Effects of environmental change on population nutrition and health: A comprehensive framework with a focus on fruits and vegetables

Exploration of the rhizosphere microbiome of native plant Ceanothus velutinus - an excellent resource of plant growth-promoting bacteria

Continuous demand for an increase in food production due to climate change and a steady rise in world population requires stress-resilient, sustainable agriculture. Overuse of chemical fertilizers and monoculture farming to achieve this goal deteriorated soil health and negatively affected its microbiome. The rhizosphere microbiome of a plant plays a significant role in its growth and development and promotes the plant's overall health through nutrient uptake/availability, stress tolerance, and biocontrol activity. The Intermountain West (IW) region of the US is rich in native plants recommended for low water use landscaping because of their drought tolerance. The rhizosphere microbiome of these native plants is an excellent resource for plant growth-promoting rhizobacteria (PGPR) to use these microbes as biofertilizers and biostimulants to enhance food production, mitigate environmental stresses and an alternative for chemical fertilizer, and improve soil health. Here, we isolated, purified, identified, and characterized 64 bacterial isolates from a native plant, Ceanothus velutinus, commonly known as snowbrush ceanothus, from the natural habitat and the greenhouse-grown native soil-treated snowbrush ceanothus plants. We also conducted a microbial diversity analysis of the rhizosphere of greenhouse-grown native soil-treated and untreated plants (control). Twenty-seven of the 64 isolates were from the rhizosphere of the native region, and 36 were from the greenhouse-grown native soil-treated plants. These isolates were also tested for plant growth-promoting (PGP) traits such as their ability to produce catalase, siderophore, and indole acetic acid, fix atmospheric nitrogen and solubilize phosphate. Thirteen bacterial isolates tested positive for all five plant growth-promoting abilities and belonged to the genera Pantoea, Pseudomonas, Bacillus, and Ancylobacter. Besides, there are isolates belonging to the genus Streptomyces, Bacillus, Peribacillus, Variovorax, Xenophilus, Brevundimonas, and Priestia, which exhibit at least one of the plant growth-promoting activities. This initial screen provided a list of potential PGPR to test for plant health improvement on model and crop plants. Most of the bacterial isolates in this study have a great potential to become biofertilizers and bio-stimulants.

Eco-friendly approach to improve traits of winter wheat by combining cold plasma treatments and carbonization of subtropical biomass waste

This study aims to improve the quality and quantity of winter wheat by using the potential of combining the use of cold plasma and waste biorefinery products for improving wheat yield. Plasma was applied by a radio frequency (RF) plasma reactor operated with air for 180 s and 50 W. The waste biorefinery products, including pyroligneous acid, biochar, and azolla compost, were used as plant nutrition. The effects of cold plasma treatment and waste biorefinery products were determined by measuring plant photosynthesis, grain yield, and content of chlorophyll, carotenoids, anthocyanin, protein, and starch. The experiment was conducted during the cropping seasons 2016-18 in a randomized complete block design with four replications. The combination of cold plasma and pyroligneous acid increased the grain yield up to 40.0%. The photosynthesis rate was improved up to 39.3%, and total chlorophyll content up to 48.3% in both years. Seed plasma treatment combined with biochar application increased the starch content by 36.8%. Adding azolla compost increased the protein content by 35.4%. Using seed plasma treatment with biochar increased the microbial biomass carbon by 16.0%. The application of plasma and azolla compost increased the microbial biomass nitrogen by 29.0%.

A Community-Based Approach to Integrating Socio, Cultural and Environmental Contexts in the Development of a Food Database for Indigenous and Rural Populations: The Case of the Batwa and Bakiga in South-Western Uganda

Comprehensive food lists and databases are a critical input for programs aiming to alleviate undernutrition. However, standard methods for developing them may produce databases that are irrelevant for marginalised groups where nutritional needs are highest. Our study provides a method for identifying critical contextual information required to build relevant food lists for Indigenous populations. For our study, we used mixed-methods study design with a community-based approach. Between July and October 2019, we interviewed 74 participants among Batwa and Bakiga communities in south-western Uganda. We conducted focus groups discussions (FGDs), individual dietary surveys and markets and shops assessment. Locally validated information on foods consumed among Indigenous populations can provide results that differ from foods listed in the national food composition tables; in fact, the construction of food lists is influenced by multiple factors such as food culture and meaning of food, environmental changes, dietary transition, and social context. Without using a community-based approach to understanding socio-environmental contexts, we would have missed 33 commonly consumed recipes and foods, and we would not have known the variety of ingredients’ quantity in each recipe, and traditional foraged foods. The food culture, food systems and nutrition of Indigenous and vulnerable communities are unique, and need to be considered when developing food lists.

A Rapid Review of Territorialized Food Systems and Their Impacts on Human Health, Food Security, and the Environment

The global food system is facing multiple problems, including rising food insecurity, degrading environments, and an increased incidence of diet-related chronic diseases. International organizations are thus calling for a transition toward territorialized food systems to alleviate some of these challenges. Yet, limited evidence supporting the benefits of territorialized food systems is available. Our objective was to summarize the current body of literature on territorialized food systems and their impacts on human health, food security, and the environment using a rapid review methodology. Articles were retrieved from three databases and analyzed using keywords and inclusion criteria corresponding to territorialized food systems, environment, human health, and food security. Six relevant publications were identified. While this limited evidence suggests that territorialized food systems may have positive effects on all three dimensions, data are not consistent across publications. For example, territorialized food systems may contribute to improved diet quality, provide agroecosystem services, and contribute to food security. However, food produced within these food systems may have a higher carbon footprint and be less available than industrially produced food. This rapid review also highlights the siloed nature of the current research on territorialized food systems and emphasizes the need for more holistic and interdisciplinary research.

