In this post-genomic era, we now have easy access to the genetic information of entire living organisms, and that information has been essential for biological research. The prosperity of genomics resulted from the progress of DNA sequence technologies, the development of computational analysis environments, and the establishment of biological resources. Plant genomics is one of the research fields that has strongly benefited from these technical advances. This chapter presents the evolution and transition of DNA sequence technologies and gives concrete examples of the proliferation in plant genomic research.

Epigenetic regulation is highly conserved in eukaryotes. In general, events mediated by the genome – such as the regulation of gene activity and establishment and arrangement of chromatin structure – are coordinated by epigenetic and chromatin-remodeling factors. The concept of epigenetics was coined by Waddington (1957). In the context of embryogenesis, cells are affected by particular circumstances during development. This idea involves the possibility of “epi” factors that determine cell fate (“epi” is a Greek prefix meaning “external action or effect”). Currently, the definition of epigenetics remains interpretive in various contexts; however, the concept is based on “heritable phenotype changes that do not involve alterations in DNA sequence” and involves “nonheritable chromatin-level regulation that does not involve alterations in DNA sequence.” In this chapter, the basic concepts of genome-wide regulation of histone modifications and DNA methylation – known as epigenetic and chromatin regulatory factors – are the primary focus, with an emphasis on understanding the fundamental mechanisms of epigenetic regulation.

Recent progress of deep learning (DL) frameworks has allowed various high-quality classifications and regressions to be developed. Their performances have often exceeded human standards, especially in image diagnoses, so we may be able to reproduce artificial professional eyes for various objectives. Furthermore, recent development of explainable DL technology (or explainable AI (X-AI)), which can visualize the relevance of DL predictions, would allow biological interpretations of the predictions, potentially providing insights that only DL models may be able to recognize. Nevertheless, the application of DL frameworks has still progressed less in plant science than in animal, medical, and social sciences. In this chapter, mainly focused on classification and regression analyses, we introduce the current applications and potential prospects of DL technologies with respect to plant images and genetic sequences. Here, we take as examples taxonomic classification, disease/stress diagnosis, non-invasive prediction, and implementation with automated sorting systems based on plant images, as well as prediction of gene functions, such as expression patterns and protein folding structures, based on DNA or amino acid sequences. For beginners in the use of DL techniques, tips and precautions regarding practical application of DL frameworks are also provided.

Tomato (Lycopersicon esculentum) is the main vegetal crop that has tremendous popularity around the world. Medicago truncatula NOOT gene (Mt-NOOT) encodes a BTB/POZ-ankyrin repeat protein of the NONEXPRESSOR OF PR GENES1 (NPR1 family). It was introduced into Lycopersicon esculentum (Tomato) genome. The tomato plants that ectopically expressed Mt-NOOT obtained several favorable traits and fruit quality. Heteroblasty between the transgenic and the non-transgenic tomato leaves and flower architecture were used to distinguish transgenic and wild lines. Transgenic tomato plants accumulated a significant amount of phenolic compounds and plant pigmentations compared to the wild type. On the other hand, transgenic plants acquired a considerable amount of antioxidant such as CuZnSO superoxide dismutase (SOD), tomato Catalase (CAT), and tomato Cell wall-associated peroxidase (TPX1) than the wild type. Antioxidant high content together with the high content of phenolic compounds enabled the transgenic tomato fruits to gain not only edible benefits, but also a significant higher shelf-time, extended to six months more than the wild type stored at 25°C in dark and dry condition. Surprisingly, transgenic tomato fruits did not show any rotten process during long time storage as they did not acquire any contagious microorganism. Total fruit productivity in transgenic tomato was greater than the control with an estimated ratio of 84%.

Chemical seed treatment is a recommended technique to protect seeds from pathogens that can affect their quality. The objective of this work was to analyse the quality of soybean seeds with different treatments under different storage temperatures. Seeds of cultivar ‘M 8378 IPRO’ produced in Mato Grosso, Brazil were used. A completely randomised design was used in a 4 × 3 two-factorial scheme. The seeds were treated with three different combinations of chemicals (fungicides, insecticides, polymer and drying powder) in addition to the control (untreated seeds) combined with three different storage temperatures (13 °C, 19 °C and uncontrolled temperature), with three repetitions. Quality was assessed by the germination test (TG), accelerated aging (AA), field emergence (FE), tetrazolium test (TZ) and isoenzyme analysis. The uncontrolled storage temperature negatively influenced the variables germination, accelerated aging and field emergence. The vigour and viability of the tetrazolium test showed that untreated seeds had better physiological quality than seeds with chemical treatment. The expression of isoenzymes showed a difference between treatments. Even with the stress caused by the seed treatment, this tool is very important for the initial protection of the seedlings.

