Bidhan Chandra Krishi Viswavidyalaya

An optical mouse is a computer navigation device that uses light, primarily to track movement and control the cursor on a computer screen. Other than computer cursors, various fields of applications such as process instrumentation, robotics, healthcare, and agriculture now using this ready-to-use device as sensor due to its low latency, light weight, high accuracy, and power efficiency. It is also compatible with wearable devices, and Internet of Things (IOT)-based applications, which are prefer low-power digital output. Typically, the optical mouse sensor getting popularity for those applications where measurement is possible by precise motion data or analysis of object image. The sensor detects motion in both the x and y axes and the built-in signal processing unit helps to interface with computers through wires and wireless data transfer protocols. This paper’s main contribution is a comprehensive study of optical mouse sensors used for various applications other than computer-pointing devices.

Soybean is one of the most popular food in India, where most of the people are vegetarian, fats and proteins that come from plants are especially important. It is affected by different diseases, but rust is the most dangerous one. Since the beginning of agriculture, people have had to contend with recurrent outbreaks of crop rust. As a direct consequence of this, cereal rust infections were among the very first to get extensive research as the field of plant pathology developed during the 1800s and into the early 1900s. It was quickly discovered that the rust fungus was refered to as “shifty enemies,” a phrase coined by E. C. Stakman. These fungi had a persistent ability to generate new virulences that were capable of defeating freshly introduced resistant cultivars. However, a new science of disease stabilization and management is currently coming into being. This new science makes use of an increased understanding of the complexity of rust disease in order to halt the creation of harmful new virulences, to delay epidemics, and to reduce losses. This chapter presents the information that serves as the foundation for the new tactics that have been developed regarding soybean rust.

Soyabean is economically important crop and known for their exceptional nutritional value. Soybean purple seed stain is a prevalent disease that poses a considerable threat to soybean production worldwide. The disease progresses through the development of dark purple to black stains on soybean seeds, leading to substantial reductions in both yield and seed quality. This chapter focuses on the epidemiological aspects of soybean purple seed stain, exploring how the disease spreads within and between soybean fields. Identifying key factors contributing to its dissemination can aid in the development of targeted disease management strategies. Various factors, including weather conditions, agronomic practices, and seed transmission, influence the disease’s epidemiology and severity. It is important to understand the disease’s progression, timely detection, and effective management practices to mitigate losses due to this disease. Disease management strategies such as cultural practices, biological control, varietal resistance, chemical management are discussed. Overall, this chapter provides a comprehensive analysis of the symptomatology, epidemiology, and detection of the disease and briefly describes the conventional and modern trends in disease management practices.

Phytophthora stem and root rot is a catastrophic plant disease, caused due to Phytophthora sojae. The disease manifests through a range of symptoms, including damping-off, rotting, as well as blighting that ultimately lead to plant death. Epidemiological factors, such as environmental conditions and host susceptibility, greatly influence disease development and spread. Understanding the factors contributing to pathogen dispersal and infection can aid in the formulation of efficient management strategies. Phytophthora stem and root rot management approaches primarily encompass on cultural practices, chemical control, and genetic resistance. Crop rotation, proper drainage, and the use of resistant cultivars are essential components of integrated disease management strategies. Genetic resistance presents a promising avenue for sustainable disease management. The identification and deployment of resistant genes through breeding programs can provide durable protection against Phytophthora stem and root rot. This chapter focuses on the symptomatology, epidemiology, and management strategies employed to mitigate its impact.

