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Organic manures in combination with biochar might improve efficacy of biochar in improving soil functions related to hydro-physical properties and a field experiment was conducted over the course of two years with two levels of biochar @ 0 and 2tha−1 and four levels of compost (100% recommended dose of N through farm yard manure, 100% recommended dose of N through vermicompost, 50% recommended dose of N through farm yard manure, and vermicompost each, and unfertilized control). Each treatment was replicated three times in factorial randomized block design (RBD). The objective of this research was to determine the effects of biochar and compost on soil hydro-physical properties, water use efficiency, monetary returns and yield of knolkhol (Brassica oleracea var. gongyloides L.) under sub-tropics of North West India. Compared with no-biochar, application of biochar significantly increased knolkhol yield by 7.8% and soil properties (infiltration rate, aggregate stability, maximum water holding capacity and hydraulic conductivity). Similarly, integration of compost significantly enhanced the soil water retention, aggregate stability, hydraulic conductivity and crop yield and gave highest infiltration rate, water retention, hydraulic conductivity and crop yield under M3 (50 % N through farm yard manure, +50 % N through vermicompost) treatment. Furthermore, synergetic positive effect of biochar and compost were noted for soil infiltration rate (4–38%), water retention (0.9–13.7%), aggregate stability (6–10.7%) and yield (6–11.9%) over the sole application of compost. Combined use of farm yard manure, and vermicompost accompanied by biochar resulted in highest net returns and B:C ratio. Biochar in combination with farm yard manure, and vermicompost can enhance soil hydraulic properties resulting in increased crop yield and maximum monetary returns under subtropical conditions.

Nitric oxide releasing compound sodium nitroprusside (SNP) is regarded as novel chemical to beat the daunting challenges of postharvest losses in cut flowers. In the recent years, it has yielded propitious results as postharvest vase preservative for cut flowers. Our study explicates the efficacy of SNP in mitigating postharvest senescence in Consolida ajacis (L.) Schur cut spikes. The freshly excised C. ajacis spikes were subjected to different SNP treatments viz, 20 μM, 40 μM, 60 μM and 80 μM. The control spikes were held in distilled water. The spikes held in test solutions showed a marked improvement in vase life and flower quality. Our results indicate a profound surge in sugars, phenols and soluble proteins in SNP-treated spikes over control. Moreover, the SNP treatments improved membrane stability as signposted by decreased lipoxygenase activity (LOX). The SNP treatments also upregulated different antioxidant enzymes viz, ascorbate peroxidase (APX), catalase (CAT) and superoxide dismutase (SOD). The current study recommends 40 μM SNP as optimum concentration for preserving floral quality and extending display period of C. ajacis spikes. Together, these findings reveal that SNP at proper dosage can efficiently alleviate deteriorative postharvest changes by modulating physiological and biochemical mechanisms underlying senescence.

Superoxide Dismutase SODs are defense associated proteins that detoxify ROS and primarily serve as scavengers. They have been described in numerous plant species, but their in-depth characterization in Brassica rapa has not been reported. Therefore, the present investigation on genome wide study of SOD gene family was conducted to identify BrSOD genes, their domain-based organization, gene structure analysis, phylogenetic analysis, intron-exon structure of genes and expression analysis. The sequence characterization of Super oxide dismutase gene family in Brassica rapa, their syntenic associateship of conserved motifs and phylogenetic correlationship, prediction of cis-elements and determing the expression analysis in distinct tissues namely plant callus, root, stem, leaf, flower, and silique under abiotic conditions have been analysed using different software’s. The study on SOD gene family identified 17 BrSOD genes which were grouped into eight BrCu-ZnSODs and nine BrFe-MnSODs domain-based organization. Furthermore, the conserved character of BrSODs were confirmed by intron-exon organisation, motif arrangements and domain architectural investigations. Expression analysis using RNA Sequence data of different developmental stages proclaimed that genes were manifested in all six tissues with an exception of BrCu-ZnSOD3, which was not manifested in roots; however, whose transcript was detected in all other tested tissues. The study has genome wide insight into the occurrence and functional specifications of BrSOD gene family in Brassica rapa that can be potentially utilized in breeding program for resilience to climate change and abiotic stresses tolerance Brassica variety.

