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Digital technologies are transforming horticultural production by enabling data-driven crop management and precise decision-making. This chapter introduces agricultural informatics, sensors, Internet of Things, remote sensing, drones, artificial intelligence, machine learning, geographic information systems, robotics, and precision technologies. These tools can support crop monitoring, disease detection, irrigation scheduling, nutrient management, yield prediction, phenotyping, and resource optimization. AI-based image analysis can identify symptoms and assist in early crop diagnosis, while sensors provide continuous information about soil and plant conditions. The chapter emphasizes the integration of digital data with practical horticultural knowledge to improve productivity, profitability, sustainability, and resilience while reducing unnecessary inputs and improving decision-making.

One of the important studies in the crop improvement programme is the discriminant function analysis. This is a method of exercising selection in plants, which show the extent of which character is genetically related to yield (Goulden, 1959). The technique of discriminant function was developed by Fisher (1936). But, the application of this method for plant selection was first made by Smith (1936) in wheat. He developed an index design for the selection of plant lines in wheat using the concept of discriminant function to derive a linear equation based on observable characteristics as the best available guide to the genetic value of each line.

Stephens (1942) reported about the interaction of yield components within the plant and within the population, which serves as an index for yielding ability. According to Hazel and Lush (1943), selection for a total score or net desirability is more efficient that selection for one trait at a time. The formulae presented by them for selection index give proper weight to each trait that are more efficient than selection for one trait at a time or for several traits with an independent culling level for each trait. According to Darlington and Mather (1949) discriminant function has been defined as a linear compound of series of varieties, obtained by giving the different varieties with individual coefficients which will minimize the difference between classes relative to variation within classes of objects of which the variates are measurements. Mather (1949) reported that these functions afford to the best available means of discriminating the classes and evaluating the genotype of a plant in terms of the observed values of various characters. Pundir and Raj (1971) reported that selection index based on three characters combination i.e., seeds per siliqua, 1000 seed weight and yield per plant was efficient in toria.

Introduction

In agriculture, plant diseases have always been a major problem, as they cause crop quality to decrease, resulting in yield. Plant disease has a range of effects from minor symptoms to serious damages in whole crop areas, which lead to high financial costs and significantly impact the agricultural economy, particularly in developing countries dependent on a single crop or on a few crops.

Various approaches have been developed to detect disease in order to avoid significant losses. Causal agents have been precisely defined by methods developed in molecular biology and immunology. However, for many farmers these techniques are inaccessible and require detailed knowledge of the field or substantial time and energy to be used. According to the United Nations Food and Agriculture Organization, most farms in the world are small and family-owned in developed countries. Such families provide food for a significant proportion of the population of the planet. However, hunger and food insecurity are not rare and there is restricted access to markets and services. For the above reasons, a great deal of work has been undertaken in order to establish methods that are sufficiently reliable and available to most farmers. Where Plant disease is an essential factor contributing to a major decline in plant production quality and quantity. Plant disease identification and classification are a significant role in improving plant production and economic development.

The disease , referred as the disorder of crop plants caused by fungi, mycoplasma, bacteria and viruses. Plant resistance is one of the most effective and ideal approach to combat diseases and insect-pest. Resistance is the capacity of plants to resist, withstand and overcome the attack of pathotypes.

Mechanism of Disease Resistance

Different mechanism of disease resistance are as under:

1. Disease escape

The ability of susceptible host plants to avoid attack of disease due to environmental factors like early maturing varieties, shift in the date of planting, change the field, balanced application of NPK etc. Example., early maturing varieties of groundnut and potato may escape from ‘Tikka’ and ‘Late blight’ diseases respectively.

2. Disease tolerance

The ability of the plants to tolerate the attack of the pathogen without loss or little loss in the yield. This endurance is brought about by the influence of external characters. Generally, tolerance is difficult to measure since it is confounded with partial resistance and disease escape. Disease tolerance is of three types:

Introduction

Biological nitrogen fixation (BNF), generally found in legumes, is a valuable nature’s gift through which atmospheric nitrogen is fixed by symbiotically associated rhizobia that make it available to plants. Among cereals, rice (Oryza sativa) is an important staple food crop that feeds a large proportion of the world population [1]. There is tremendous pressure on agriculturists worldwide to increase the yield to meet growing consumption to feed a world population increasing day by day. However, unlike symbiotic plant–microbe interactions commonly observed in legumes, in several cereal crop plants including Oryza sativa, endophytic associations have been observed [2-8].

