Molecular and Genetic Characterization of Colicinogenic Escherichia coli Strains Active against Shiga Toxin-Producing Escherichia coli O157:H7.

The objective of this work was to molecularly and genotypically characterize and test the inhibitory activity of six colicinogenic Escherichia coli strains (ColEc) and their partially purified colicins against STEC O157:H7 isolated from clinical human cases. Inhibition tests demonstrated the activity of these strains and their colicins against STEC O157:H7. By PCR it was possible to detect colicins Ia, E7, and B and microcins M, H47, C7, and J25. By genome sequencing of two selected ColEc strains, it was possible to identify additional colicins such as E1 and Ib. No genes coding for stx1 and stx2 were detected after analyzing the genome sequence. The inhibitory activity of ColEc against STEC O157:H7 used as an indicator showed that colicins are potent growth inhibitors of E. coli O157:H7, being a potential alternative to reduce the presence of pathogens of public health relevance.

Characterization of the Key Compounds of Bell Pepper by Spectrophotometry and Gas Chromatography on the Effects of Induced Stress on the Concentration of Secondary Metabolite.

Sweet peppers are consumed worldwide, and traditional uses have sparked interest in their applications as dietary antioxidants, which can be enhanced in plants using elicitors. These are endowed with phytochemicals with potential health benefits such as antioxidants, bioavailability, and bioaccessibility. The trend in metabolomics shows us chemical fingerprints linking metabolomics, innovative analytical form, and bioinformatics tools. The objective was to evaluate the impact of multiple stress interactions, elicitor concentrations, and electrical conductivity on the concentration of secondary metabolites to relate their response to metabolic pathways through the foliar application of a cocktail of said elicitors in pepper crops under greenhouse conditions. The extracts were analyzed by spectrophotometry and gas chromatography, and it was shown that the PCA analysis identified phenolic compounds and low molecular weight metabolites, confirming this as a metabolomic fingerprint in the hierarchical analysis. These compounds were also integrated by simultaneous gene and metabolite simulants to obtain effect information on different metabolic pathways. Showing changes in metabolite levels at T6 (36 mM H2O2 and 3.6 dS/m) and T7 (0.1 mM SA and 3.6 dS/m) but showing statistically significant changes at T5 (3.6 dS/m) and T8 (0.1 mM SA, 36 mM H2O2, and 3.6 dS/m) compared to T1 (32 dS/m) or control. Six pathways changed significantly (p < 0.05) in stress-induced treatments: aminoacyl t-RNA and valine-leucine-isoleucine biosynthesis, and alanine-aspartate-glutamate metabolism, glycoxylate-dicarboxylate cycle, arginine-proline, and citrate. This research provided a complete profile for the characterization of metabolomic fingerprint of bell pepper under multiple stress conditions.

Relationship between Volatile Organic Compounds and Microorganisms Isolated from Raw Sheep Milk Cheeses Determined by Sanger Sequencing and GC-IMS.

Recently, the interest of consumers regarding artisan cheeses worldwide has increased. The ability of different autochthonous and characterized lactic acid bacteria (LAB) to produce aromas and the identification of the volatile organic compounds (VOCs) responsible for flavor in cheeses are important aspects to consider when selecting strains with optimal aromatic properties, resulting in the diversification of cheese products. The objective of this work is to determine the relationship between VOCs and microorganisms isolated (Lacticaseibacillus paracasei, Lactiplantibacillus plantarum, Leuconostoc mesenteroides and Lactococcus lactis subsp. hordniae) from raw sheep milk cheeses (matured and creamy natural) using accuracy and alternative methods. On combining Sanger sequencing for LAB identification with Gas Chromatography coupled to Ion Mobility Spectrometry (GC−IMS) to determinate VOCs, we describe cheeses and differentiate the potential role of each microorganism in their volatilome. The contribution of each LAB can be described according to their different VOC profile. Differences between LAB behavior in each cheese are shown, especially between LAB involved in creamy cheeses. Only L. lactis subsp. hordniae and L. mesenteroides show the same VOC profile in de Man Rogosa and Sharpe (MRS) cultures, but for different cheeses, and show two differences in VOC production in skim milk cultures. The occurrence of Lactococcus lactis subsp. hordniae from cheese is reported for first time.

Pitahaya Peel: A By-Product with Great Phytochemical Potential, Biological Activity, and Functional Application.