Phalaenopsis bellina, is an orchid widely known for their distinctive fragrance. Of late, fragrant orchids are getting more attention from Orchid breeders for their horticultural market value. Although volatile compounds have been identified in several orchid species, the floral scent emission of P. bellina is far from understood. Therefore, this study was carried out to investigate the influence of different timing and floral development stages on the volatile emissions from P. bellina flowers using Solid Phase Micro Extraction (SPME) and Gas Chromatography-Mass Spectrometry (GC-MS). The volatile compound was extracted during morning and afternoon sessions from three different floral developmental stages. The volatile compounds emitted from flowers from two different sessions were trapped with SPME fiber for 30 minutes before directly injected into GC-MS for identification. Results showed that approximately 79 volatile compounds were identified, with the terpenoid presented as the major compound class. P. bellina had the highest number of volatiles during the morning and full bloom (41), with 29.82% monoterpene and 23.33% sesquiterpenes accounted in total. α-farnesene (19.56%) was abundance during morning emission and remains as the highest volatile in afternoon emission (44.08%), even higher when compared to morning emission. However, a decrease in the volatile compound was observed in afternoon emission, in which only 34 volatile compounds detected. Meanwhile, partial bloom developmental stage revealed linalool as the major terpenoid volatile compounds (25.89%), with only 20 volatile compounds recorded. On the other hand, no volatile compounds were recorded and profiled from flower bud stage. The establishment of a floral scent study provides a brief overview of the regulation of fragrance in P. bellina, which can be continued through gene isolation or fragrance-related enzymes study. This information will provide necessary information on orchid floral scent research that useful in boosting horticultural trade of the scented orchids and their function in pollination ecology study

Maize (Zea mays L.) is the cereal most produced in the world, due to its wide scope and utilization in human and animal diet. This study aims to evaluate the agronomic performance of intervarietal maize hybrids, as well as the linear associations, interrelations of cause and effect, and the genotypes dispersion through canonical variates. The experiment was conducted in the agricultural year of 2014/2015. The crosses that originated the hybrids were carried out on the growing season of 2013/2014 and hybrids evaluated on 2014/2015. The hybrids were arranged in randomized blocks, being 13 treatments with five repetitions. The measured characters were: plant height, spike insertion height, stem diameter, spike diameter, spike length, spike mass, number of rows of grains per spike, number of grains per row, cob diameter, cob mass, spike grains mass, mass of a thousand grains, grain length and grain yield. The data were submitted to analysis of variance and mean values compared by the Tukey test at 5% of probability. The Pearson’s linear correlation analysis and path analysis were performed using grain yield as a dependent character. Furthermore, the analysis of canonical variables was carried out. The hybrid H5: G3 X G4 revealed higher grain yield, spike grains mass, number of grains per row and spike diameter. Grain yield of intervarietal hybrids presented positive correlations with the traits such as stem diameter, spike diameter, spike length, number of grains per row, mass of a thousand grains, grain length and spike grains mass. Spike diameter and spike length presented higher direct effects on grain yield of intervarietal hybrids. The canonical variates revealed the formation of five phenotypically distinct groups of intervarietal hybrids.

Plant chitinases are involved in defense as well as a wide range of physiological functions in plants, including germination, embryogenesis, flowering, and senescence. This study was conducted to identify and annotate the chitinase-related genes from the pigeonpea genome version 2.0, their chromosomal localization and phylogenetic relationship with chitinase genes from 13 different plant species. Here, we report the identification of 34 putative chitinase genes in the pigeonpea genome. These 34 genes encode proteins belonging to two functional domain families, and are subdivided into four classes matching four of the five chitinase classes in Arabidopsis. These chitinase genes are present in clusters on the chromosome. We investigated the expression patterns of these chitinases in 29 different tissues at five developmental stages. There was clear clustering of the chitinase genes into three groups based on their expression patterns in tissues. We identified two chitinase genes C_caj-24 and C_caj-25 that were highly expressed in all tissues as well as other chitinase genes with tissue-specific expression, which suggests that they play important roles in plant defense at specific developmental stages. This information on pigeonpea chitinases could be useful for the development of pigeonpea varieties that are resistant to insect pests and fungal diseases.

Heat and drought stresses are presently the principal risk on world's food quantity, limiting yield. Both of these two stresses affect plants metabolism, physiological and morphological processes, which ultimately reduces the productivity. The plant cell develops different stress induced self-defence mechanisms to reduce the effect of stresses. These defence mechanisms are developed by modifying gene expression pattern, which results in qualitative and quantitative deviations in proteins synthesis, leading to the modulation of certain metabolic and defensive pathways. New metabolic profiling technologies offer a great opportunity for biologist to understand defence mechanism of plants under stress conditions. Metabolomics technologies presently enabled the using of different multi-variate analyses, generated from various hyphenated and chromatographic discovery systems, such as gas or liquid chromatography together with mass spectrometry, or nuclear magnetic resonance (NMR) based methods. Investigation and mining of metabolomics data can be done through a blend of different statistical methods, such as independent component analysis and analysis of variance. Metabolomics in combination with gene expression, protein interaction and other different regulatory pathways can be useful to diverse organisms with trivial alterations. In recent time, this technology has been used to investigate drought tolerance in plant crops to find particular stress related patterns in metabolic expression. These studies identified the vital roles of primary and secondary metabolites associated with abiotic stress tolerance.