used in various plant-breeding applications, such as the identification of germplasm resources, quality control (QC) analysis, allele mining, linkage mapping, quantitative trait locus (QTL) mapping, genetic map construction, trait-specific marker development, and MAS. This review provides an overview of the KASP assay and emphasizes its validation in crop improvement related to various biotic and abiotic stress tolerance and quality traits.

Genome-Wide Analysis of the Oat (Avena sativa) HSP90 Gene Family Reveals Its Identification, Evolution, and Response to Abiotic Stress.

Oats (Avena sativa) are an important cereal crop and cool-season forage worldwide. Heat shock protein 90 (HSP90) is a protein ubiquitously expressed in response to heat stress in almost all plants. To date, the HSP90 gene family has not been comprehensively reported in oats. Herein, we have identified twenty HSP90 genes in oats and elucidated their evolutionary pathways and responses to five abiotic stresses. The gene structure and motif analyses demonstrated consistency across the phylogenetic tree branches, and the groups exhibited relative structural conservation. Additionally, we identified ten pairs of segmentally duplicated genes in oats. Interspecies synteny analysis and orthologous gene identification indicated that oats share a significant number of orthologous genes with their ancestral species; this implies that the expansion of the oat HSP90 gene family may have occurred through oat polyploidization and large fragment duplication. The analysis of cis-acting elements revealed their influential role in the expression pattern of HSP90 genes under abiotic stresses. Analysis of oat gene expression under high-temperature, salt, cadmium (Cd), polyethylene glycol (PEG), and abscisic acid (ABA) stresses demonstrated that most AsHSP90 genes were significantly up-regulated by heat stress, particularly AsHSP90-7, AsHSP90-8, and AsHSP90-9. This study offers new insights into the amplification and evolutionary processes of the AsHSP90 protein, as well as its potential role in response to abiotic stresses. Furthermore, it lays the groundwork for understanding oat adaptation to abiotic stress, contributing to research and applications in plant breeding.

Why should we study plant sex chromosomes?

Understanding plant sex chromosomes involves studying interactions between developmental and physiological genetics, genome evolution, and evolutionary ecology. We focus on areas of overlap between these. Ideas about how species with separate sexes (dioecious species, in plant terminology) can evolve are even more relevant to plants than to most animal taxa because dioecy has evolved many times from ancestral functionally hermaphroditic populations, often recently. One aim of studying plant sex chromosomes is to discover how separate males and females evolved from ancestors with no such genetic sex-determining polymorphism, and the diversity in the genetic control of maleness vs femaleness. Different systems share some interesting features, and their differences help to understand why completely sex-linked regions may evolve. In some dioecious plants, the sex-determining genome regions are physically small. In others, regions without crossing over have evolved sometimes extensive regions with properties very similar to those of the familiar animal sex chromosomes. The differences also affect the evolutionary changes possible when the environment (or pollination environment, for angiosperms) changes, as dioecy is an ecologically risky strategy for sessile organisms. Dioecious plants have repeatedly reverted to cosexuality, and hermaphroditic strains of fruit crops such as papaya and grapes are desired by plant breeders. Sex-linked regions are predicted to become enriched in genes with sex differences in expression, especially when higher expression benefits one sex function but harms the other. Such trade-offs may be important for understanding other plant developmental and physiological processes and have direct applications in plant breeding.

Salinity-driven changes in Salicornia cell wall nanomechanics and lignin composition

