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The phenotypic and genotypic characterization of eight rhizobial isolates obtained from Arachis hypogaea nodules grown under stress environment was performed. Isolates were screened for their ability to tolerate different abiotic stresses (high temperature (60° C), salinity (1–5% (w/v) NaCl), and pH (1–12). The genomic analysis of 16S rRNA and housekeeping genes (atpD, recA, and glnII) demonstrated that native groundnut rhizobia from these stress soils are representatives of fast growers and phylogenetically related to Rhizobium sp. The phenotypic characterization (generation time, carbon source utilization) also revealed the isolates as fast-growing rhizobia. All the isolates can tolerate NaCl up to 3% and were able to grow between 20 and 37 °C with a pH between 5 to 10, indicating that the isolates were alkali and salt-tolerant. The tested isolates effectively utilize mono and disaccharides as carbon source. Out of eight, three rhizobial isolates (BN-20, BN-23, and BN-50) were able to nodulate their host plant, exhibiting their potential to be used as native groundnut rhizobial inoculum. The plant growth promoting characterization of all isolates revealed their effectiveness to solubilize inorganic phosphate (56–290 µg mL−1), synthesize indole acetic acid (IAA) (24–71 µg mL−1), and amplification of nitrogen fixing nifH gene, exploring their ability to be used as groundnut biofertilizer to enhance yield and N2-fixation for the resource poor farmers of rainfed Pothwar region.

This study aimed to realize Sustainable Development Goals (SDGs), i.e., no poverty, zero hunger, and sustainable cities and communities through the implementation of an intelligent cattle-monitoring system to enhance dairy production. Livestock industries in developing countries lack the technology that can directly impact meat and dairy products, where human resources are a major factor. This study proposed a novel, cost-effective, smart dairy-monitoring system by implementing intelligent wireless sensor nodes, the Internet of Things (IoT), and a Node-Micro controller Unit (Node-MCU). The proposed system comprises three modules, including an intelligent environmental parameter regularization system, a cow collar (equipped with a temperature sensor, a GPS module to locate the animal, and a stethoscope to update the heart rate), and an automatic water-filling unit for drinking water. Furthermore, a novel IoT-based front end has been developed to take data from prescribed modules and maintain a separate database for further analysis. The presented Wireless Sensor Nodes (WSNs) can intelligently determine the case of any instability in environmental parameters. Moreover, the cow collar is designed to obtain precise values of the temperature, heart rate, and accurate location of the animal. Additionally, auto-notification to the concerned party is a valuable addition developed in the cow collar design. It employed a plug-and-play design to provide ease in implementation. Moreover, automation reduces human intervention, hence labor costs are decreased when a farm has hundreds of animals. The proposed system also increases the production of dairy and meat products by improving animal health via the regularization of the environment and automated food and watering. The current study represents a comprehensive comparative analysis of the proposed implementation with the existing systems that validate the novelty of this work. This implementation can be further stretched for other applications, i.e., smart monitoring of zoo animals and poultry.

Saffron, also known as “the golden spice”, is one of the most expensive crops in the world. The expensiveness of saffron comes from its rarity, the tedious harvesting process, and its nutritional and medicinal value. Different countries of the world are making great economic growth due to saffron export. In India, it is cultivated mostly in regions of Kashmir owing to its climate and soil composition. The economic value generated by saffron export can be increased manyfold by studying the agronomical factors of saffron and developing a model for artificial cultivation of saffron in any season and anywhere by monitoring and controlling the conditions of its growth. This paper presents a detailed study of all the agronomical variables of saffron that have a direct or indirect impact on its growth. It was found that, out of all the agronomical variables, the important ones having an impact on growth include corm size, temperature, water availability, and minerals. It was also observed that the use of IoT for the sustainable cultivation of saffron in smart cities has been discussed only by very few research papers. An IoT-based framework has also been proposed, which can be used for controlling and monitoring all the important growth parameters of saffron for its cultivation.