Projections of disability-adjusted life years for major diseases due to a change in vegetable intake in 2017-2040 in Japan

Background

Low vegetable intake is one of the key dietary risk factors known to be associated with a range of health problems, including cardiovascular diseases (CVDs), cancer, and diabetes and kidney diseases (DKDs). Using data from Japan’s National Health and Nutrition Surveys and the Global Burden of Diseases study in 2017, this study aimed to forecast the impact of change in vegetable intake on disability-adjusted life years (DALYs) between 2017 and 2040 for three diseases.

Methods

We generated a three-component model of cause-specific DALYs, including changes in major behavioural and metabolic risk predictors, the socio-demographic index and an autoregressive integrated moving average model to project future DALY rates for 2017–2040 using the data between 1990 and 2016. Data on Vegetable consumption and risk predictors, and DALY rate were obtained from Japan’s National Health and Nutrition Surveys and the Global Burden of Diseases Study in 2017. We also modelled three scenarios of better, moderate and worse cases to evaluate the impact of change in vegetable consumption on the DALY rates for three diseases (CVDs, cancer, and DKDs).

Results

Projected mean vegetable intake in the total population showed a decreasing trend through 2040 to 237.7 g/day. A significant difference between the reference scenario and the better case scenario was observed with un-overlapped 95% prediction intervals of DALY rates in females aged 20–49 years (− 8.0%) for CVDs, the total population for cancer (− 5.6%), and in males (− 8.2%) and females (− 13.7%) for DKDs.

Conclusions

Our analysis indicates that increased vegetable consumption would have a significant reduction in the burdens of CVDs, cancer and DKDs in Japan. By estimating the disease burden attributable to low vegetable intake under different scenarios of future vegetable consumption, our study can inform the design of targeted interventions for public health challenges.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-10772-2.

Machine Learning-Based Microclimate Model for Indoor Air Temperature and Relative Humidity Prediction in a Swine Building

Simple Summary

Indoor air temperature (IAT) and indoor relative humidity (IRH) are the prominent microclimatic variables. Among other livestock animals, pigs are more sensitive to environmental equilibrium; a lack of favorable environment in barns affects the productivity parameters such as voluntary feed intake, feed conversion, heat stress, etc. Machine learning (ML) based prediction models are utilized for solving various nonlinear problems in the current decade. Meanwhile, multiple linear regression (MLR), multilayered perceptron (MLP), random forest regression (RFR), decision tree regression (DTR), and support vector regression (SVR) models were utilized for the prediction. Typically, most of the available IAT and IRH models are limited to feed the animal biological data as the input. Since the biological factors of the internal animals are challenging to acquire, this study used accessible factors such as external environmental data to simulate the models. Three different input datasets named S1 (weather station parameters), S2 (weather station parameters and indoor attributes), and S3 (Highly correlated values) were used to assess the models. From the results, RFR models performed better results in both IAT (R² = 0.9913; RMSE = 0.476; MAE = 0.3535) and IRH (R² = 0.9594; RMSE = 2.429; MAE = 1.47) prediction with S3 input datasets. In addition, it has been proven that selecting the right features from the given input data builds supportive conditions under which the expected results are available.

Abstract

Indoor air temperature (IAT) and indoor relative humidity (IRH) are the prominent microclimatic variables; still, potential contributors that influence the homeostasis of livestock animals reared in closed barns. Further, predicting IAT and IRH encourages farmers to think ahead actively and to prepare the optimum solutions. Therefore, the primary objective of the current literature is to build and investigate extensive performance analysis between popular ML models in practice used for IAT and IRH predictions. Meanwhile, multiple linear regression (MLR), multilayered perceptron (MLP), random forest regression (RFR), decision tree regression (DTR), and support vector regression (SVR) models were utilized for the prediction. This study used accessible factors such as external environmental data to simulate the models. In addition, three different input datasets named S1, S2, and S3 were used to assess the models. From the results, RFR models performed better results in both IAT (R² = 0.9913; RMSE = 0.476; MAE = 0.3535) and IRH (R² = 0.9594; RMSE = 2.429; MAE = 1.47) prediction among other models particularly with S3 input datasets. In addition, it has been proven that selecting the right features from the given input data builds supportive conditions under which the expected results are available. Overall, the current study demonstrates a better model among other models to predict IAT and IRH of a naturally ventilated swine building containing animals with fewer input attributes.

The Climate Change, Food Security and Human Health Nexus in Canada: A Framework to Protect Population Health

Climate change impacts on the Canadian food system pose risks to human health. Little attention has been paid to the climate change, food security, and human health nexus, resulting in a number of knowledge gaps regarding food system components that are most vulnerable to climate change. The lack of understanding of key dynamics and possible future impacts challenges the ability of public health officials and partners in other sectors to prepare Canadians for future health risks. A series of literature reviews were conducted to establish the relationship between climate change, food security, and human health, and to identify vulnerabilities within the Canadian food system. Evidence suggests that key activities within the food system are vulnerable to climate change. The pathways in which climate change impacts travel through the food system and affect the critical dimensions of food security to influence human health outcomes are complex. Climate-related disruptions in the food system can indirectly impact human health by diminishing food security, which is a key determinant of health. Human health may also be directly affected by the physical effects of climate change on the food system, primarily related to the impacts on nutrition and foodborne illnesses. In this study, we propose a novel analytical framework to study and respond to the climate change, food security, and human health nexus. This work is intended to help public health officials, researchers, and relevant stakeholders investigate and understand current and future risks, and inform adaptation efforts to protect the health of Canadians.