Widespread increases in soil salinization significantly reduce agricultural lands. Nevertheless, salt-tolerant plants, such as Salicornia europaea L., can play a crucial role in the reclamation of these lands. We selected S. europaea for this study due to its potential to mitigate soil salinization and its numerous applications, such as intercropping in agriculture, biocompounds production and bioenergy. This work was designed to determine whether different salinities induce significant biophysical, anatomical, lignin and gene transcript changes in S. europaea. Through atomic force microscopy (AFM), we revealed that salinity stimulated an increase in cell wall elasticity (CWE) as an important physiological mechanism of adaptation known as cell’s turgor conservation effect. Direct values of the cell wall stiffness subjected to salinity were obtained, with Young’s modulus (E) ranging from low and high salinity 0.52 to 0.03 MPa. The softening of the cell wall properly correlated with an increase in cell size, plant cells under strong salinity 1000 mM NaCl, swelled 5.4 times. The best salinity range found for its optimum growth was 200–400 mM NaCl. At higher salinities, we identified increases in the lignified xylem, large calcium oxalate crystals, and in transcript amounts of SeSOS1 and SeNHX1, which has a significant negative correlation with cell wall stiffness (−0.57 and −0.95, respectively). The high syringyl and guaiacyl ratio (S/G) in lignin for 0–400 mM NaCl may have influenced the rigidity and hydrophobicity of the cell walls. A positive S/G ratio and sugar yields are associated with higher bioethanol production, these values may also be useful for agriculture, biorefinery, biocompounds and plant-breeding applications. We conclude that salinity indeed influenced the cell wall traits of S. europaea. This halophyte is capable of markedly softening its cell wall as a way of adapting to the high level of salinity. Our presented insights and correlations not only provide a better understanding of cell wall remodelling but are also considered vital traits of adaptation strategies that this halophyte holds under salinity environment. These inputs can also be applied in future research aiming to produce biomass and biofuel or to improve the salinity tolerance during the cultivation of non-tolerant plants, crops and glycophytes, which is a significant challenge in agriculture, particularly in arid and coastal regions. The unique properties of the S. europaea cell walls could also inspire the development of materials with enhanced nanomechanical elasticity for resistance to osmotic stress.

Microbiome-enabled genomic selection improves prediction accuracy for nitrogen-related traits in maize.

Root-associated microbiomes in the rhizosphere (rhizobiomes) are increasingly known to play an important role in nutrient acquisition, stress tolerance, and disease resistance of plants. However, it remains largely unclear to what extent these rhizobiomes contribute to trait variation for different genotypes and if their inclusion in the genomic selection protocol can enhance prediction accuracy. To address these questions, we developed a microbiome-enabled genomic selection method that incorporated host SNPs and amplicon sequence variants from plant rhizobiomes in a maize diversity panel under high and low nitrogen (N) field conditions. Our cross-validation results showed that the microbiome-enabled genomic selection model significantly outperformed the conventional genomic selection model for nearly all time-series traits related to plant growth and N responses, with an average relative improvement of 3.7%. The improvement was more pronounced under low N conditions (8.4-40.2% of relative improvement), consistent with the view that some beneficial microbes can enhance N nutrient uptake, particularly in low N fields. However, our study could not definitively rule out the possibility that the observed improvement is partially due to the amplicon sequence variants being influenced by microenvironments. Using a high-dimensional mediation analysis method, our study has also identified microbial mediators that establish a link between plant genotype and phenotype. Some of the detected mediator microbes were previously reported to promote plant growth. The enhanced prediction accuracy of the microbiome-enabled genomic selection models, demonstrated in a single environment, serves as a proof-of-concept for the potential application of microbiome-enabled plant breeding for sustainable agriculture.

Genome Editing of Plant Mitochondrial and Chloroplast Genomes.

Plastids (including chloroplasts) and mitochondria are remnants of endosymbiotic bacteria, yet they maintain their own genomes, which encode vital components for photosynthesis and respiration, respectively. Organellar genomes have distinctive features, such as being present as multicopies, being mostly inherited maternally, having characteristic genomic structures and undergoing frequent homologous recombination. To date, it has proven to be challenging to modify these genomes. For example, while CRISPR/Cas9 is a widely used system for editing nuclear genes, it has not yet been successfully applied to organellar genomes. Recently, however, precise gene-editing technologies have been successfully applied to organellar genomes. Protein-based enzymes, especially transcription activator-like effector nucleases (TALENs) and artificial enzymes utilizing DNA-binding domains of TALENs (TALEs), have been successfully used to modify these genomes by harnessing organellar-targeting signals. This short review introduces and discusses the use of targeted nucleases and base editors in organellar genomes, their effects and their potential applications in plant science and breeding.