Soil salinity and the use of saline groundwater are two major constraints in crop production, which covers a ~1.0 billion ha area of arid and semi-arid regions. The improved drainage function of soil can modify the salty growing environment for higher agricultural production. The present study evaluated the effectiveness of cut-soiler-constructed rice residue-filled preferential shallow subsurface drainage (PSSD) to improve the drainage function and its effect on the yield, quality and plant–water relations of mustard over 2019–2021. Cut-soiler-simulated drains were made in a semi-controlled lysimeter (2 × 2 × 3; L*W*H m) as the main plot treatment in a double replicated split–split experiment with two soil types (subplot) and three irrigation water salinities (4, 8 and 12 dS m−1) as the sub-sub-plot treatment. The drainage volume of variable salinity (EC), dependent on the total water input, was substantially higher in the rainy season (April to October), i.e., 16.6, 7.76 and 12.0% during 2018, 2019 and 2020, with 1.7, 0.32 and 0.77 kg salt removal per lysimeter, compared to the post-rainy season. The mustard seed, straw and biological yields were improved by 31.4, 14.41 and 18.08%, respectively, due to a positive effect on plant–water relations. The mustard seeds produced in the cut-soiler-treated plots recorded higher oil, crude fiber and protein contents and a lower erucic acid content. The increase in salt load, by higher-salinity irrigation water, was also efficiently managed by using cut-soiler PSSD. It was found that the saline irrigation water up to 12.0 dS m−1 can be used under such PSSD without any extra salt loading. The present study showed the potential of cut-soiler PSSD in root zone salinity management by improving drainage in salt-affected arid regions.

Sufficient production, consistent food supply, and environmental protection in urban +settings are major global concerns for future sustainable cities. Currently, sustainable food supply is under intense pressure due to exponential population growth, expanding urban dwellings, climate change, and limited natural resources. The recent novel coronavirus 2019 (COVID-19) pandemic crisis has impacted sustainable fresh food supply, and has disrupted the food supply chain and prices significantly. Under these circumstances, urban horticulture and crop cultivation have emerged as potential ways to expand to new locations through urban green infrastructure. Therefore, the objective of this study is to review the salient features of contemporary urban horticulture, in addition to illustrating traditional and innovative developments occurring in urban environments. Current urban cropping systems, such as home gardening, community gardens, edible landscape, and indoor planting systems, can be enhanced with new techniques, such as vertical gardening, hydroponics, aeroponics, aquaponics, and rooftop gardening. These modern techniques are ecofriendly, energy- saving, and promise food security through steady supplies of fresh fruits and vegetables to urban neighborhoods. There is a need, in this modern era, to integrate information technology tools in urban horticulture, which could help in maintaining consistent food supply during (and after) a pandemic, as well as make agriculture more sustainable.

Background: Temperate agroforestry is regarded as a sustainable alternative to monoculture agriculture due to enhanced provisioning of ecosystem services. Plant health and food safety are crucial requirements for sustainable agriculture; however, studies of fungal diseases and mycotoxin contamination of crops grown under temperate agroforestry are lacking. This study therefore aimed to compare fungal colonization and mycotoxin contamination of crops grown in temperate agroforestry against conventional monoculture. Methods: The biomass of plant pathogenic fungi in oilseed rape plants and barley and wheat grain harvested in 2016 to 2018 at four paired agroforestry and monoculture sites was quantified using species-specific real-time PCR. Mycotoxin content of barley and wheat grain was determined by HPLC-MS/MS. Results: The colonization of oilseed rape plants with the vascular pathogen Verticillium longisporum and wheat grain with the head blight pathogen Fusarium tricinctum was lower in agroforestry than in conventional monoculture. Mycotoxin content of barley and wheat grain did not differ between agroforestry and monoculture systems and did not exceed the legal limits of the EU. Remarkably, fumonisin B1 was detected in wheat grains at two sites in two years, yet the low levels found do not raise food safety concerns. No differences were found between the two production systems with regard to infection of wheat and barley grain with five Fusarium species (F. avenaceum, F. culmorum, F. graminearum, F. poae, and F. proliferatum) and oilseed rape with fungal pathogens Leptosphaeria biglobosa, Leptosphaeria maculans, and Sclerotinia sclerotiorum. Conclusions: Temperate agroforestry does not negatively affect the infection of wheat, barley and oilseed rape with major fungal pathogens though it may suppress the infection of oilseed rape with V. longisporum and wheat grain with F. tricinctum. Furthermore, temperate agroforestry does not increase mycotoxin contamination of barley and wheat. Therefore, temperate agroforestry does not negatively affect food safety.