Hylocereus spp. present two varieties of commercial interest due to their color, organoleptic characteristics, and nutritional contribution, such as Hylocerous polyrhizus and Selenicerus undatus. The fruit recognized as dragon fruit or Pitahaya is an exotic fruit whose pulp is consumed, while the peel is discarded during the process. Studies indicate that the pulp has vitamin C and betalains, and seeds are rich in essential fatty acids, compounds that can contribute to the prevention of chronic non-communicable diseases (cancer, hypertension, and diabetes). In the present study, polyphenolic compounds, biological activity, and fatty acids present in the peel of the two varieties of pitahaya peel were evaluated, showing as a result that the variety S. undatus had higher antioxidant activity with 51% related to the presence of flavonoids 357 mgRE/g sample and fatty acids (hexadecanoic acid and linoleate) with 0.310 and 0.248 mg AG/g sample, respectively. On the other hand, H. polyrhizuun showed a significant difference in the inhibitory activity of amylase and glucosidase enzymes with 68% and 67%, respectively. We conclude that pitahaya peel has potential health effects and demonstrate that methylated fatty acids could be precursors to betalain formation, as well as showing effects against senescence and as a biological control against insects; in the same way, the peel can be reused as a by-product for the extraction of important enzymes in the pharmaceutical and food industry.

IoT-Based Monitoring System Applied to Aeroponics Greenhouse.

The inclusion of the Internet of Things (IoT) in greenhouses has become a fundamental tool for improving cultivation systems, offering information relevant to the greenhouse manager for decision making in search of optimum yield. This article presents a monitoring system applied to an aeroponic greenhouse based on an IoT architecture that provides user information on the status of the climatic variables and the appearance of the crop in addition to managing the irrigation timing and the frequency of visual inspection using an application developed for Android mobile devices called Aeroponics Monitor. The proposed IoT architecture consists of four layers: a device layer, fog layer, cloud layer and application layer. Once the information about the monitored variables is obtained by the sensors of the device layer, the fog layer processes it and transfers it to the Thingspeak and Firebase servers. In the cloud layer, Thingspeak analyzes the information from the variables monitored in the greenhouse through its IoT analytic tools to generate historical data and visualizations of their behavior, as well as an analysis of the system's operating status. Firebase, on the other hand, is used as a database to store the results of the processing of the images taken in the fog layer for the supervision of the leaves and roots. The results of the analysis of the information of the monitored variables and of the processing of the images are presented in the developed app, with the objective of visualizing the state of the crop and to know the function of the monitoring system in the event of a possible lack of electricity or a service line failure in the fog layer and to avoid the loss of information. With the information about the temperature of the plant leaf and the relative humidity inside the greenhouse, the vapor pressure deficit (VPD) in the cloud layer is calculated; the VPD values are available on the Thingspeak server and in the developed app. Additionally, an analysis of the VPD is presented that demonstrates a water deficiency from the transplanting of the seedling to the cultivation chamber. The IoT architecture presented in this paper represents a potential tool for the study of aeroponic farming systems through IoT-assisted monitoring.

Influence of Food Matrices and the Population of Interfering Microorganisms on the Determination of Listeria monocytogenes by Conventional Methods and VIDAS.

In this study, the possible influence of the food matrix and the interfering population of microorganisms on the detection and count of Listeria monocytogenes in three common foods of the Spanish diet (Spanish omelette, fresh cheese and vegetable salad) was determined. Four groups were assayed: one control, two groups with interfering microorganisms (Salmonella Enteritidis, Staphylococcus aureus and Proteus mirabilis) with different levels of L. monocytogenes and a final group only contaminated with L. monocytogenes. The samples were analyzed with the normalized method (UNE-EN ISO 11290:2018) and with an alternative technique (VIDAS). The results show that the presence of interfering microorganisms did not seem to interfere with the determination of L. monocytogenes. Furthermore, the type of food did not seem to influence the determination of L. monocytogenes, but the culture media used showed differences. In fact, regardless of the type of food, the ALOA medium showed higher sensitivity than the other media, with higher recovery in 100% of samples (only for the Spanish omelette in Group B was the result the same as that for PALCAM, -8.11 log cfu/g). The results obtained using the VIDAS were not influenced by any of the factors or conditions used and show 100% efficiency.

Changes in the Content of Phenolic Compounds and Biological Activity in Traditional Mexican Herbal Infusions with Different Drying Methods.