Metabolic profiles of peanut (Arachis hypogaea L.) in response to Puccinia arachidis fungal infection

Background Puccinia arachidis fungus causes rust disease in the peanut plants (Arachis hypogaea L.), which leads to high yield loss. Metabolomic profiling of Arachis hypogaea was performed to identify the pathogen-induced production of metabolites involved in the defense mechanism of peanut plants. In this study, two peanut genotypes, one susceptible (JL-24) and one resistant (GPBD-4) were inoculated with Puccinia arachidis fungal pathogen. The metabolic response was assessed at the control stage (0 day without inoculation), 2 DAI (Day after inoculation), 4 DAI and 6 DAI by Gas Chromatography-Mass Spectrometry (GC-MS). Results About 61 metabolites were identified by NIST library, comprising sugars, phenols, fatty acids, carboxylic acids and sugar alcohols. Sugars and fatty acids were predominant in leaf extracts compared to other metabolites. Concentration of different metabolites such as salicylic acid, mannitol, flavonoid, 9,12-octadecadienoic acid, linolenic acid and glucopyranoside were higher in resistant genotype than in susceptible genotype during infection. Systemic acquired resistance (SAR) and hypersensitive reaction (HR) components such as oxalic acid was elevated in resistant genotype during pathogen infection. Partial least square-discriminant analysis (PLS-DA) was applied to GC-MS data for revealing metabolites profile between resistant and susceptible genotype during infection. Conclusion The phenol content and oxidative enzyme activity i.e. catalase, peroxidase and polyphenol oxidase were found to be very high at 4 DAI in resistant genotype (p-value < 0.01). This metabolic approach provides information about bioactive plant metabolites and their application in crop protection and marker-assisted plant breeding.

Ectopic expression of PmGRF7 isolated from Japanese apricot in tomato leads to seed sterility

The role of GRF (Growth-regulating Factor) in regulating plant growth and development has been studied, but its potential role in regulating seed fertility remains unclear. PmGRF7 overexpression in tomatoes altered leaf morphology and pollen activity. Most importantly, genetically modified tomato plants had no offspring. PmGRF7 overexpression resulted in abnormal leaf morphology, and transgenic plants that produced seedless fruit or seeds only showed signs of abortion. Pollination of genetically modified tomatoes with wild-type tomato pollen still produced sterile seeds. Further research using bioinformatics tools and physiological index measurement showed that PmGRF7 induced a hormone pathway leading to seed sterility, and at the same time, it caused differential genes to be induced in the plant hormone signal transduction pathway, ribosome pathway, sphingolipid metabolism and other related pathways, leading to morphogenesis in plant leaves. Collectively, our research findings reveal a potential new mechanism by which PmGRF7 regulates seed fertility and leaf growth, and these findings are of potential application in molecular plant breeding.

In vitro Regeneration of Multiple Shoots in Abelmoschus esculentus (L.) Moench (Okra) via Apical Shoot Meristem Culture

Introduction: To develop the efficient protocol for multiple shoot regeneration of A.esculentus by apical root culture method. Abelmoschus esculentus L., commonly known as okra, is a member of the Malvaceae family, which is widely consumed due to its high nutrient content and potential therapeutic properties. Okra contains various bioactive compounds that ex-hibit antibacterial properties and may be useful in treating type-2 diabetes, digestive diseases, and liver detoxification. To select the plant for the present and prepare the efficient protocol for the development of multiple shoot regeneration culture method. Methods: In this study, we developed an efficient protocol for multiple shoot regeneration of A. esculentus using the apical shoot culture method. Mature shoot apex explants of the germinated A. esculentus genotype CoBhH1 were cultured on Murashige and Skoog (MS) medium supple-mented with different concentrations of cytokinins (BAP and TDZ) and auxins (IAA and NAA) to determine the optimal conditions for shoot induction. Results: The highest number of multiple shoots (27.04 shoots) was obtained with 0.8 mg/L TDZ. Excised shoots were cultured on MS medium supplemented with GA3, which induced elongation of the shoots to a maximum of 8-10 cm. Regenerated plantlets were successfully transferred to soil, with a 100% survival rate and no differences in morphology or growth characteristics com-pared to control plants. Rooting was achieved with 1 mg/L IBA. Conclusion: This study provides an efficient protocol for multiple shoot regeneration of A. esculentus through apical shoot culture, which has potential applications in plant breeding and genetic engineering.

Genome-wide identification and characterization of glutathione S-transferase gene family in quinoa (Chenopodium quinoa Willd.).

