Plant Site Research Articles

Prediction of Plant Ubiquitylation Proteins and Sites by Fusing Multiple Features

Introduction: Protein ubiquitylation is an important post-translational modification (PTM), which is considered to be one of the most important processes regulating cell function and various diseases. Therefore, accurate prediction of ubiquitylation proteins and their PTM sites is of great significance for the study of basic biological processes and the development of related drugs. Researchers have developed some large-scale computational methods to predict ubiquitylation sites, but there is still much room for improvement. Much of the research related to ubiquitylation is cross-species while the life pattern is diversified, and the prediction method always shows its specificity in practical application. This study just aims at the issue of plants and has constructed computational methods for identifying ubiquitylation protein and ubiquitylation sites. Method: In this work, we constructed two predictive models to identify plant ubiquitylation proteins and sites. First, in the ubiquitylation proteins prediction model, in order to better reflect protein sequence information and obtain better prediction results, the KNN scoring matrix model based on functional domain Gene Ontology (GO) annotation and word embedding model, i.e. Skip-Gram and Continuous Bag of Words (CBOW), are used to extract the features, and the light gradient boosting machine (LGBM) is selected as the ubiquitylation proteins prediction engine. Results: As a result, accuracy (ACC), Precision, recall rate (Recall), F1_score and AUC are respectively 85.12%, 80.96%, 72.80%, 76.37% and 0.9193 in the 10-fold cross-validations on independent dataset. In the ubiquitylation sites prediction model, Skip-Gram, CBOW and enhanced amino acid composition (EAAC) feature extraction codes were used to extract protein sequence fragment features, and the predicted results on training and independent test data have also achieved good performance. Conclusion: In a word, the comparison results demonstrate that our models have a decided advantage in predicting ubiquitylation proteins and sites, and it may provide useful insights for studying the mechanisms and modulation of ubiquitination pathways

Land-based wind plant wake characterization using dual-Doppler radar measurements at AWAKEN

Wind plant wakes have been shown to persist for tens of kilometers downstream in offshore environments, reducing the power output of neighboring plants, but their behavior on land remains relatively unexplored through observation. This study capitalizes on the unique and extensive field data collected for the American WAKE ExperimeNt (AWAKEN) project underway in northern Oklahoma. X-band dual-Doppler radars deployed at this site measure wind speed and direction at 25-m and 2-min resolution within a 30-km range, capturing the interactions between three neighboring wind plants. These measurements show that the wake of one wind plant extends at least 15 km downstream under easterly wind and stable atmospheric conditions. Though the wake wind speed increases within the first 10 km, it plateaus at 90% of the freestream wind speed. The spanwise velocity distribution within the wake initially shows the clear signature of the wind plant layout, which is smoothed as it propagates downstream, indicating spanwise momentum transfer is a key mechanism in wind plant wake development and recovery. These findings have important implications for wind plant siting decisions and resource assessments, and provide insights into atmospheric interactions at the wind plant scale.

Productivity Of Palm Oil (Elaeis guineensis Jacq) (Elaeis guineensis Jacq) In The Highlands In Simalungun District With Percentage Levels Of Bunch Rot Based On Planting Year

The study was conducted to evaluate the percentage rate of bunch rot by planting year and the productivity of oil palm in the highlands. The research was conducted on the plant area yielded by survey method at Kebun Bah Birung Ulu Sidamanik Subdistrict Simalungun Regency. The study was conducted in August 2014 with a height of 648 - 1087 meters above sea level located on Longitude: 2o 52 '08.70' 'N - 99o 00' 14.96'' T and Latitude: 2o 46 '12.59' 'U-98o 56 ' 03.63 '' Q. This research was conducted by collecting data such as An Overview of Biru Ulu Garden of PTPN. IV, the production of fresh fruit bunches per block per year of planting: Actual production (tons/ha) for the 1996, 2004, 2005 and 2006 cropping periods and the number of staples per five years was also used in the determination of palm oil grade and attack percentage data bunch rot) and fruit parthenocarpy in Garden Bah Birung Ulu, PT Perkebunan Nusantara IV, Sidamanik Subdistrict, Simalungun Regency, North Sumatra Province. Research Results Show Oil palms at 4 - 9 years old are still attacked by rotting fruit, but the percentage of attacks tends to decrease with the age of oil palm plantations. The percentage of fruits shipped to the palm oil mill at 4 - 5 year olds is very low and tends to increase fruit rot and parthenocarpi attacks with increasing altitude of the plant site. bunch diseases commonly caused by Marasmius palmivorus also affect the low productivity of plants in the highlands

Antioxidant and LC-MS screening of banana pseudostem.