UNTIL THE 1940S BIOLOGISTS ARGUED ABOUT WHETHER DNA OR PROTEIN WAS THE MOLECULE OF HEREDITY

Nuclei observed to divide when cells reproduced themselves

Large amounts of both DNA & protein in the nucleus

Many though protein was most likely molecule of heredity

Proteins made of 20 different amino acids- could have more variety than DNA (made of only 4 different bases)

Introduction
DNA barcoding is a molecular taxonomic method used to identify species by analyzing variations in conserved DNA sequences that differ among species. The concept of “barcoding” refers to pooling multiple samples and sequencing and analysing them collectively. This technique has been widely applied to identify organisms ranging from simple to complex forms. Unlike other genetic markers, such as short tandem repeats (STR), which are typically used to identify individual organisms, DNA barcoding enables broader species identification. However, identifying species-specific DNA sequences across different taxa can be complex and time-consuming. For accurate species differentiation, the variation in DNA sequences must be sufficiently high to clearly distinguish between closely related species (Antil et al., 2023).
DNA barcode sequences are stored in databases like the Barcode of Life Data Systems (BOLD), which is an online repository containing reference DNA sequences for comparison with unknown samples. These databases store speciesspecific genetic sequences, specimen images, and related data, and also track updates to barcode libraries (Jin et al., 2020). DNA barcoding has progressed alongside genomics research, with large online libraries serving as reference databases for identifying samples from various environments like gardens, forests, and even commercial products (Seethapathy et al., 2019).
As research advances, the number of conserved genomic regions used for DNA barcoding continues to grow. For phylogenetic analysis, the rbcL gene locus is commonly used, along with other regions such as the trnL-F intergenic spacer, matK, ndhF, and atpB (Shaw et al., 2005). The CoxI gene has been wellestablished for barcoding animals and plant species. The trnH, psbA region of the plastid has been proposed as a universal barcode for terrestrial plants (Ward et al., 2005). Several other conserved genomic regions have been established by a “plant working group” for molecular taxonomy (Singh et al., 2012). Despite these advancements, further critical evaluations of the authenticity of these DNA barcoding markers in assessing biological diversity are still needed. Over the last few decades, DNA barcoding has become a widely used tool for confirming species identification, as evidenced by the growing body of research publications on the topic (Rob et al., 2019).Publications on DNA barcoding have seen a notable increase, as shown by a search using specific keywords in the CabDirect database (http://www.cabdirect.org/). This trend highlights the growing importance of DNA barcoding in taxonomic research

Introduction
Pathogenic organisms that cause diseases in plants are generally referred to as plant pathogens. Fungi, bacteria, viruses, viroids, algae and protozoa are the important phytopathogenic organisms responsible for plant diseases and they cause immense economic losses to growers. Recent estimates indicate that crop losses due to diseases range from 17-30%, primarily caused by fungal, oomycete, and nematode pathogens (Agrios, 2005). Beyond biotic factors, crop losses can also be attributed to abiotic causes, such as poor agricultural practices, nutrient deficiencies, changes in temperature and rainfall patterns, inadequate/overirrigation and weather extremes, all of which exert selection pressure on plant pathogens, potentially leading to new host infections. Hence, for effective disease management strategy, accurate identification and diagnosis of plant pathogens are of paramount importance before the pathogen induces any epidemic leading to immense loss of crop plants which is certain. Often, identification can be accomplished either visually through microscopic observation of disease-causing micro-organisms or molecular diagnosis based on nucleic acid detection methods. Microscopic observations alone are inadequate for species-level identification of plant pathogens and can often lead to taxonomic errors due to the potential for misidentification of organisms. Nucleic acid-based diagnostic tools allow for the sensitive detection, precise quantification, and specific differentiation of pathogens.Although numerous nucleic acid-based methods are available for plant pathogen detection, PCR-based diagnostics, especially those employing DNA barcodes, are still considered highly reliable and accurate. Scientists, especially plant pathologists, can now easily identify and diagnose most plant diseases as many standardized phytopathogen barcodes facilitate rapid, early, and accurate identification of plant diseases.