The present investigation was envisaged for large scale in-silico genome wide identification and characterization of glutathione S-transferases (GSTs) in Chenopodium quinoa. In this study, a total of 120 GST genes (CqGSTs) were identified and divided into 11 classes of which tau and phi were highest in numbers. The average protein length of protein was found to be 279.06 with their corresponding average molecular weight of 31,819.4kDa. The subcellular localization analysis results showed that proteins were centrally localized in the cytoplasm followed by chloroplast, mitochondria and plastids. Structural analysis revealed the presence of 2 -14 exons in CqGST genes. Most of the proteins possessed two exon one intron organization. MEME analysis identified 15 significantly conserved motifs with a width of 6-50 amino acids. Motifs 1, 3, 2, 5, 6, 8, 9 and 13 were found specifically in tau class family; motifs 3, 4, 5, 6, 7 and 9 were found in phi class gene family, while motifs 3, 4, 13 and 14 were found in metaxin class. Multiple sequence alignment revealed highly conserved N-terminus with active site serine (Ser; S) or cysteine (Cys; C) residue for the activation of GSH binding and GST catalytic activity. The gene loci were found to be unevenly distributed across 18 different chromosomes with a maximum of 17 genes located on chromosome number 7. Dominance of alpha helix was followed by coil, extended strand and beta turns. Gene duplication analysis revealed that segmental duplication and purifying type selection were highest in number and found to be main source of expansion of GST gene family. Cis acting regulatory elements analysis showed the presence of 21 different elements involved in stress, hormone and light response and cellular development. The evolutionary relationship of CqGST proteins carried out using maximum likelihood method revealed that all the tau and phi class GSTs were closely associated with those of G. max, O. sativa and A. thaliana. Molecular docking of GST molecules with the fungicide metalaxyl showed that the CqGSTF1 had the lowest binding energy. The comprehensive study of CqGST gene family in quinoa provides groundwork for further functional analysis of CqGST genes in the species at molecular level and has potential applications in plant breeding.

Chemical emasculation in cowpea (Vigna unguiculata (L.) Walp.) and dicotyledonous model species using trifluoromethanesulfonamide (TFMSA)

Hybridization plays an indispensable role in creating the diversity associated with plant evolution and genetic improvement of crops. Production of hybrids requires control of pollination and avoidance of self-pollination for species that are predominantly autogamous. Hand emasculation, male sterility genes or male gametocides have been used in several plant species to induce pollen sterility. However, in cowpea (Vigna unguiculata (L.) Walp), a self-pollinated cleistogamous dryland crop, only hand emasculation is used, but it is tedious and time-consuming. In this study, male sterility was effectively induced in cowpea and two dicotyledonous model species (Arabidopsis thaliana (L.) Heynh. and Nicotiana benthamiana Domin) using trifluoromethanesulfonamide (TFMSA). Pollen viability assays using Alexander staining showed that 30 ml of 1000 mg/l TFMSA with two-time treatments of one-week interval at the early stage of the reproductive phase under field or greenhouse conditions induced 99% pollen sterility in cowpea. TFMSA treatment induced non-functional pollen in diploid A. thaliana at two-time treatment of 10 ml of 125–250 mg/l per plant and N. benthamiana at two-time treatment of 10 ml of 250–1000 mg/l per plant. TFMSA-treated cowpea plants produced hybrid seeds when used as the female parent in crosses with non-treated plants used as male parents, suggesting that TFMSA had no effect on female functionality in cowpea. The ease of TFMSA treatment and its effectiveness to induce pollen sterility in a wide range of cowpea genotypes, and in the two model plant species tested in this study, may expand the scope of techniques for rapid pollination control in self-pollinated species, with potential applications in plant breeding and plant reproduction science.

Unveiling the Mysteries of Non-Mendelian Heredity in Plant Breeding.