Agriculture is changing at a faster rate than ever before, aiming to catch up with our ever-increasing world population. A technology conquering the agricultural sector is the agribot. Agribots are, as the name suggests, agricultural robots, meaning they are machines that have specifically been designed to autonomously carry out farming-related activities. The following chapter gives the reader a review on the development and the wide applications these robots deliver and shows the potential impact they could bring to farming communities worldwide. However, specific emphasis will be placed on India, being one of the largest agricultural societies in the world. We will also highlight what is required to develop these robots further, to make them accessible to and accepted by the agricultural community.

Agriculture is a venture that is wholly dependent on conditions afforded by weather. Hence, achievement in any agricultural activity greatly depends on the extent to which weather could be accurately predicted, interpreted, and applied. In addition to field practices, proper planning and management of agricultural activities cannot be conducted effectively without grasping the environmental endowments, especially the weather components. Oftentimes, planners and farm managers expend much effort and skill in realizing the nexus between weather and agriculture to ascertain the proper weather conditions that would avail vital decisions on beneficial agricultural undertakings. Accordingly, this chapter attempts to assess sets of information from previous studies on precision agriculture vis-a-vis weather studies including forecasting. Further emphasis is placed on the results that the incorporation of modern tools such as artificial intelligence and data analytics would produce in the agricultural process. With the influence of climate change on agricultural practices, future agricultural interventions would require enormous machine power and intelligence to address issues of sustainability. This chapter presents various models and provides recommendations that would aid in promoting the sustainability of precision agriculture for food production and safety across various agricultural dealings.

Freshwater farming is gaining popularity in sub-Saharan Africa. It includes shrimp and freshwater fish. Outside the natural habitats of freshwater rivers, streams, and lakes, artificial breeding habitats such as home ponds are constructed to enhance fish production. The quality of water cannot be overemphasized, as it plays a vital role in the continuous survival of fish. Water quality hinges on physical, biological, and chemical characteristics, including ammonia content, quantity of dissolved oxygen, unregulated power of hydrogen (pH) and temperature, and pressure. The continuous monitoring and measurement of these parameters to ensure the sustainability of fish production does pose some challenges to subsistence and commercial fish farmers alike. Smarter fish farming would need improved technology. This chapter presents a detailed case study of a small-scale farming business that integrates the Internet of Things (IoT) as a technological improvement solution. This chapter addresses the various challenges through the analysis and design of an IoT-based monitoring system using a multisensor board with interconnected sensors for all necessary parameters. The chapter also sheds light on various cost-effective channels of disseminating periodic status information to farmers. The chapter concludes that a cost-effective IoT solution is realizable if consideration is given to the materials that can ensure low maintenance costs over a long period of operation.

Monitoring climate conditions has continuously gained much attention in recent times due to the dynamism associated with weather across different agricultural jurisdictions. There are several climate monitoring systems ranging from simple to more advanced automated weather monitoring systems. However, innovation drives technological advances and the place of evolving dynamic technologies such as artificial intelligence, the Internet of Things, and big data cannot be overemphasized. Modern hybrid technologies are likely to integrate data from traditional and unstructured sources, including ground-based stations, satellite observations, and prediction models, to monitor, predict, and estimate variations in weather and climatic conditions. This has become imperative in the framework of climate change, as climate inconsistency increases and historical outlines are unsustainable. The devastating effects resulting from climate inconsistency could exert massive distortions on agricultural activities and their precursors. In such a case, high-precision techniques, procedures, and tools would be invaluable in driving projects involving monitoring, data extraction, analysis, prediction, and planning tasks, then being directed to curtail such challenges. This chapter explores more intricacies of global climate conditions and systems. It presents some detailed thoughts on advances in weather monitoring systems using historical information, measurements, models, algorithms, and computations. A proper perspective for sustainable smart agriculture for food production, safety, and security is elucidated. The chapter concludes with recommendations made on future enhancements, adjustments, and evaluation of the models.