Herbalism, rooted in traditional knowledge and regional practices, leverages plants as medicinal resources. India, with its vast biodiversity, harbors numerous untapped medicinal plants. This study focuses on the bioprospecting of two underexplored wild medicinal plants, Elsholtzia griffithii from Manipur and Smilax perfoliata from West Bengal, aiming to document their medicinal potential. We characterized metabolites in their crude methanolic extracts and explored their resistance to bacterial infections. Utilizing gas chromatography-mass spectrometry (GC-MS) analysis, 17 significant chemical compounds are identified, exhibiting physiological and pharmacological importance. Conducting disc-diffusion assays against E. coli, both plant extracts demonstrate antibacterial activity. Crude methanolic extracts of Smilax perfoliata and Elsholtzia griffithii showed a zone of inhibition of approximately 13 mm and 4 mm respectively. Additionally, molecular docking studies were conducted to evaluate the binding energy of the compounds to the E. coli receptors, DNA GyrB, and FabH and identify the receptor-ligand interactions. Among them, 4-Dehydroxy-N-(4,5-methylenedioxy-2-nitrobenzylidene) tyramine and Phthalic acid, dodecyl 2-methoxyethyl ester from Smilax perfoliata, and p-(dimethyl amino) benzaldehyde pyridine-4-carbonyl hydrazone from Elsholzia griffithii exhibit lower binding energy. The interactions between these 3 compounds and the receptors consisted of hydrogen bonding and hydrophobic interactions. Thus, it underscores the potential of compounds derived from these plants as inhibitors against gram-negative bacteria. Thus, our study unveils the ethnomedicinal properties of these wild plants, providing a comprehensive metabolite profile and paving the way for potential drug discovery.

Coupled oscillators are being studied extensively to explore different dynamical phenomena in nature and society. Time delays, namely processing delay and propagation delay play a vital role in influencing the response of a coupled oscillating system. Delay, if not negligible, is to be considered in modelling a system to replicate the system dynamics as obtained in the real world. It has a significant contribution to collective behaviour if the number of interacting components is large in the network. This chapter deals with the dynamics of a mean-field diffusive coupled Van der Pol oscillator-based system with an inherent delay in each oscillator unit. The component oscillators become unstable through inhomogeneous limit cycle (IHLC) and quasi-periodic (QP) oscillations. Analytical studies and numerical simulation have been presented to explore the coupled system response with different values of delay, diffusive coupling strength as well as number of oscillators. With the increase in delay time, coupling strength or the number of oscillators in the coupled system, the complexity of the system response is increased and the system gradually becomes unstable.

Seed germination is one of the most critical stages of plants’ life cycle, significantly influencing early seedling growth and development. Environmental stressors such as salinity, drought, cold heat and heavy metal toxicity during the seed germination and seedling stages can severely impact crop growth and productivity. Reduced water quality, quantity and prolonged use of recycled wastewater for irrigation, global warming, etc. are considered potential factors contributing to land degradation and rising salinity of arable lands. Plants grown under saline conditions face several physiological and metabolic alterations that ultimately reduce crop growth and productivity. As defense response, plants have developed a range of morphological, physiological, biochemical, and molecular mechanisms to mitigate negative effects of salinity stress. Out of these, plant hormones are known to modulate cell signaling at different crop growth stages positively or negatively, especially during the seed germination and seedling stages, under both stress and non-stress conditions. The major phytohormones associated with seed germination under salinity stress include abscisic acid (ABA), ethylene (ET), jasmonates (JAs), gibberellins (GAs), salicylic acid (SA), brassinosteroids (BRs), melatonin, and auxin. Crosstalk among these hormones plays a crucial role in understanding the salinity tolerance mechanisms in plants. This review aims to summarize the roles of different phytohormones during seed germination and seedling stages during salinity stress, including their signaling and molecular aspects. Additionally, the role of exogenous applications of different phytohormones in salt stress mitigation has also been discussed. The information presented here will be useful for molecular biologists as well as plant breeders seeking to develop strategies for crop improvement under salinity stress conditions.

The increasing need for food production worldwide has primarily been met by the widespread use of conventional fertilizers (CFs). However, worries about environmental dangers, such as contaminated soil and water, have been brought up by the rising usage of CFs, particularly in cereal-based cropping systems. As a result, the agriculture industry has seen the development of healthier substitutes through the application of nanotechnology and nanofertilizers (NFs). These novel NFs increase the effectiveness of nutrient utilization by utilizing the extraordinary qualities of small sizes nanoparticles. NFs, in contrast to their traditional equivalents, have a number of benefits, such as variable solubility, reliable and efficient performance, regulated release mechanisms, improved targeted activity, less eco-toxicity, and simple, secure delivery and disposal processes. Furthermore, as compared to conventional fertilizers, their superior formulations allow for the more effective support of sustainable crop development and output. In cases when agricultural crops are subjected to abiotic stress, this study emphasizes the potential of using nanofertilizers to increase plant production and performance and ensure environment friendly crop yield while maintaining agricultural sustainability.