Mendelian heredity is the cornerstone of plant breeding and has been used to develop new varieties of plants since the 19th century. However, there are several breeding cases, such as cytoplasmic inheritance, methylation, epigenetics, hybrid vigor, and loss of heterozygosity (LOH), where Mendelian heredity is not applicable, known as non-Mendelian heredity. This type of inheritance can be influenced by several factors besides the genetic architecture of the plant and its breeding potential. Therefore, exploring various non-Mendelian heredity mechanisms, their prevalence in plants, and the implications for plant breeding is of paramount importance to accelerate the pace of crop improvement. In this review, we examine the current understanding of non-Mendelian heredity in plants, including the mechanisms, inheritance patterns, and applications in plant breeding, provide an overview of the various forms of non-Mendelian inheritance (including epigenetic inheritance, cytoplasmic inheritance, hybrid vigor, and LOH), explore insight into the implications of non-Mendelian heredity in plant breeding, and the potential it holds for future research.

"Canopy fingerprints" for characterizing three-dimensional point cloud data of soybean canopies.

Advances in imaging hardware allow high throughput capture of the detailed three-dimensional (3D) structure of plant canopies. The point cloud data is typically post-processed to extract coarse-scale geometric features (like volume, surface area, height, etc.) for downstream analysis. We extend feature extraction from 3D point cloud data to various additional features, which we denote as 'canopy fingerprints'. This is motivated by the successful application of the fingerprint concept for molecular fingerprints in chemistry applications and acoustic fingerprints in sound engineering applications. We developed an end-to-end pipeline to generate canopy fingerprints of a three-dimensional point cloud of soybean [Glycine max (L.) Merr.] canopies grown in hill plots captured by a terrestrial laser scanner (TLS). The pipeline includes noise removal, registration, and plot extraction, followed by the canopy fingerprint generation. The canopy fingerprints are generated by splitting the data into multiple sub-canopy scale components and extracting sub-canopy scale geometric features. The generated canopy fingerprints are interpretable and can assist in identifying patterns in a database of canopies, querying similar canopies, or identifying canopies with a certain shape. The framework can be extended to other modalities (for instance, hyperspectral point clouds) and tuned to find the most informative fingerprint representation for downstream tasks. These canopy fingerprints can aid in the utilization of canopy traits at previously unutilized scales, and therefore have applications in plant breeding and resilient crop production.

Plant breeding advancements with "CRISPR-Cas" genome editing technologies will assist future food security.

Genome editing techniques are being used to modify plant breeding, which might increase food production sustainably by 2050. A product made feasible by genome editing is becoming better known, because of looser regulation and widespread acceptance. The world's population and food supply would never have increased proportionally under current farming practices. The development of plants and food production has been greatly impacted by global warming and climate change. Therefore, minimizing these effects is crucial for agricultural production that is sustainable. Crops are becoming more resilient to abiotic stress because of sophisticated agricultural practices and a better understanding of the abiotic stress response mechanism. Both conventional and molecular breeding techniques have been used to create viable crop types both processes are time-consuming. Recently, plant breeders have shown an interest in genome editing approaches for genetic manipulation that use clustered regularly interspaced short palindromic repeats (CRISPR/Cas9). To ensure the security of the food supply in the future, plant kinds with desired traits must be developed. A completely new era in plant breeding has begun because of the revolution in genome editing techniques based on the CRISPR/CRISPR-associated nuclease (Cas9) systems. All plants may effectively target a particular gene or group of loci using Cas9 and single-guide RNA (sgRNA). CRISPR/Cas9 can thereby save time and labor compared to conventional breeding methods. An easy, quick, and efficient method for directly altering the genetic sequences in cells is with the CRISPR and Cas9 systems. The CRISPR-Cas9 system, which was developed from components of the earliest known bacterial immune system, allows for targeted gene breakage and gene editing in a variety of cells/RNA sequences to guide endonuclease cleavage specificity in the CRISPR-Cas9 system. Editing can be directed to practically any genomic site by altering the guide RNA (gRNA) sequence and delivering it to a target cell along with the Cas9 endonuclease. We summarize recent CRISPR/Cas9 plant research findings, investigate potential applications in plant breeding, and make predictions about likely future breakthroughs and approaches to food security through 2050.

Molecular Markers in Plant Breeding

Molecular markers are an important tool for plant breeding. Since the 1980s, in response to the technology development, molecular marker approaches have been further diversified. The establishment of new-generation sequencing and high-throughput plant phenotyping has greatly decreased the time to genotype large numbers of individuals. For breeders who are not very familiar with molecular techniques and want to catch up with the advances in the field, this review offers basic knowledge. Each molecular marker technology has specific advantages as well as limitations. Molecular marker types, diversity studies, QTL mapping, associative mapping, marker-assisted backcrossing and genomic selection are explored. Marker application in plant breeding is also described. In the genome, molecular markers can detect the genetic architecture of a trait, but also identify candidate genes with an important role in plant breeding programs.

