Food and water are inextricably linked. With the increase of water consumption in irrigation and food growth, water shortage has become an urgent issue. Irrational cross-regional transfer of water embodied in food exacerbates water scarcity and restrict China's sustainable development. Given that, a Virtual Water-Food Nexus Model is developed to quantify the inter-provincial transfer of water embodied in food and to identify the complicated interactions between different provinces. In detail, Environmental Input-Output Analysis is applied to quantitatively estimate the inter-provincial water transfer embodied in food trades. Based on the network constructed by interrelated nature of nexus, the mutual interactions, control situation, and the dominant and weak pathways are examined through the combination of Ecological Network Analysis and Principal Component Analysis. Two new indictors water consumption intensity and water supply capacity are first performed to measure the role of each province from the supply and consume side respectively. It is revealed that interregional food transactions failed to realize water resources dispatching management. Many water-deficient regions suffered from massive virtual water losses through food exports, but water-rich areas still import large quantities of food containing virtual water. Results show that exploitation and competition dominate the ecological relationships between provinces. Agricultural GDP ratio is the indicator which most affect water consumption intensity and water supply capacity. Network-based research contributes more insights into the recognition of water management responsibilities across provinces and municipalities. These findings will provide a scientific support to adjust unreasonable allocation of water resources in China in an attempt to addressing the contradiction between food demand and water shortages.

Water security is a crucial element in the realm of agricultural development, significantly impacting the welfare of farmers and stakeholders throughout the agricultural supply chain. However, the connection between agricultural water security and food security has been relatively understudied. This research seeks to fill this gap by examining the influence of agricultural water security on the food security of smallholder farm households in Ghana. Using principal component analysis, the study classified farmers into two groups: those considered agriculturally water-secure (48.56%) and those agriculturally water-insecure (51.44%), with a threshold set at the 40th percentile. Employing an endogenous treatmenteffect ordered probit model, the research delved into the impact of water security on household food security among smallholder farmers. The analysis revealed several critical factors influencing agricultural water security, including gender, land ownership, non-farm income, access to extension services, credit availability, membership in farmer-based organizations (FBOs), adoption of irrigation, and information sources like NGOs and the Ministry of Food and Agriculture (MoFA). These factors were identified as positively contributing to water security. Conversely, factors such as age, total livestock count, distance to water sources from the farm, and information obtained from fellow farmers hurt agricultural security. Concerning the effect of agricultural water security on food security, the study found that farmers achieving water security witnessed a significant 23% improvement in their food security status. This translated to reductions in mild food insecurity (by 0.8%), moderate food insecurity (by 6.1%), and severe food insecurity (by 17.8%). These findings underscore the importance of government and development partners' support for enhancing agricultural water security among smallholder farmers to improve overall food security.

To investigate biomarkers representing the physiological and biochemical responses of the brackish-water clam Corbicula japonica, we conducted a full factorial-design experiment to test different water-temperature levels (20 °C and 25 °C), salinity levels (5 and 20 psu), and food-availability levels (0.5 and 2.0 mg suspended solids (SS)·ind⁻¹·d⁻¹). Increase in water temperature significantly decreased superoxide dismutase (SOD) and catalase (CAT) activities and oxyradical-absorbance capacity (ORAC), leading to lipid peroxidation (i.e., oxidative damage). Salinity activated or inhibited these biochemical markers. Food availability supported a detoxification mechanism against oxidative stress. Principal-components and cluster analyses revealed that a total of eight experimental conditions fell into three groups related to water temperature and/or salinity. The shift from Group I (20 °C water temperature) to Group II (25 °C water temperature and 5-psu salinity) demonstrated that the condition index, SOD, CAT, and ORAC had significantly decreased. With the further shift to Group III (25 °C water temperature and 20-psu salinity), we found a prominent increase in ORAC, which led to oxidative damage but no mortality. We conclude that future habitat changes driven by global warming should be closely watched, particularly given that local anthropogenic disturbances further add to natural ones.

Microorganism assessment plays a key role in food quality and safety control but conventional techniques are costly and/or time consuming. Alternatively, electronic tongues (E-tongues) can fulfill this critical task. Thus, a potentiometric lab-made E-tongue (40 lipid sensor membranes) was used to differentiate four common food contamination bacteria, including two Gram positive (<i>Enterococcus faecalis</i>, <i>Staphylococcus aureus</i>) and two Gram negative (<i>Escherichia coli</i>, <i>Pseudomonas aeruginosa</i>). Principal component analysis and a linear discriminant analysis-simulated annealing algorithm (LDA-SA) showed that the potentiometric signal profiles acquired during the analysis of aqueous solutions containing known amounts of each studied bacteria allowed a satisfactory differentiation of the four bacterial strains. An E-tongue-LDA-SA model (12 non-redundant sensors) correctly classified 98 ± 5% of the samples (repeated K-fold-CV), the satisfactory performance of which can be attributed to the capability of the lipid membranes to establish electrostatic interactions/hydrogen bonds with hydroxyl, amine and/or carbonyl groups, which are comprised in the bacteria outer membranes. Furthermore, multiple linear regression models, based on selected subsets of E-tongue sensors (12–15 sensors), also allowed quantifying the bacteria contents in aqueous solutions (0.993 ± 0.011 ≤ <i>R</i>² ≤ 0.998 ± 0.005, for repeated K-fold-CV). In conclusion, the E-tongue could be of great value as a preliminary food quality and safety diagnosis tool.