Mexican spices are used in the supplementation of the human diet and as medicinal herbs for the particularly high amounts of compounds capable of deactivating free radicals. In addition, these spices can have beneficial effects on chronic, no-transmissible diseases such as type II diabetes and hypertension arterial. The objective of this study is to determine the content of phenolic compounds on the antioxidant activity and inhibitory enzymes of α-amylase, α-glucosidase and angiotensin-converting enzyme in melissa, peppermint, thyme and mint, which are subjected to microwave drying, conventional and freeze-drying to be used as alternative treatments. Spices were evaluated to determine total phenols, flavonoids, tannins, 2,2-Diphenyl-1-picrylhydrazyl (DPPH), (2,2'-azino-bis- (3-ethyl benzothiazolin-6-ammonium sulphonate) (ABTS) and Ferric Reducing/Antioxidant Power (FRAP), enzymatic activity. The investigation showed that conventional drying caused a decrease in antioxidant properties and inhibitory activity, in some species, while remained preserved in microwave drying and freeze-drying. The activity of polyphenol oxides and peroxidase decreases with high temperatures and these increase with the use of cold temperatures. This study aims to determine the extent of optimal drying required to preserve phenolic compounds, and the positive effect on antioxidant activity and enzymatic activity in in vitro models, which will produce benefits for the infusion processing industry and the pharmaceutical industry.

Low Computational-Cost Footprint Deformities Diagnosis Sensor through Angles, Dimensions Analysis and Image Processing Techniques.

Manual measurements of foot anthropometry can lead to errors since this task involves the experience of the specialist who performs them, resulting in different subjective measures from the same footprint. Moreover, some of the diagnoses that are given to classify a footprint deformity are based on a qualitative interpretation by the physician; there is no quantitative interpretation of the footprint. The importance of providing a correct and accurate diagnosis lies in the need to ensure that an appropriate treatment is provided for the improvement of the patient without risking his or her health. Therefore, this article presents a smart sensor that integrates the capture of the footprint, a low computational-cost analysis of the image and the interpretation of the results through a quantitative evaluation. The smart sensor implemented required the use of a camera (Logitech C920) connected to a Raspberry Pi 3, where a graphical interface was made for the capture and processing of the image, and it was adapted to a podoscope conventionally used by specialists such as orthopedist, physiotherapists and podiatrists. The footprint diagnosis smart sensor (FPDSS) has proven to be robust to different types of deformity, precise, sensitive and correlated in 0.99 with the measurements from the digitalized image of the ink mat.

Target identification of volatile metabolites to allow the differentiation of lactic acid bacteria by gas chromatography-ion mobility spectrometry.

The purpose of this work was to study the potential of gas chromatography-ion mobility spectrometry (GC-IMS) to differentiate lactic acid bacteria (LAB) through target identification and fingerprints of volatile metabolites. The LAB selected were used as reference strains for their influence in the flavour of cheese. The four strains of LAB can be distinguished by the fingerprints generated by the volatile organic compounds (VOCs) emitted. 2-butanone, 2-pentanone, 2-heptanone and 3-methyl-1-butanol were identified as relevant VOCs for Lactobacillus casei and Lactobacillus paracasei subsp. paracasei. 2-Butanone and 3-methyl-1-butanol were identified in Lactococcus lactis subsp. lactis and Lactococcus cremoris subsp. cremoris. The IMS signals monitoring during a 24-30h period showed the growth of the LAB in vitro. The results demonstrated that GC-IMS is a useful technology for bacteria recognition and also for screening the aromatic potential of new isolates of LAB.

FPGA-based smart sensor for drought stress detection in tomato plants using novel physiological variables and discrete wavelet transform.

Soil drought represents one of the most dangerous stresses for plants. It impacts the yield and quality of crops, and if it remains undetected for a long time, the entire crop could be lost. However, for some plants a certain amount of drought stress improves specific characteristics. In such cases, a device capable of detecting and quantifying the impact of drought stress in plants is desirable. This article focuses on testing if the monitoring of physiological process through a gas exchange methodology provides enough information to detect drought stress conditions in plants. The experiment consists of using a set of smart sensors based on Field Programmable Gate Arrays (FPGAs) to monitor a group of plants under controlled drought conditions. The main objective was to use different digital signal processing techniques such as the Discrete Wavelet Transform (DWT) to explore the response of plant physiological processes to drought. Also, an index-based methodology was utilized to compensate the spatial variation inside the greenhouse. As a result, differences between treatments were determined to be independent of climate variations inside the greenhouse. Finally, after using the DWT as digital filter, results demonstrated that the proposed system is capable to reject high frequency noise and to detect drought conditions.

An analysis of electrical impedance measurements applied for plant N status estimation in lettuce (Lactuca sativa).

Nitrogen plays a key role in crop yields. Hence, farmers may apply excessive N fertilizers to crop fields, inducing environmental pollution. Crop N monitoring methods have been developed to improve N fertilizer management, most of them based on leaf or canopy optical-property measurements. However, sensitivity to environmental interference remains an important drawback. Electrical impedance has been applied to determine the physiological and nutritional status of plant tissue, but no studies related to plant-N contents are reported. The objective of this article is to analyze how the electrical impedance response of plants is affected by their N status. Four sets of lettuce (Lactuca sativa L.) with a different N-source concentrations per set were used. Total nitrogen and electrical impedance spectra (in a 1 to 100 kHz frequency range) were measured five times per set, three times every other day. Minimum phase angles of impedance spectra were detected and analyzed, together with the frequency value in which they occurred, and their magnitude at that frequency. High and positive correlation was observed between plant N content and frequency values at minimum phase angle with no significant variations detected between days of measurement. These results suggest that electrical impedance can be sensitive to plant N status.