Sustainable food security is a vision of many governments and international organizations across the globe with its goal directed at preventing hunger, starvation, food shortages, and mortality. These are dreaded indicators that had been long fingered as principal problems that would envelop the world around 2050 when the global population is estimated to hit 9 billion. Global organizations such as the Food and Agricultural Organization (FAO), Heifer International, the International Fund for Agricultural Development, etc., have consistently demonstrated strategies that would help eradicate global hunger by 2030. As sustained efforts are directed at thousands of remarkable projects worldwide, it is important to reemphasize that such projects could only be realized through insights derived from meaningful information and knowledge resources. In agriculture, there has been a rapid rise of late in the modernization and deployment of automated agricultural information systems (agricultural databases, smart systems, Internet of Things (IoT) systems, agribots, etc.) to aid planning, production, and distribution processes. Interestingly, most of these global knowledge and information bases are in the cloud and other Internet infrastructure. The trend in global information storage has sensitive information (government policies, orders, decisions, plans, etc., on agriculture and food production) from public and private domains residing on one or more cyberinfrastructures. That leads to an attendant risk of sabotage and breaches. This is due to the ever-growing attempts on critical infrastructure worldwide by apologists, cyberterrorists, and cybercriminals. This could result in project failures, irrecoverable losses, and governance and policy failures, to name a few. This chapter presents a detailed account of the various cyberthreats, especially cyberespionage and cyberterrorism that are capable of sabotaging the collective strategies of organizations and entities pursuing sustainable food security. In this chapter, we discuss motivations, ideologies, and strategies behind cyberespionage against agriculture and related platforms; the architecture, categorization, propagation, and attack methods; the socioeconomic implications of these attacks; countermeasures; and legal frameworks.

Shrimp contribute immensely to useful nutrients devoid of health hazards owing to their negligible carbohydrate and saturated fat constituents. They are a highly demanded seafood mainly due to their health benefits, as this crustacean is rich in protein, selenium, vitamin B12, iron, phosphorus, niacin, zinc, magnesium, iodine, omega-3 fatty acids, anticarcinogens, and astaxanthin antioxidants. Hence, they are in high demand in jurisdictions such as the continental United States and Europe. The demand across different jurisdictions reflects their economic value in the food production and supply chain. Phylogenetically, true shrimp are of the suborder pleocyemata from the order Decapods in the Malacostraca class of the subphylum Crustacea of the phylum Arthropoda. This order places them in the same category with other important seafood such as crayfish, crabs, and lobsters. They are often scientifically distinguished from prawns of the suborder dendrobranchiata, though both animals share many features. Hence, the terms prawn and shrimp are used interchangeably in most jurisdictions. It is believed that 90% of shrimp consumed is produced in private farms operated by individuals or organizations in different parts of the globe. The production of shrimp is affected by three major factors: environmental conditions, feed, and diseases. Accordingly, every aquaculture or farm designed for efficiency must take into account these factors. This chapter has carefully articulated the various environmental conditions and feed requirements for setting up saline water aquaculture. In this chapter, we also discuss diseases that affect the growth and turnover of shrimp. However, through intuition and scientific evidence, we are expend more effort on environmental conditions and feed because diseases largely exploit unwholesome gaps in the two factors, that is, the environment and aqua feed. Discussions on the interrelationships that exist among the environmental factors are stressed and their impact documented. Going forward, a predictive model is proposed. The proposed model is a fuzzy logic system, which would use the most interesting parameters such as pH, temperature, turbidity, salinity, dissolved oxygen, and nitrates as fuzzy inputs to predict the optimal mix of environmental conditions that favors the efficient growth of shrimp. The chapter also discusses the architecture of the fuzzy logic system and how it could be extended to integrate sensors for real-time effective monitoring and control.

The influence of varying concentrations (0, 1, 3, 4, 5, 6, 8, and 10 % v/v) of neem (

Today, the threat of crude oil pollution globally, has been a resounding epoch of ecosystem degradation. This affects the lives of flora and fauna in the ecosystem as well as influence the human's economic needs. The aim of this study is to assess the heavy metals and petroleum hydrocarbons concentrations (crude oil pollutants) in agricultural soils of selected communities in Niger-Delta region. Models were used to assess the crude oil pollution loads and its source apportionment. The results from the principal components analysis (PCA) for the heavy metals (HMs) and total petroleum hydrocarbons (TPHs) in soils showed high loading factors > 0.32. The source allotment were both of crustal and human origin. The cluster analysis for the physical and chemical parameters of the HMs and TPHs showed that stations 1, 5, 2, 4, 6 and 7 and 2, 6, 7 and 9 were similar respectively. The outcome of the ecological risk status of the sampled soils, showed that the metals in the nine sampling stations were at the slight risk level with Cd being the main donor. The results of the health risk for both non-carcinogenic and carcinogenic pathways for the metals were

