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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.

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.

Cover crops (CCs) are a promising strategy for maintaining and enhancing agroecosystem sustainability, yet CCs’ effects on the subsequent crop yield are highly variable. To quantitatively synthesize the effects of CCs on subsequent crop yield, a meta-analysis of 672 observations collected from 63 recent studies (2015 to 2021) in temperate climates was conducted. Legume CC species increased subsequent crop yield significantly more than grass (by 14%), nonlegume broadleaves (by 7%), and mixtures (by 2%). Incorporation of CC residue into soil increased crop yield by approx. 15% compared to leaving the CC residue on the soil surface. Relative to the no-CC control, the adoption of grass and legume CC species in non-organic vegetable cropping systems enhanced crop yield by 14% and 19%, respectively. Likewise, crop yield with legume CCs in coarse and medium textured soil, and under high precipitation conditions (>700 mm), was significantly greater than the no-CC control by 18%, 4%, and 11%, respectively. Cover crops significantly increased vegetable crop yields and decreased the silage corn yield; however, grain corn, soybean, and winter wheat yield did not decrease with CC. Adoption of CC in no-tillage and plow tillage systems contributed to an increase in crop yield compared to the no-CC control. Our meta-analysis highlights that crop yield response to CC might become more robust when pedo-climatic conditions and agronomic factors are considered.

A new method for measuring the porosity of individual 2D raster patches in a GIS for characterizing the combined complexity of a shape’s edge in conjunction with its internal perforations is developed. The method is centered on comparing the number of cellular edge–edge joins relative to the theoretical maximum number of similar joins possible given a set number of cells comprising a landscape patch. As this porosity (Φ) increases, the patch (or shape) can be viewed as deviating from a maximally compact form, comprising higher edge complexity and internal heterogeneity (inclusion of perforations). The approach is useful for characterizing shapes for which a simple perimeter- or area-based metric misses the internal complexity and where the porosity of the patch may provide insight into spatial processes leading to the development of the landscape fabric. I present theoretical results to illustrate the mechanics of the approach and a small case study of boreal wildfire residual vegetation patches in Ontario, where real resulting wildfire process-driven landscape patches are assessed for their porosity at five spatial resolutions. The results indicate that naturally occurring and unsuppressed boreal wildfires in the study area typically produce residual vegetation patches with an average porosity of 17.6%, although this value varies slightly with the spatial resolution of the data representation.

Using survey information of 150 randomly selected households across 21 villages of the forest-rich district of Swat, Pakistan, this study assessed households’ decision-making behaviors in depending on income from nearby forested land using socio-economic attributes. The evidence from the study may aid in making the existing policies be better targeted toward families that depend on the forest for income. Descriptive statistics and econometric techniques such as logit and tobit were used to analyze the data. Respondent households obtained the highest share of their income from off-farm activities (37%) and least from forest activities (16%). Fuelwood constitutes the biggest share (66%) of forest income, followed by medical plants (20%) and fodder (13%). We found that households with more physical assets, more family members working in off-farm jobs, and households earning more income from off-farm jobs were significantly and negatively associated with households’ decision to depend on forest income and total income obtained. We also found that households with less distance to the market and membership to joint forest management committees (JFMCs) were significantly and negatively associated with households’ total income obtained. However, household size was significantly and positively related to households’ decision of forest dependency. The study recommends the creation of off-farm opportunities and inclusion of local people in the management of forests through establishment of JFMCs, particularly for large and poor families.

Meat replacers could play a role in achieving more plant-based diets, but their current consumption is limited. The present modelling study aimed to explore the nutritional and greenhouse gas emissions impacts of meat replacers. Using dietary surveys from Denmark, Czech Republic, Italy and France (~6500 adults), we composed alternative diets in which all the meat in the observed diet (in grams) was substituted by similar use meat replacers (with and without fortification). Starting from the observed diets and meat-replacement diets, diets with improved adherence to food-based dietary guidelines (FBDGs) were modelled using Data Envelopment Analysis. These improved diets were then further optimised for dietary preferences (MaxP, diet similarity index), nutrient quality (MaxH, Nutrient Rich Diet score, NRD15.3) or diet-related greenhouse gas emissions (GHGE) (MaxS, CO2 equivalents). In all optimised modelled diets, the total amount of meat was lower than in the observed diets, i.e., 30% lower in the MaxP, 50% lower in the MaxH, and 75% lower in the MaxS diets. In the MaxP diet, NRD15.3 was ~6% higher, GHGE was ~9% lower, and ~83% of food intake remained similar. In the MaxH diet, NRD15.3 was ~17% higher, GHGE was ~15% lower, and ~66% of food intake remained similar. In the MaxS diet, NRD15.3 was ~9% higher, GHGE was ~33% lower, and ~65% of food intake remained similar. When using fortified meat replacers, for all modelled diets, the diet similarity was on average 2% lower and the GHGE reduction was on average 3% higher as compared with the same scenarios without fortification. This analysis showed that meat replacers, provided their preference is similar to meat, can provide benefits for GHGE, without necessarily compromising nutrient quality.

During the last decades, organic food products have become the main sustainable alternative to conventional food consumption. Among the several organic food attributes that consumers recognize in organic food, healthiness has been reported as the primary motivation to buy products certified as organic. The objective of the current study is to assess the relative weight of the health attribute among other recognized organic food attributes. To achieve this aim, a multiple price list (MPL) methodology is adopted to elicit consumers’ Willingness to Pay (WTP) for organic extra virgin olive oil (EVOO). Findings show that the contribution of the health attribute to determine the average premium price for organic EVOO is 78.9% of its total premium price. The study generates managerial implications to promote further expansion of the organic food market.

It is often said that innovations create winners and losers. All innovations are somewhat disruptive, but some have more distributed effects. We have a sense of who the winners are and how much they gain. Yet, how much do losers actually lose? Organic farmers frequently like to publicly announce that they are the losers following the commercialization of genetically modified (GM) crops, yet consumers in search of non-GM products have helped increase demand for organic products, something that would not have occurred in the absence of GM crops. Are organic farmers really losers? This article lays out the argument that were it not for the commercialization of GM crop varieties in the mid-1990s, organic production and food sectors would not be at the level they enjoy today. That is, the commercialization of GM crops has made the organic industry better off than had GM crops not been commercialized. Theoretical modelling of the organic benefits is complemented by supportive market data. The article concludes that in spite of numerous vocal offerings about the adverse impacts suffered by the organic industry due to GM crop production, the organic industry has gained significantly from that which they vociferously criticize.