Introduction
Rice is a key crop that directly feeds about half of the global population, with most of it consumed in developing countries (Wang et al., 2018). It is cultivated in many different types of environments and is always being enhanced by the creation of new varieties and the assessment and conservation of germplasm collections. To improve rice diversity and increase its genetic range, numerous researchers and organizations have been attempting to bring long-forgotten types back into production.This variation among varieties is essential for breeders as it provides genetic traits that can be incorporated into commercial varieties, such as resistance to diseases and pests, tolerance to abiotic stresses and improvements in grain nutritional quality, among others. In some cases, specific new traits areintroduced through crosses made with distantly-related genotypes. As a result of these efforts, despite being one of the first domesticated crops, cultivated rice continues to tap into a vast gene pool (Vieira et al., 2022).
There are over 500,000 rice accessions stored in gene banks around the world (Genesys 2021). To further explore the molecular diversity of this germplasm International Rice Research Institute (IRRI), Chinese Academy of Agricultural Sciences and BGI-Shenzheninitiated the 3K Rice Genome Project. This project focused on the most important rice species, Oryza sativa, and involved resequencing 3,000 rice genomes selected from the available genetic diversity, creating an invaluable resource for large-scale genetic variation discovery in this species (Vieira et al., 2022).
Varietal identification and classification in breeding programs are typically assessed using the distinctness, uniformity, and stability (DUS) approach, which relies on morphological descriptors (Tiwari et al., 2013). However, using morphological data/markers to determine genetic variation has limitations due to the labor-intensive, time-consuming nature of the process, as well as theagronomical traits and season-specific that are heavily influenced by ecologicalaspects. The development of genetically and morphologically similar varieties has made the task of clearly distinguishing between them increasingly complex. These environmental challenges necessitate the use of new techniques that are fast, reliable and environmentally independent.Biochemical and chemical tests fail to accurately estimate genetic distances among closely related genotypes. PCRbased molecular markers, however, are fast, reliable, and effective for determining the genetic purity of crop varieties (Rana, 2006). Hypervariable microsatellites (Teymnykhet al., 2011) offer a valuable source of polymorphic DNA markers, connecting genetic maps to genomic sequences and, ultimately, to phenotypic variation. SSR-based “DNA barcodes” are unique patterns of SSR polymorphism that assist in the precise identification of varieties, providing stability and resistance to environmental influences, epistatic interactions, and pleiotropic effects.

Introduction
Plant genetic resources (PGRS) encompasses everything that is on the earth related to the plants which are beneficial to mankind (Appazov,2008). So, it is the basic raw material for crop improvement (Somsenet al., 2002). In the present regime of transgenic crops, you can have ‘designer crops’- crops of your willingness (Wisner et al., 2001). From the heritage of mankind to the sovereign rights of the states this is the path that PGRs have traversed, earlier before CBD (Conventional Biological Diversity)(Chakraborty et al., 2018) PGRs were considered as a heritage of mankind freely available to everybody but after signing that they became the sovereign rights of the states with sovereign rights of the nation (Brahmiet al., 2015). In such a scenario where states have their rights on those plants’ genetic wealth, protection becomes very important (Clevelandet al., 1997). DNA fingerprinting is one of the technologies which can facilitate that protection (Wanget al., 2019).Rapeseed-mustard (Brassica spp.) is a vital oilseed crop cultivated extensively in India and other parts of the world (Kumaret al., 2008). It plays a crucial role in ensuring edible oil security and contributes significantly to the agricultural economy(Pahariyaet al., 2007). The genetic diversity within rapeseed-mustard species is a key factor in improving yield potential, disease resistance, and oil quality through breeding programs (Chandet al., 2021). However, accurately identifying and characterizing varieties is a challenge due to phenotypic similarities, environmental influences, and potential genetic erosion(Chhikaraet al., 2024). To address these challenges, DNA fingerprinting has emerged as a powerful molecular tool for precise varietal identification, genetic purity assessment, and germplasm conservation (Hosseinpouret al., 2024).DNA fingerprinting involves the use of molecular markers to generate unique genetic profiles of plant varieties, enabling breeders and researchers to differentiate between closely related cultivars (Singhet al., 2022; Singhet al., 2014). This technology is instrumental in breeding programs, ensuring the registration and protection of plant varieties under legal frameworks such as the Protection of Plant Varieties and Farmers’ Rights Act (PPV&FRA) in India (Williamet al., 2024). Additionally, DNA-based markers provide valuable insights into genetic relationships, aiding in the efficient selection of parent lines for hybridization and improving crop resilience to biotic and abiotic stresses (Nadeemet al., 2018; Haqueetal., 2021).Over the past two decades, several DNA fingerprinting techniques, including Random Amplified Polymorphic DNA (RAPD), Amplified Fragment Length Polymorphism (AFLP), Simple Sequence Repeats (SSR), and Single Nucleotide Polymorphisms (SNPs), have been widely applied to characterize rapeseed-mustard varieties (Nybomet al., 2014; Panjabietal.,2019) Advances in high-throughput genotyping and nextgeneration sequencing (NGS) technologies have further enhanced the resolution and accuracy of genetic profiling, paving the way for marker-assisted selection (MAS) and genomic-assisted breeding strategies (Sinhaet al., 2023).