A review of methods for sensing the nitrogen status in plants: advantages, disadvantages and recent advances.

Nitrogen (N) plays a key role in the plant life cycle. It is the main plant mineral nutrient needed for chlorophyll production and other plant cell components (proteins, nucleic acids, amino acids). Crop yield is affected by plant N status. Thus, the optimization of nitrogen fertilization has become the object of intense research due to its environmental and economic impact. This article focuses on reviewing current methods and techniques used to determine plant N status. Kjeldahl digestion and Dumas combustion have been used as reference methods for N determination in plants, but they are destructive and time consuming. By using spectroradiometers, reflectometers, imagery from satellite sensors and digital cameras, optical properties have been measured to estimate N in plants, such as crop canopy reflectance, leaf transmittance, chlorophyll and polyphenol fluorescence. High correlation has been found between optical parameters and plant N status, and those techniques are not destructive. However, some drawbacks include chlorophyll saturation, atmospheric and soil interference, and the high cost of instruments. Electrical properties of plant tissue have been used to estimate quality in fruits, and water content in plants, as well as nutrient deficiency, which suggests that they have potential for use in plant N determination.

Instrumentation in developing chlorophyll fluorescence biosensing: a review.

Chlorophyll fluorescence can be defined as the red and far-red light emitted by photosynthetic tissue when it is excited by a light source. This is an important phenomenon which permits investigators to obtain important information about the state of health of a photosynthetic sample. This article reviews the current state of the art knowledge regarding the design of new chlorophyll fluorescence sensing systems, providing appropriate information about processes, instrumentation and electronic devices. These types of systems and applications can be created to determine both comfort conditions and current problems within a given subject. The procedure to measure chlorophyll fluorescence is commonly split into two main parts; the first involves chlorophyll excitation, for which there are passive or active methods. The second part of the procedure is to closely measure the chlorophyll fluorescence response with specialized instrumentation systems. Such systems utilize several methods, each with different characteristics regarding to cost, resolution, ease of processing or portability. These methods for the most part include cameras, photodiodes and satellite images.

Development of a potential functional food prepared with pigeon pea (Cajanus cajan), oats and Lactobacillus reuteri ATCC 55730.

The purpose of this study was to investigate the survival of Lactobacillus reuteri ATCC 55730 in creams, prepared with pigeon peas and oat. Products were analysed to determine their content of protein, fibre, fat, carbohydrates and degree of likeness. Viable numbers of L. reuteri and pH were determined after 1, 7, 14, 21 and 28 days of storage at 4°C. Results showed significant differences (P < 0.05) in protein, fat, fibre and carbohydrate content between creams. No significant differences (P > 0.05) were found on sensory quality between control and creams with L. reuteri. After 28 days, the cell viability was above 7 log cfu/g in all creams. L. reuteri ATCC 55730 had the highest viability in cream with 40% pigeon pea and 20% oat (8.16 log cfu/g). In conclusion, due to its acceptability and highly nutritious value, the product could be used so as to support the growth of L. reuteri.

Smart sensor for real-time quantification of common symptoms present in unhealthy plants.

Plant responses to physiological function disorders are called symptoms and they are caused principally by pathogens and nutritional deficiencies. Plant symptoms are commonly used as indicators of the health and nutrition status of plants. Nowadays, the most popular method to quantify plant symptoms is based on visual estimations, consisting on evaluations that raters give based on their observation of plant symptoms; however, this method is inaccurate and imprecise because of its obvious subjectivity. Computational Vision has been employed in plant symptom quantification because of its accuracy and precision. Nevertheless, the systems developed so far lack in-situ, real-time and multi-symptom analysis. There exist methods to obtain information about the health and nutritional status of plants based on reflectance and chlorophyll fluorescence, but they use expensive equipment and are frequently destructive. Therefore, systems able of quantifying plant symptoms overcoming the aforementioned disadvantages that can serve as indicators of health and nutrition in plants are desirable. This paper reports an FPGA-based smart sensor able to perform non-destructive, real-time and in-situ analysis of leaf images to quantify multiple symptoms presented by diseased and malnourished plants; this system can serve as indicator of the health and nutrition in plants. The effectiveness of the proposed smart-sensor was successfully tested by analyzing diseased and malnourished plants.