Abstract Bananas are herbaceous plants in the Musaceae family, which includes three genera: Musa, Musella, and Ensete. Musa acuminata and M. balbisiana are the main species that produce edible bananas. The peels and leaves of the banana tree include antioxidants and biological activities such as anti-diabetic, anti-diarrheal, anti-tumor, anti-mutagenic, and anti-ulcerogenic properties. Bananas have also been shown to have bioactive compounds that inhibit the growth of bacteria and fungus. The wide waxy surface of the banana pseudo-stem contains a lot of fibre, flavonoids, polyphenols, and tannins. Because of their cooling characteristics, the leaves have long been used to treat eczema, wounds, inflammation, rashes, dandruff, and sunstroke. The pseudo-stem comprises a significant portion of the plant biomass, which is often left on the plantation site or burned and discarded. Banana (Musa spp.) pseudostem, a byproduct of banana farming, has long been used in numerous cultures for its alleged health benefits. The purpose of this study was to investigate the potential of banana pseudostem as a potent source of phytochemicals or secondary metabolites using biochemical tests and chromatography techniques. Fresh pseudostem samples were obtained and subjected to biochemical testing such as flavonoid, phenol, antioxidant, and antibacterial activity. The results demonstrated presence of potential phytochemicals in its aqueous and methanolic extracts, indicating a rich biochemical composition. Furthermore, thin layer chromatography (TLC) and liquid chromatography - mass spectroscopy (LC-MS) were used to identify different phytochemical compounds present in the extract. The analysis revealed unique separation patterns, indicating a wide range of secondary metabolites within pseudostem extract. This extensive investigation highlights banana pseudostem's potential as a great source of phytochemicals viz. with a variety of biological functions. Further detailed investigations may reveal the potential of banana pseudostem, an agricultural waste, as a rich source of many bioactive compounds.

Risk perception in long-term evacuees of Futaba town, Fukushima: a cross-sectional study reveals greater concerns outside the prefecture, 12years after the accident.

For over 12years since the 2011 East Japan Earthquake, the decontamination of radioactive materials is still incomplete. Although evacuation orders had been lifted in ~15% of Futaba town, the site of the Fukushima Daiichi Nuclear Power Plant, by August 2022, anxiety regarding the effects of nuclear radiation persists among evacuees, and their intention to return (ITR) remains low. As of August 2023, only 90 residents lived there. As the only town with government functions relocated outside Fukushima Prefecture, Futaba has more residents who evacuated outside the prefecture. Although numerous factors affect risk perception and ITR to the place of previous residence, the impact of evacuation destination on risk perception remains unknown. Therefore, this study aimed to evaluate the impact of evacuation destination on radiation risk perception. In 2022, a survey was conducted on 404 evacuees aged >18years. The responses were compared between groups outside and inside Fukushima using the chi-square test and multivariate logistic regression analysis. Significant relationships were found between the evacuation destination and risk perception of genetic effects in the next generation (odds ratio [OR] = 1.92, 95% confidence interval [CI]: 1.15-3.20) and of the health effects of radiation (OR = 1.76, 95%CI: 1.10-2.84), which were both higher in those who had evacuated outside Fukushima. These findings stress the importance of evacuation destination choice and information access for evacuees' risk perception. Enhanced education and support efforts are necessary to help evacuees not only in Fukushima but also throughout Japan.

Radiometric Infrared Thermography of Solar Photovoltaic Systems: An Explainable Predictive Maintenance Approach for Remote Aerial Diagnostic Monitoring

Solar photovoltaic (SPV) arrays are crucial components of clean and sustainable energy infrastructure. However, SPV panels are susceptible to thermal degradation defects that can impact their performance, thereby necessitating timely and accurate fault detection to maintain optimal energy generation. The considered case study focuses on an intelligent fault detection and diagnosis (IFDD) system for the analysis of radiometric infrared thermography (IRT) of SPV arrays in a predictive maintenance setting, enabling remote inspection and diagnostic monitoring of the SPV power plant sites. The proposed IFDD system employs a custom-developed deep learning approach which relies on convolutional neural networks for effective multiclass classification of defect types. The diagnosis of SPV panels is a challenging task for issues such as IRT data scarcity, defect-patterns’ complexity, and low thermal image acquisition quality due to noise and calibration issues. Hence, this research carefully prepares a customized high-quality but severely imbalanced six-class thermographic radiometric dataset of SPV panels. With respect to previous approaches, numerical temperature values in floating-point are used to train and validate the predictive models. The trained models display high accuracy for efficient thermal anomaly diagnosis. Finally, to create a trust in the IFDD system, the process underlying the classification model is investigated with perceptive explainability, for portraying the most discriminant image features, and mathematical-structure-based interpretability, to achieve multiclass feature clustering.