Introduction
DNA fingerprinting envisages a very significant molecular methodology employed for identification and characterization of wheat varieties and germplasm. It is of utmost importance in varietal authentication, rights protection of breeders, and analysis of genetic diversity. Currently employed molecular markers like SSRs, SNPs, and DArT are applied extensively for wheat fingerprinting. Such markers precisely differentiate closely related varieties and aid in breeding programs (Babu et al., 2020; Kiss et al., 2021).
The current standing of wheat DNA fingerprinting shows a trend toward high-throughput genotyping and genomic selection strategies to accelerate crop improvement. Future prospects would entail the integration of advanced sequencing technologies such as Next-Generation Sequencing (NGS) and machine learning for genetic analysis. These technologies will ease wheat breeding and dramatically contribute to food security and climate-resilient agriculture. Expanding the global DNA fingerprinting database would further enhance global wheat germplasm conservation and utilization (Sandhu et al., 2021; Ahmadi et al., 2020). Wheat (Triticum spp.) is one of the major staple crops of the world, supporting the sustenance of over one-third of the total world population. It is the main source of carbohydrates, proteins, fibers, and other important micronutrients, making it very important for human nutrition. Wheat is cultivated mainly in all types of agro-climatic zones, with major producers being China, India, Russia, United States, and the European Union.
Wheat is highly valuable not only in terms of food security, but also economically with millions of farmers involved in its production and trading worldwide. Wheat is an important raw material for many food products, such as bread, pasta, and baked goods. Wheat production faces challenges from climate change, pests, and emerging pathogens. Therefore, continuous research on wheat, genetic improvement for desirable traits, and sustainable agricultural practices are needed to enhance yield, resilience, and in turn global food security. Genetic diversity in wheat is pertinent for fulfilling food security at the global level and for the success of breeding programs, apart from giving diverse traits for resistance against pests, diseases, and environmental stresses like droughts

Principle

The rate of joining of DNA fragments is affected by seven parameters:

DNA concentration,

Concentration of compatible ends,

Size of the fragments,

Presence or absence of complementary, single-stranded ends (some nucleases form blunt ends and in these cases special techniques are needed for joining),

G + C content and length of the complementary single strands,

Temperature of the reaction and

Ionic composition of the solution.

Introduction

DNA denaturation, also called DNA melting, is the process by which double-stranded deoxyribonucleic acid unwinds and separates into single-stranded strands during the breaking of hydrogen bonding between the bases. Both terms are used to refer to the process as it occurs when a mixture is heated, although “denaturation” can also refer to the separation of DNA strands induced by chemicals like urea. For multiple copies of DNA molecules, the melting temperature (T_m) is defined as the temperature at which half of the DNA strands are in the double-helical state and half are in the “random-coil” states. The melting temperature depends on both the length of the molecule, and the specific nucleotide sequence composition of that molecule.

