Conventional food supply chains are centralized in nature and possess challenges pertaining to a single point of failure, product irregularities, quality compromises, and loss of data. Numerous cases of food fraud, contamination, and adulteration are daily reported from multiple parts of India, suggesting the absolute need for an upgraded decentralized supply chain model. A country such as India, where its biggest strength is its demographic dividend, cannot afford to malnutrition a large population of its children by allowing them to consume contaminated and adulterated dairy products. In view of the gravity of the situation, we propose a blockchain-enabled supply chain platform for the dairy industry. With respect to the supply chain platform, the dairy products of choice include milk, cheese, and butter. Blockchain is one of the fastest growing technologies having widespread acceptance across multiple industry verticals. Blockchain possesses the power to transform traditional supply chains into decentralized, robust, transparent, tamper proof, and sustainable supply chains. The proposed supply chain platform goes beyond the aspect of food traceability and focuses on maintaining the nutritional values of dairy products, identification of adulteration and contamination in dairy products, the increasing economic viability of running a dairy farm, preventing counterfeit dairy products, and enhancing the revenue of the dairy company. The paper collates the mentioned functionalities into four distinct impact dimensions: social, economic, operations, and sustainability. The proposed blockchain-enabled dairy supply chain platform combines the use of smart contracts, quick response code (QR code) technology, and IoT and has the potential to redefine the dairy supply chains on socio-economic, operational, and sustainability parameters.

Agrivoltaics (Agri-PV, AV)—the joint use of land for the generation of agricultural products and energy—has recently been rapidly gaining popularity, as it can significantly increase income per unit of land area. In a broad sense, AV systems can include converters of solar energy, and also energy from any other local renewable source, including bioenergy. Current approaches to AV represent the evolutionary development of agroecology and integrated PV power supply to the grid, and can result in nearly doubled income per unit area. AV could provide a basis for a revolution in large-scale unmanned precision agriculture and smart farming which will be impossible without on-site power supply, reduction of chemical fertiliser and pesticides, and yield processing on site. These approaches could dramatically change the logistics and the added value production chain in agriculture, and so reduce its carbon footprint. Utilisation of decommissioned solar panels in AV could halve the cost of the technology and postpone the need for bulk PV recycling. Unlike the mainstream discourse on the topic, this review feature focuses on the possibilities for AV to become more strongly integrated into agriculture, which could also help in resolution of relevant legal disputes (considered as neither rather than both components).

Over the last couple of years, Blockchain technology has emerged as a game-changer for various industry domains, ranging from FinTech and the supply chain to healthcare and education, thereby enabling them to meet the competitive market demands and end-user requirements. Blockchain technology gained its popularity after the massive success of Bitcoin, of which it constitutes the backbone technology. While blockchain is still emerging and finding its foothold across domains, Cloud computing is comparatively well defined and established. Organizations such as Amazon, IBM, Google, and Microsoft have extensively invested in Cloud and continue to provide a plethora of related services to a wide range of customers. The pay-per-use policy and easy access to resources are some of the biggest advantages of Cloud, but it continues to face challenges like data security, compliance, interoperability, and data management. In this article, we present the advantages of integrating Cloud and blockchain technology along with applications of Blockchain-as-a-Service. The article presents itself with a detailed survey illustrating recent works combining the amalgamation of both technologies. The survey also talks about blockchain–cloud services being offered by existing Cloud Service providers.

This article presents the results of the start-up of continuous production of biohydrogen from cheese whey (CW) in an anaerobic filter (AF) and anaerobic fluidized bed (AFB) with a polyurethane carrier. Heat and acid pretreatments were used for the inactivation of hydrogen-scavengers in the inoculum (mesophilic and thermophilic anaerobic sludge). Acid pretreatment was effective for thermophilic anaerobic sludge to suppress methanogenic activity, and heat treatment was effective for mesophilic anaerobic sludge. Maximum specific yields of hydrogen, namely 178 mL/g chemical oxygen demand (COD) and 149 mL/g COD for AFB and AF, respectively, were obtained at the hydraulic retention time (HRT) of 4.5 days and organic load rate (OLR) of 6.61 kg COD/(m³ day). At the same time, the maximum hydrogen production rates of 1.28 and 1.9 NL/(L day) for AF and AFB, respectively, were obtained at the HRT of 2.02 days and OLR of 14.88 kg COD/(m³ day). At the phylum level, the dominant taxa were Firmicutes (65% in AF and 60% in AFB), and at the genus level, Lactobacillus (40% in AF and 43% in AFB) and Bifidobacterium (24% in AF and 30% in AFB).

In the past couple of years, the world has come to realize the importance of renewable sources of energy and the disadvantages of excessive use of fossil fuels. Numerous studies have been conducted to implicate the benefits of artificial intelligence in areas of green energy production. Artificial intelligence (AI) and machine learning algorithms are believed to be the driving forces behind the fourth industrial revolution and possess capabilities for interpreting non-linear relationships that exist in complex problems. Sustainable biofuels are derived from renewable resources such as plants, crops, and waste materials other than food crops. Unlike traditional fossil fuels such as coal and oil, biofuels are considered to be more sustainable and environmentally friendly. The work discusses the transesterification of jatropha oil into biodiesel using KOH and NaOH as alkaline catalysts. This research aims to examine and optimize the nonlinear relationship between transesterification process parameters (molar ratio, temperature, reaction time, and catalyst concentration) and biodiesel properties. The methodology employed in this study utilizes AI and machine learning algorithms to predict biodiesel properties and improve the yield and quality of biodiesel. Deep neural networks, linear regression, polynomial regression, and K-nearest neighbors are the algorithms implemented for prediction purposes. The research comprehensively examines the impact of individual transesterification process parameters on biodiesel properties, including yield, viscosity, and density. Furthermore, this research introduces the use of genetic algorithms for optimizing biodiesel production. The genetic algorithm (GA) generates optimal values for transesterification process parameters based on the desired biodiesel properties, such as yield, viscosity, and density. The results section presents the transesterification process parameters required for obtaining 72%, 85%, and 98% biodiesel yields. By leveraging AI and machine learning, this research aims to enhance the efficiency and sustainability of biodiesel production processes.