Understanding the status of water-energy-food (WEF) Nexus, oriented to the whole process of water extraction and deployment, water consumption for crop growth, and food production output, in irrigation systems is essential for food security and resources sustainability. Based on WEF Nexus quantification, combining traditional agricultural water-saving and water footprint theory, the sustainable development level (SDL) of water acquisition-transfer-consumption process for pumped irrigation systems was analyzed, using the principal component analysis (PCA) and taking the Lianshui Irrigation District (LID) in eastern China as a case study, in this paper. The driving mechanism of SDL for WEF Nexus was revealed by virtue of the partial least-squares regression (PLSR). Results showed that, annual SDL of the WEF Nexus in the pumped irrigation systems was 0.3 during the study period 2005–2019, mainly due to the low SDLₑ and SDLf, indicating that sustainability had been concerned. PRE and RRI were significant-positive factors, while CDI functioned as significant-negative driving factors on SDL of WEF Nexus. The measures adjusting crop planting structure, transforming irrigation and drainage mode, updating water pump equipment, and increasing agricultural investment contribute to the sustainability of WEF Nexus in the observed irrigation systems. Therefore, the sustainable management can be implemented according to the unique driving factors identification of WEF Nexus in pumped irrigation systems. The research is conducive to the management and program for irrigated agricultural systems under the changing circumstances.

We have previously shown that diarrheagenic Escherichia coli (DEC) and non-DEC are prevalent in food sources and irrigation water in South Africa. Recent data suggest that an increased relative abundance of faecal Enterobacteriaceae is associated with poorer health outcomes among children in developing countries. Thus, exposure to non-DEC from environmental sources may incur adverse effects, although the mechanisms underlying these effects remain obscure. To further elucidate this phenomenon, we assayed non-DEC strains from environmental sources in South Africa for phenotypes that may be associated with intestinal dysfunction (ID). DEC strains were also used. The strains had previously been isolated from Producer Distributor Bulk Milk (PDBM), irrigated lettuce, street vendor coleslaw and irrigation water.In-vitro assays identified; biofilm formation (n = 38), extracellular polymeric substance (EPS) formation (n = 38), cytotoxic activity (n = 10), disruption of tight junctions and induction of Interleukin 8 (IL-8) on polarized T-84 cells (n = 20). The number of strains tested for each assay differed, depending on prior molecular and phenotypic characterization that signalled potential pathogenicity in-vitro. Subsequently, all strains having data points for all analyses were used to compute Principal Component Analysis (PCA) plot curves to infer potential associations amongst test strains and a standard DEC pathogenic strain (042).Biofilm formation on glass coverslips after strains were grown in nutrient-rich media (LB and DMEM-F12 + 0.5% D-Mannose) at 37 °C varied based on pathotype (DEC and non-DEC) and source of isolation (food, irrigation water, clinical) suggesting that pathotype and source isolation influence persistence within a defined environmental niche. Additionally, DEC isolated from irrigated lettuce had a significantly higher (p ≤ 0.05) propensity for biofilm formation in both media compared to all strains including DEC standard controls. This suggested the propensity for irrigated lettuce as a potential source of persistent pathogenic strains. Furthermore, all strains were able to form EPS suggesting the ability to form mature biofilms under conditions relevant for food processing (20–25 °C). Of the (60%, 6 out of 10) strains that showed cytotoxic activity, most (83%, 5 out of 6 strains) were non-DEC isolated from food sources many of which are consumed with minimal processing.Mean percentage reduction in initial TEER (a measure of intestinal disruption), did not significantly differ (p = 0.05) in all test strains from that observed in the standard DEC. Additionally, IL-8 induction from strains isolated from PDBM (139 pg/mL), irrigation water (231.93 pg/mL) and irrigated lettuce (152.98 pg/mL) was significantly higher (p ≤ 0.05) than in the commensal strain aafa. PCA categorized strains based on sources of isolation showed potential for use in source tracking especially when comparing many strains from various environmental sources. We show that non-DEC strains along the food chain possess characteristics that may lead to ID. Further investigations using a larger collection of strains may provide a clearer link to these reported observations that could be associated with the high diarrheal disease burden within the country, especially among infants.

Unsustainable use of water resources and environmental degradation as related to global food production systems are critical issues of concern. However, reducing food wastage along the supply chain can provide the needed solutions to resources and environmental conservations, while meeting food demand. This study quantified the wastage of common food types at each stage along the supply chain in Korea using top-down mass flow analysis for the period of 2007–2017. The principal component analysis (PCA) was used to rank the food types based on their contribution to the total wastage. The water resources and GHG emissions associated with food wastage were assessed using the production footprint concept, after which prediction models were developed. The estimated food wastage was 14.97 ± 1.2 million tonnes, with production, postharvest, processing, distribution, and consumption representing 14%, 11%, 13%, 15%, and 46%, respectively. Vegetables, maize, and rice were ranked as the highest food types contributing to the total wastage, while mutton and rapeseed were the least. Our results indicated 15.24 ± 1.95 billion m³ and 20.08 ± 6.14 megatonnes CO₂eq of water footprint and GHG emissions associated with food wastage, respectively, with substantial variations among the 28 major food commodity types. The prediction models using Bradley-Terry fitted well for the trend analysis of water footprint and GHG emission associated with food wastage. The prediction suggested that the total food supply, total wastage, water footprint, and GHG emission were estimated to reach 54.89 million tonnes, 16.91 million tonnes, 18.63 billion m³, and 27.41 megatonnes CO₂eq by 2030, respectively. This study is of utmost importance considering the strong desire of the Korean government to pursue food self-sufficiency in the face of constraint water resources and GHG emission reduction target.