In order to get higher productivity, continuous use of conventional fertilizer in agricultural land causes soil degradation and undesirable changes in our environment. As a result, crop response to the fertilizer is declining and farmers are using more fertilizers unknowingly which is jeopardizing soil natural ecosystem. Sometimes, even after following proper agronomic management practices, nutrient use efficiency (NUE) can’t be improved owing to the constraints rendered by crop microclimate. Moreover, for food security, total food production is being more emphasized rather than nutritious food production, and its ill effect is being manifested as micronutrient malnutrition across the world. In this context, nanofertilizers (NFs) could be a decent alternative to improve crop production with high NUE. On the other hand, it can fortify the crop produce with essential nutrient. NFs are of submicroscopic size with large surface area as compared to volume and sometimes fertilizers are encapsulated with nanoparticles (NPs), to get higher mobility and slow release of nutrient. However, optimization of dose of NFs and proper size and shape of NPs are the prerequisite for higher crop response.

Breeding of crop plants has achieved notable success in developing cultivars that significantly boost agricultural production in favorable conditions. These cultivars, which are typically homozygous inbreds or hybrids descended from inbred parents, are produced under ideal conditions in the field and thrive especially in regions with sufficient moisture and nutrients. These ideal circumstances are, nevertheless, uncommon in the world at large, with a sizable portion of arable land being judged unsuitable for agricultural use. Agricultural marginal land is typically located in semi-arid or saline regions, has little soil depth, low production, and is prone to erosion. It is also anticipated that the effects of climate change and the ongoing depletion of the world’s soil and water resources would make these difficult circumstances much more severe. Crop wild relatives, or CWRs, are frequently bred for their ability to withstand biotic stress; typically, they possess traits that allow them to flourish in challenging conditions. Using CWRs directly for varietal development initiatives is often not advantageous because of their high frequencies of agronomically unfavorable genes and crossover or possible obstacles to chromosomal introgression with crops species. Linkage drag may cause unwanted traits in the progeny when phenotype-linked genomic regions, or quantitative trait loci (QTLs), are introgressed from wild germplasm. On the other hand, modern breeding practices focused on broad adaptation have led to decreased genetic diversity and heightened susceptibility to both biotic and abiotic stressors. There is a possibility to utilize genetic diversity instead of advocating for genetic consistency in breeding, aiming to improve the adaptability of crops for less favorable lands. In this chapter, we have detailed the adaptive traits that may increase crop variety productivity in challenging circumstances, and we offer recommendations on how to efficiently and rapidly utilize these wild relatives for prebreeding research projects that involve the introgression of foreign genes.

Considering the recent trend of population growth, the current worldwide crop productivity needs to be doubled by 2050. The prevalence of disease and insect infestations is one of the main obstacles in achieving this productivity goal. As a result, it is essential to develop effective techniques for the automatic detection, identification, and forecasting of pests and diseases in agricultural crops. In recent years, the agricultural sector has witnessed a transformative wave of technological advancements, particularly in the realms of artificial intelligence (AI) and machine learning (ML). Experimental results based on current data of pests and diseases have proved that the AI method is faster and more accurate than conventional and existing monitoring and forecasting procedures. By leveraging advanced algorithms and data-driven approaches, AI empowers farmers with early detection tools, enabling swift identification of pest infestations and diseases. Image recognition technologies, coupled with drones and smartphones, offer a proactive solution by capturing real-time data from fields, which AI algorithms analyze to pinpoint specific issues. Additionally, Internet of Things (IoT) devices equipped with sensors facilitate the collection of vital environmental data, paving the way for predictive modeling and precision agriculture practices. Moreover, AI-driven robotic systems equipped with precision spraying mechanisms minimize pesticide usage, reducing environmental impact and promoting sustainable farming practices. Collaborative efforts among researchers, technologists, and farmers have led to the creation of smart farming solutions that integrate AI and ML. This chapter highlights the transformative potential of AI and ML in reshaping pest and disease management paradigms, fostering a future where agriculture is not only productive and resilient but also ecofriendly and sustainable.