Dissecting the role of soybean rhizosphere-enriched bacterial taxa in modulating nitrogen-cycling functions

Crop roots selectively recruit certain microbial taxa that are essential for supporting their growth. Within the recruited microbes, some taxa are consistently enriched in the rhizosphere across various locations and crop genotypes, while others are unique to specific planting sites or genotypes. Whether these differentially enriched taxa are different in community composition and how they interact with nutrient cycling need further investigation. Here, we sampled bulk soil and the rhizosphere soil of five soybean varieties grown in Shijiazhuang and Xuzhou, categorized the rhizosphere-enriched microbes into shared, site-specific, and variety-specific taxa, and analyzed their correlation with the diazotrophic communities and microbial genes involved in nitrogen (N) cycling. The shared taxa were dominated by Actinobacteria and Thaumarchaeota, the site-specific taxa were dominated by Actinobacteria in Shijiazhuang and by Nitrospirae in Xuzhou, while the variety-specific taxa were more evenly distributed in several phyla and contained many rare operational taxonomic units (OTUs). The rhizosphere-enriched taxa correlated with most diazotroph orders negatively but with eight orders including Rhizobiales positively. Each group within the shared, site-specific, and variety-specific taxa negatively correlated with bacterial amoA and narG in Shijiazhuang and positively correlated with archaeal amoA in Xuzhou. These results revealed that the shared, site-specific, and variety-specific taxa are distinct in community compositions but similar in associations with rhizosphere N-cycling functions. They exhibited potential in regulating the soybean roots’ selection for high-efficiency diazotrophs and the ammonia-oxidizing and denitrification processes. This study provides new insights into soybean rhizosphere-enriched microbes and their association with N cycling.Key points• Soybean rhizosphere affected diazotroph community and enriched nifH, amoA, and nosZ.• Shared and site- and variety-specific taxa were dominated by different phyla.• Rhizosphere-enriched taxa were similarly associated with N-cycle functions.

QUANTUM-ENHANCED SOLAR SITE SELECTION: A NOVEL MCDM APPROACH

In the pursuit of optimizing renewable energy sources, the selection of solar plant installation sites presents a complex decision-making challenge that involves multiple criteria. This research introduces a groundbreaking algorithm, leveraging quantum computing techniques to enhance Multi-Criteria Decision Making (MCDM) for solar plant site selection. The proposed algorithm harnesses the superposition and entanglement properties of quantum bits to evaluate extensive datasets and criteria with unprecedented speed and accuracy. By integrating quantum versions of established MCDM methods such as the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), the algorithm provides a sophisticated tool for decision-makers. The research demonstrates the algorithm’s superiority over classical methods through rigorous simulation and validation processes. The findings suggest that quantum-enhanced MCDM can significantly streamline the solar plant site selection, paving the way for a more efficient deployment of solar energy infrastructure and contributing to a sustainable energy future.

Remaining Life Assessment of Kotabaru 2x7 MW Coal Fired Power Plant Circulating Water A252 Gr 2 Intake Pipe by Inspection Method

Kotabaru power plant is a power plant that was built in 2010 and currently the construction work is pending. The construction work stopped in 2014 and based on Kotabaru power plant construction final quantity report, Kotabaru construction work progress is 79,61% up to now. Kotabaru power plant uses open cooling system and takes seawater as cooling water resources. The seawater distribute through intake pipeline which use A252 grade 2 material 600 mm and 800 mm diameter pipeline with 3PL coating and rubber lining inside the pipe. The pipeline distribute the water in 3.184.739 kg/hr flow rate and 5 kg/cm2 G pressure. These pipeline material was on site in 2013 and it was not constructed yet. In 2022 Kotabaru power plant is planned to continue the construction work progress. It was about 9 years of pipeline material on Kotabaru power plant site and these pipeline is exposed to the environment such as sunlight, temperature, oxygen, water, and contaminants and cause a primer failure, especially ultraviolet light (UV) from the sunlight is the main damaging factor. Ultraviolet light from sunlight is high enough to break the coating of pipeline. Inspection and assess the pipeline can help the management to figure out pipeline actual condition. More effective inspections can reduce the risk level by reducing the frequency of future failures, through corrective and preventive action. In general, the purpose of this method is classify all risk level equipment, calculate the risk value of all equipment and it can help to make a decision to the next construction period. The service lifetime of pipeline prediction can be determined by actual pipe condition by use corrosion test and actual thickness dimension of the pipeline. This method will inform the life time prediction of the pipeline that should be meet the 15 years life time required and also inform the risk matrix value of all pipeline equipment on the site.