Today, the global food security is one of the most pressing issues for humanity, and, according to Food and Agriculture Organisation (FAO), the increasing demand for food is likely to grow by 70% until 2050. In this current condition and future scenario, the agricultural production is a critical factor for global food security and for facing the food security challenge, with specific reference to many African countries, where a large quantities of rice are imported from other continents. According to FAO, to face the Africa’s inability to reach self-sufficiency in rice, it is urgent “to redress to stem the trend of over-reliance on imports and to satisfy the increasing demand for rice in areas where the potential of local production resources is exploited at very low levels” The present study was undertaken to design a new method for land evaluation based on soil quality indicators and remote sensing data, to assess and map soil suitability for rice crop. Results from the investigations, performed in some areas in the northern part of the Nile Delta, were compared with the most common approaches, two parametric (the square root, Storie methods) and two qualitative (ALES and MicrioLEIS) methods. From the qualitative point of view, the results showed that: (i) all the models provided partly similar outputs related to the soil quality assessments, so that the distinction using the crop productivity played an important role, and (ii) outputs from the soil suitability models were consistent with both the satellite Sentinel-2 Normalize Difference Vegetation Indices (NDVI) during the crop growth and the yield production. From the quantitative point of view, the comparison of the results from the diverse approaches well fit each other, and the model, herein proposed, provided the highest performance. As a whole, a significant increasing in R2 values was provided by the model herein proposed, with R2 equal to 0.92, followed by MicroLES, Storie, ALES and Root as R2 with value equal to 0.87, 0.86, 0.84 and 0.84, respectively, with increasing percentage in R2 equal to 5%, 6% and 8%, respectively. Furthermore, the proposed model illustrated that around (i) 44.44% of the total soils of the study area are highly suitable, (ii) 44% are moderately suitable, and (iii) approximately 11.56% are unsuitable for rice due to their adverse physical and chemical soil properties. The approach herein presented can be promptly re-applied in arid region and the quantitative results obtained can be used by decision makers and regional governments.

This work intended to explore some motivations that influence people’s eating habits towards sustainability. This was an observational, cross-sectional study, carried out by questionnaire survey on a non-probabilistic sample of 10,067 participants from 13 countries (Argentina, Brazil, Croatia, Greece, Hungary, Latvia, Lithuania, Poland, Portugal, Serbia, Slovenia, Romania and United States). Results indicated that people prefer fresh local foods from the season, being important because it allows transportation and storage to be reduced, which in many cases implies refrigeration systems and consequent energy expenditure. Although people avoid food waste at home, the awareness for the waste at restaurants still needs to be improved. Consumers seem to prefer foods that have been produced and packed in sustainable ways but still give importance to the package—understandable for food products. The results also indicated significant differences in the food choice motivations between groups for all sociodemographic variables tested (age, sex, marital status, education, professional area, living environment and country), but the association was high only for variable country. Additionally, a tree classification analysis allowed to identify the relative importance of the influential variables on the sustainable food choices, with country being the most important, followed by age and sex. Additionally, discriminant function analysis allowed establishing a model for the relation between country and six variables accounting for preservation of biodiversity, respect for life, save natural resources, save energy, reduce industrial pollution and minimal packaging. Although with some limitations, this study brings valuable insight into some aspects linked with sustainable food choices on a number of countries and how people shape their food choices according to some sustainability issues.