The Indo-Gangetic Plain (IGP), India’s “breadbasket”; is essential for food security in India and South Asia. Rainfall patterns significantly influence the agriculture and water resources of this region. The current study aimed to identify homogeneous rainfall zones over IGP across different seasons through unsupervised machine learning methods like k-means clustering during 1961 – 2020 utilizing high-resolution gridded from (0.25° × 0.25°) rainfall data India Meteorological Department (IMD). Three homogeneous rainfall zones were identified during pre-monsoon and monsoon, and two for post-monsoon and winter. Seasonal rainfall trends for each homogeneous zone were analyzed using parametric (linear regression) and non-parametric (Mann-Kendall) methods. Both approaches revealed a significant increasing trend (2.07 – 2.13 mm/year) in pre-monsoon rainfall over zone 2 (Sub-Himalayan West Bengal, SHWB), a significant decreasing trend in monsoon rainfall (2.62 – 2.85 mm/year) over zone 1 (Trans-Gangetic and western Upper-Gangetic Plains) and post-monsoon rainfall (0.26 – 0.37 mm/year) over zone 1 (Trans-Gangetic, Upper-Gangetic, and western middle Gangetic Plains). No significant rainfall trend was observed during the winter season over the IGP. Changepoint detection was applied to identify shifts in the long-term inter-annual mean of seasonal rainfall. There was no significant shift in pre-monsoon rainfall time series over the IGP except for an increase in the SHWB after the changepoint year 1973. Monsoon rainfall over two other zones except SHWB decreased after the respective changepoint years (1996 and 2008). The identified trends over homogeneous rainfall zones may provide valuable inputs for multi-level stakeholders to implement different water management and adaptation strategies for agricultural development planning under changing scenarios.

Currently, crop modeling is a useful tool for simulating crop output and growth under various agronomic practices. It also can used to evaluate the impact of these managements on the environment such as greenhouse gases i.e. N2O, CH4, CO2, N, NH3 and the transport of carbon, nitrogen, water and pesticide in soil at upper or deeper depth levels. Recently, the DSSAT 4.8 version integrated a pest growth module too which will help to stimulate the growth of pest during the crop growth period. Further, crop simulation models are integrated with forestry or tree models and now these can used for carbon sequestration purposes to reduce the carbon concentration from the atmosphere and restore into soil. Hence, crop modelling technic have a lot of scope to work to maintain the environment without affecting crop production for a global population.

Understanding the mechanisms that regulate plant growth, development, and responses to environmental stimuli necessitates a deep knowledge of the complex signalling networks exhibited by plant hormones. This review aims to decipher the molecular underpinnings of these plant hormone signalling networks, particularly in response to environmental changes, a critical aspect in the context of climate change. The review employs interdisciplinary methodologies such as bioinformatics, systems biology, genomics, and proteomics to examine the intricate interplay and regulatory pathways that govern plant hormone responses. It focuses on key hormone families—auxins, gibberellins, cytokinins, abscisic acid, ethylene, and brassinosteroids—and elucidates their roles in various physiological processes, including senescence, cell division, elongation, and stress responses, all of which have implications for plant adaptation to changing climates. The paper addresses the identification and characterization of hormone receptors, transcription factors, and downstream signalling components that regulate hormone responses. It highlights the emerging function of hormone crosstalk and the interaction between hormones in determining plant growth and development, crucial for plants’ resilience in the face of climate change. Moreover, the review discusses the potential benefits of unraveling the molecular underpinnings of plant hormone signalling networks. These include enhancing crop yield, increasing resilience to stress, and promoting sustainable agriculture, all of which are vital for food security in a changing climate. This review as book chapter presents a comprehensive examination of the research article, shedding light on the current understanding and potential future developments in the field of plant hormone signalling. It underscores the importance of this research in understanding how plants can adapt to and mitigate the impacts of climate change, thereby contributing to the development of climate-resilient agricultural practices.