Applications of DNA Denaturation

The process of DNA denaturation can be used to analyze some aspects of DNA. Because cytosine / guanine base-pairing is generally stronger than adenosine / thymine base-pairing, the amount of cytosine and guanine in a genome (called the “GC content”) can be estimated by measuring the temperature at which the genomic DNA melts. Elevated temperatures are associated with high GC content. GC ratios within a genome are found to be markedly variable. These variations in GC ratio within a genome of higher organisms results in a mosaic like formation with islet regions called isochores. This results in the variations in staining intensity in the chromosomes. The isochores include in them essential protein coding genes, termed housekeeping genes and thus determination of ratio of these specific regions contributes in mapping these essential genesbacterial systematics has recommended use of GC ratios in higher level hierarchical classification. For example, the Actinobacteria are characterised as “high GC-content bacteria”. In Streptomyces coelicolor A3(2), GC content is 72%. The GC-content of Yeast (Saccharomyces cerevisiae) is 38%, and that of another common model organism Thale Cress is 36%. Because of the nature of the genetic code, it is virtually impossible for an organism to have a genome with a GC-content approaching either 0% or 100%. A species with an extremely low GC-content is Plasmodium falciparum (GC% = ~20%), and it is usually common to refer to such examples as being AT-rich instead of GC-poor.

Preparation of Solutions

GTE buffer

50 mM Glucose,

25 mM Tris-Cl,

10 mM EDTA,

pH 8

NaOH/SDS lysis solution

0.2 M NaOH,

1% SDS

Reagents

EDTA

Ethanol, absolute

Isopropanol

Phosphate Buffered Saline (PBS), 1X

Proteinase K

Sodium Acetate, 3 M pH 5.2 (Molecular Biology Grade)

Sodium chloride (NaCl)

Sodium Dodecyl Sulfate (SDS ), 10%

Tris EDTA (TE), pH 7.4

Tris EDTA (TE), pH 8.0

Tris HCl, pH 8.0

Reagents

Chloroform

EDTA, 0.5 M

Ethanol, absolute

Isoamyl alcohol

Phenol

Phosphate Buffered Saline (PBS), 1X

Proteinase K

RNAse A

Sodium dodecyl sulfate (SDS) solution, 10%

Reagents

Chloroform

EDTA, 0.5 M

Ethanol, absolute

Is amyl alcohol

Phenol

Proteinase K

RNase A

Sodium acetate, pH 5.2

Sodium chloride, 5 M
Sodium thiocyanate (NaSCN), 1 M

TE Buffer (Tris-EDTA), pH 7.4

Tween 20

Xylene

DNA replication. The double helix is unwound and each strand acts as a template. Bases are matched to synthesize the new partner strands.

DNA replication, the basis for biological inheritance, is a fundamental process occurring in all living organisms to copy their DNA. This process is “replication” in that each strand of the original double-stranded DNA molecule serves as template for the reproduction of the complementary strand. Therefore, following DNA replication, two identical DNA molecules have been produced from a single double-stranded DNA molecule. Cellular proofreading and error toe-checking mechanisms ensure near perfect fidelity for DNA replication.

In a cell, DNA replication begins at specific locations in the genome, called “origins”.

Unwinding of DNA at the origin, and synthesis of new strands, forms a replication fork. In addition to DNA polymerase, the enzyme that synthesizes the new DNA by adding nucleotides matched to the template strand, a number of other proteins are associated with the fork and assist in the initiation and continuation of DNA synthesis.

Watson and Crick based on their double helical DNA model, offered to explain DNA replication by a method where each single strand of DNA is template or mold for its complement and a new helix has one old strand and one newly synthesized strand. This type of DNA replication is called as semi-conservative as in this method one old strand is retained and one new complementary strand is synthesized. In contrast to semi-conservative mode of DNA replication, two more modes of DNA replication were proposed. One is conservative type where two new strands are synthesized in form of a double helix while the old double helix remains unchanged. The third type of DNA replication proposed has been dispersive mode of DNA replication which amounts to breaking down of double helical strands into small pieces along the length, their replication and random assemblage with newly synthesized pieces to form a patchwork single string of dispersed old and new pieces. These three modes of replication of DNA molecule are shown in Fig. 40.1.