Salt stress is one of the major constraints affecting plant growth and agricultural productivity worldwide. Sorghum is a valuable food source and a potential model for studying and better understanding the salt stress mechanics in the cereals and obtaining a more comprehensive knowledge of their cellular responses. Herein, we examined the effects of salinity on reserve mobilization, antioxidant potential, and expression analysis of starch synthesis genes. Our findings show that germination percentage is adversely affected by all salinity levels, more remarkably at 120 mM (36% reduction) and 140 mM NaCl (46% reduction) than in the control. Lipid peroxidation increased in salt-susceptible genotypes (PC-5: 2.88 and CSV 44F: 2.93 nmloe/g.FW), but not in tolerant genotypes. SSG 59-3 increased activities of α-amylase, and protease enzymes corroborated decreased starch and protein content, respectively. SSG 59-3 alleviated adverse effects of salinity by suppressing oxidative stress (H2O2) and stimulating enzymatic and non-enzymatic antioxidant activities (SOD, APX, CAT, POD, GR, and GPX), as well as protecting cell membrane integrity (MDA, electrolyte leakage). A significant increase (p ≤ 0.05) was also observed in SSG 59-3 with proline, ascorbic acid, and total carbohydrates. Among inorganic cations and anions, Na+, Cl−, and SO42− increased, whereas K+, Mg2+, and Ca2+ decreased significantly. SSG 59-3 had a less pronounced effect of excess Na+ ions on the gene expression of starch synthesis. Salinity also influenced Na+ ion efflux and maintained a lower cytosolic Na+/K+ ratio via concomitant upregulation of SbNHX-1 and SbVPPase-I ion transporter genes. Thus, we have highlighted that salinity physiologically and biochemically affect sorghum seedling growth. Based on these findings, we highlighted that SSG 59-3 performed better by retaining higher plant water status, antioxidant potential, and upregulation of ion transporter genes and starch synthesis, thereby alleviating stress, which may be augmented as genetic resources to establish sorghum cultivars with improved quality in saline soils.

Managing irrigation efficiently is paramount given the uncertainty in the future availability of water and rising demand for this resource. Scheduled irrigation significantly influences vegetative growth through improving crop physiology and nutrient uptake and use efficiency. Influence of different irrigation treatments (100%, 75%, and 50% volume of Class A pan evapotranspiration) applied at four different phenological stages (flowering and fruit set (C1), fruit growth stage (C2), pre-harvest stage (C3), and throughout the growing season (C4)) through drip along with a control (rainfed) on leaf physiology, nutrient content, and uptake through gene expression was studied on Super Chief Sandidge variety raised on M9T337 (5 and 6 years old) grown at a spacing of 1.5 × 3 m (2222 plants/ha) under high density condition of Kashmir Himalayan range of India. A comparison of data reveals that drip irrigation at 100% Crop evapotranspiration (ETc) increased leaf area by 60% compared to rainfed conditions. Leaf area significantly increased in plants irrigated throughout the growing season (C4) and during flowering and fruit set stage (C1). Irrigation amount likely does not have any influence on leaf development after the fruit growth stage. Stomatal opening and their size greatly vary from no irrigation to optimum irrigation in these plants. High density apple trees exposed to optimum irrigation levels (100% and 75% ET) had significantly higher concentrations of nutrients (N, P, and K) in their leaf tissues. The concentration of Ca and Mg content in leaf tissues are greatly influenced by the optimum supply of water during the early growth stages of apple growth. The availability of water significantly influences nutrient transporter gene expression and thus nutrient uptake by regulating such transporter genes. It is therefore observed that proper irrigation during C1 and stage C2 stage are the critical growth stages of apple for optimum leaf physiological activity and proper nutrient uptake.

The present investigation was committed to examining the effect of soil spiked with diesel contamination (0, 1.5, 2.5, 3.5 g diesel kg

The carcinogenic attribute of arsenic (As) has turned the world to focus more on the decontamination and declining the present level of As from the environment especially from the soil and water bodies. Phytoremediation has achieved a status of sustainable and eco-friendly approach of decontaminating pollutants, and in the present study, an attempt has been made to reveal the potential of As remediation by a halophyte plant, Acanthus ilicifolius L. Special attention has given to analyse the morphological, physiological and anatomical modulations in A. ilicifolius, developed in response to altering concentrations of Na