Downy mildew (Pseudoperonospora cubensis) is a menace to the cucumber growers and mitigation of this dreaded disease necessitates multiple synthetic pesticide applications, often leading toxic residue issues and environmental as well as health hazards. Spectral imaging is a modern approach for early detection of various stress hotspots that can help us to mitigate those issues very promptly. Plant pathogens caused different biochemical and histopathological modifications inside the infected host plants with advancement of the disease development. Different vegetative indices based on the changes in the dynamics of the spectral responses with disease progression was used to determine the stress issues in early phases of infection non-destructively. In our study ten different vegetative indices and 2 interactive indices were correlated with different biochemical parameters (total chlorophyll, total carbohydrate and carotenoids) at different disease progression stages (Light Green/LG, Light Yellow/LY, Deep Yellow/DY, Yellow & Necrotic/Y & N, and Necrotic/N). When correlated with total chlorophyll concentration, PRI (Photochemical reflectance index) gave R2 value of 0.896 and 0.861 in all disease progression stages and early diseased stages (LG, LY, DY) respectively, and RSI (Ratio spectral index) 3 gave R2 value of 0.785 in early disease progression stages. The R2 value of 0.862 was obtained when correlation between PRI with dynamics of carotenoids at early phases of disease progression was done. Total carbohydrate concentration dynamics yielded less R2 value with examined vegetative indices except RSI 2 and NDSI (Normalized difference spectral indices) 3 in early phases with R2 of 0.512. Thus, the selected vegetative indices may be interlinked for non-destructive way of early detection and interventions of cucumber downy mildew disease for effective and early hotspot-specific management operations. This prototype study has wide scope in disease assessment through advanced techniques which can be directly applied or appropriately modified for the benefit of cucumber growers, breeders and scientific research purposes.

Lentil is an essential edible legume crop, especially for developing countries, due to the presence of high‐quality proteins, fibers, essential vitamins, and mineral nutrients. The short height of this crop is often linked with a slow pace of growth, favoring the suitable space and time for weed incursion. Consequently, the developmental period during the crop growth cycle is shortened, leading to a decline in crop productivity. To control the menace of weeds and sustain the yield potential of lentils, we have evaluated the impact of imazethapyr spray on the osmotic behavior of lentil crops. Further, we have investigated the kinetics of PAL (phenylalanine ammonia lyase) and GST (glutathione‐s‐transferase) to elucidate the process of imazethapyr detoxification by lentil crop at the seedling stage. The results of the present study demonstrated that imazethapyr spray reduced the RWC (relative water content) in the range of 3.10–40.48% across the applied doses of 0.5 RFD (recommended field dose), 1 RFD, 1.25 RFD, 1.5 RFD, and 2 RFD, during different sampling periods from 0 HBT (hours before treatment) to 120 HAT (hours after treatment). On the other hand, proline content increased across different doses of imazethapyr and sampling hours. Proline content was highest at 2 RFD and varied in the 112.12–309.49% range during different sampling hours. Similarly, total soluble sugar content increased (18.15–151.66%) in response to varying imazethapyr doses across different sampling hours. The kinetic study of PAL and GST indicated progressive increases in the Vmax (maximum velocity) and Km (Michelis‐Menten constant) of both enzymes. Vmax of PAL varied from 1.09–2.31 μmol of t‐cinnamic acid produced (h‐1 mg‐1 protein), whereas that of GST varied from 35.59–83.33 μmol of CDNB (1‐chloro‐2,4‐dinitrobenzene) across the imazethapyr doses.