Machine learning bridges omics sciences and plant breeding.

Some of the biological knowledge obtained from fundamental research will be implemented in applied plant breeding. To bridge basic research and breeding practice, machine learning (ML) holds great promise to translate biological knowledge and omics data into precision-designed plant breeding. Here, we review ML for multi-omics analysis in plants, including data dimensionality reduction, inference of gene-regulation networks, and gene discovery and prioritization. These applications will facilitate understanding trait regulation mechanisms and identifying target genes potentially applicable to knowledge-driven molecular design breeding. We also highlight applications of deep learning in plant phenomics and ML in genomic selection-assisted breeding, such as various ML algorithms that model the correlations among genotypes (genes), phenotypes (traits), and environments, to ultimately achieve data-driven genomic design breeding.

Point Cloud Completion of Plant Leaves under Occlusion Conditions Based on Deep Learning.

The utilization of 3-dimensional point cloud technology for non-invasive measurement of plant phenotypic parameters can furnish important data for plant breeding, agricultural production, and diverse research applications. Nevertheless, the utilization of depth sensors and other tools for capturing plant point clouds often results in missing and incomplete data due to the limitations of 2.5D imaging features and leaf occlusion. This drawback obstructed the accurate extraction of phenotypic parameters. Hence, this study presented a solution for incomplete flowering Chinese Cabbage point clouds using Point Fractal Network-based techniques. The study performed experiments on flowering Chinese Cabbage by constructing a point cloud dataset of their leaves and training the network. The findings demonstrated that our network is stable and robust, as it can effectively complete diverse leaf point cloud morphologies, missing ratios, and multi-missing scenarios. A novel framework is presented for 3D plant reconstruction using a single-view RGB-D (Red, Green, Blue and Depth) image. This method leveraged deep learning to complete localized incomplete leaf point clouds acquired by RGB-D cameras under occlusion conditions. Additionally, the extracted leaf area parameters, based on triangular mesh, were compared with the measured values. The outcomes revealed that prior to the point cloud completion, the R2 value of the flowering Chinese Cabbage's estimated leaf area (in comparison to the standard reference value) was 0.9162. The root mean square error (RMSE) was 15.88 cm2, and the average relative error was 22.11%. However, post-completion, the estimated value of leaf area witnessed a significant improvement, with an R2 of 0.9637, an RMSE of 6.79 cm2, and average relative error of 8.82%. The accuracy of estimating the phenotypic parameters has been enhanced significantly, enabling efficient retrieval of such parameters. This development offers a fresh perspective for non-destructive identification of plant phenotypes.

Rapid online plant leaf area change detection with high-throughput plant image data

High-throughput plant phenotyping (HTPP) has become an emerging technique to study plant traits due to its fast, labor-saving, accurate and non-destructive nature. It has wide applications in plant breeding and crop management. However, the resulting massive image data has raised a challenge associated with efficient plant traits prediction and anomaly detection. In this paper, we propose a two-step image-based online detection framework for monitoring and quick change detection of the individual plant leaf area via real-time imaging data. Our proposed method is able to achieve a smaller detection delay compared with some baseline methods under some predefined false alarm rate constraint. Moreover, it does not need to store all past image information and can be implemented in real time. The efficiency of the proposed framework is validated by a real data analysis.

Bioinformatics in Plant Breeding and Research on Disease Resistance.

In the context of plant breeding, bioinformatics can empower genetic and genomic selection to determine the optimal combination of genotypes that will produce a desired phenotype and help expedite the isolation of these new varieties. Bioinformatics is also instrumental in collecting and processing plant phenotypes, which facilitates plant breeding. Robots that use automated and digital technologies to collect and analyze different types of information to monitor the environment in which plants grow, analyze the environmental stresses they face, and promptly optimize suboptimal and adverse growth conditions accordingly, have helped plant research and saved human resources. In this paper, we describe the use of various bioinformatics databases and algorithms and explore their potential applications in plant breeding and for research on plant disease resistance.