The need for transparency and traceability in the food supply chain has increased in an increasingly linked world, especially in smart tourism destinations where visitors are looking for real, sustainable, and safe food experiences. By establishing a decentralized, immutable ledger that tracks every transaction and movement of food products from farm to fork, blockchain technology transforms food traceability and guarantees that all parties involved farmers, processors, distributors, retailers, and consumers have access to accurate, up-to-date data. With only a quick scan of a QR code, consumers can verify the provenance and path of food, preventing fraud and boosting customer confidence. The real-time data collection and transmission of parameters like temperature, humidity, and location by IoT devices like sensors and RFID tags, which are then recorded on the blockchain to create an extensive and transparent record of the food product’s journey, is one way that the integration of blockchain technology with the Internet of Things (IoT) improves traceability systems even further. This technology guarantees that local food items in a smart tourism zone fulfill strict safety and quality criteria, boosting the area’s image and offering visitors reliable, genuine dining experiences. By utilizing blockchain technology and the IoT, intelligent tourist destinations may attain previously unheard-of levels of traceability and transparency in their food supply chains, satisfying the increasing needs of environmentally aware customers and encouraging sustainable practices that boost local economies. Using these technologies is a big step toward guaranteeing food authenticity, quality, and safety in a society that values transparency and interconnection.

Minor pulses are crucial for nutrition and sustainable agriculture; yet, limited resources and inherent challenges hindered their genetic enhancement. However, recent advances in next-generation breeding tools are thought to be an encouraging solution. This chapter explores how genomics, molecular biology, and precision breeding can be applied to minor pulse crops, ensuring global food security and environmental sustainability. Cutting-edge techniques like genotyping, genome sequencing, and high-throughput phenotyping have revolutionized our grasp of genetic diversity and adaptive mechanisms within minor pulse species. Methods such as genome editing, marker-assisted selection, genomic selection, and genomic prediction are enhancing breeding efficiency and facilitating the development of high-yielding, nutritionally rich, and stress-tolerant varieties. Additionally, these tools contribute to sustainable agriculture by producing pulse varieties resilient to climate change and efficient in resource use, aligning with global efforts to mitigate environmental impacts. In conclusion, next-generation breeding tools offer immense promise for significant impacts on global agriculture and nutrition. By harnessing the power of genomics and precision breeding, we can unlock the latent potential of minor pulses, thereby advancing toward a more sustainable and food-secure future.

The incessant anthropogenic activities, such as fast urbanization and industrialization, population growth and indiscriminate use of chemical fertilizers, are deteriorating soil health, environmental quality and crop yield tremendously. Nanofertilizer (NF) is a novel approach for efficient utilization and cost minimizing approach to supplement fertilizer against the bulky use of synthetic chemical fertilizer for a greater improvement of agricultural productivity and crop quality while fostering soil biological activity and environmental sustainability. The controlled release of nanomaterials to the targeted site through soil or foliar application of NF can help plants to absorb them through roots or leaves. The smaller size and precise action of these materials can minimize nutrient loss and increase nutrient use efficiency. Nanomaterials undeniably exert a significant influence on soil health and agricultural productivity. This article aims to identify the impacts of nanomaterials on soil properties and high-quality crop production with a special focus on optimal soil health management for sustainable crop production.

Minor pulse crops are resilient in challenging environments and harsh climates, especially in arid regions worldwide. Characterized by their low-input needs and climate resilience, these pulses have a significantly reduced carbon footprint compared to more intensively farmed crops. This book chapter discusses minor pulse crops, their potential to address global agricultural challenges, and respective plant genetic resources (PGRs), highlights relevant genomic resources and breakthroughs, and provides a comprehensive overview of various breeding strategies used to enhance the productivity of minor pulses. The chapter also explores strategies for reducing anti-nutritional factors and increasing the nutritional value of these crops. By removing undesirable traits and/or incorporating favourable traits, technology integration, like CRISPR/Cas9, can greatly expand agricultural research and foster the creation of novel varieties. The various applications of the CRISPR method in genetic manipulation have garnered substantial interest in recent years. A thorough explanation of the possible applications of CRISPR/Cas9 technology for improving minor pulses is given. The role of strategic advancements in targeted breeding, unravelling genetic potential, and market integration for underutilized pulses is discussed. Additionally, this chapter emphasizes the critical role that minor pulses play in strengthening global food systems in response to climate change and suggests innovative breeding techniques as a means of bringing these formerly marginal crops to the forefront of agriculture.