A CFD study on radionuclides diffusion and dose assessment in Daya Bay nuclear power plant

Computational fluid dynamics (CFD) is used to simulate the short-range dispersion of radionuclides in a real nuclear power plant site. Firstly, the results of the validation case showed that the wind speed and concentration distribution were consistent with the measured data. Then, the potential consequences of radionuclide diffusion within the Daya Bay Nuclear Power Plant (DBNPP) were evaluated. Based on the wind direction and speed data from DBNNP over a 30-year period, the prevailing wind is northeasterly and southwesterly. The simulation results show that northeasterly and southwesterly winds dominate the diffusion direction of radionuclides, which mainly accumulate near nuclear reactor containment vessels. However, radionuclides cover most areas of DBNPP under a tailwind condition, causing severe contamination. Finally, it is necessary to pay attention to the accumulation of I-131 and Cs-137, and corresponding actions should be taken for regions of different radiation doses.

Container and transport technology for harvesting, storing and selling selected potatoes of the first field reproduction

The article discusses the issues of moving, loading, transshipment and storage of loaded and empty containers on the field-warehouse line. The work was carried out at the Redkinskaya AIC LLC enterprise, which has 625 hectares of arable land for growing seed potatoes with appropriate crop rotation and producing up to 10 000 tons of elite seeds. The technology for harvesting potatoes using soft containers (bags) and containers is described. The required number of containers for harvesting was calculated, depending on the gross harvest of potatoes in fields of different areas and the time of all operations of the technological process. Suitable overall dimensions of containers and materials for their manufacture have been determined. Transport for moving and loading and unloading operations using both types of containers is indicated. A comparative assessment of the bags and containers usage is provided, and prospects for the development of the latter in various agricultural operations are outlined. The processes of sorting, warehousing, storing and planting potatoes using containers are presented. A diagram of tubers delivery to the planting site and the planting process is shown. A container-transport technology for harvesting selection potatoes of the first field reproduction has been developed.

Improved Design and Economic Estimation of Cold-End Systems for Inland Nuclear Power Plants

Improved Design and Economic Estimation of Cold-End Systems for Inland Nuclear Power Plants

Nursery cultural practices influence morphological and physiological aspen seedling traits: implications for post-fire restoration

Aspen forests are threatened by the impacts of a changing climate and are showing large-scale mortality with meager natural regeneration to restore these loses. Therefore, there is an increasing demand for high-quality aspen seedlings to assist with forest restoration efforts. Nursery cultural practices can be used to alter aspen seedling traits to improve adaptability to dry planting conditions. In this study, the effects of container size (SC10 and D30; 158 and 490 mL, respectively) and nursery irrigation treatment (high and low irrigation; 90% and 70% container capacity, respectively) on seedling growth and a suite of morphological and physiological traits were investigated. The combination of large container size and low irrigation treatment resulted in seedlings with lowest height-to-diameter ratio and specific leaf area, which are desired traits for seedling performance on dry sites. Additionally, seedlings exposed to low irrigation conditions at the nursery stage had a lower (more negative) osmotic potential at full turgor, suggesting a higher likelihood of drought tolerance. Overall results from this study provide insight into utilizing nursery cultural practices to produce seedlings with target characteristics that may ultimately lead to establishment on harsh, dry planting sites in large-scale reforestation projects.

Wood Quality of Young Tectona grandis L. f. Trees and Its Relationship with Genetic Material and Planting Site in Mato Grosso, Brazil

Tectona grandis L. f. (teak) is highly valued in the international market, but its volume and properties vary depending on its genetic material and planting site. Evaluating these factors is crucial for promoting new plantations. Therefore, this study aimed to assess the impact of genetic material (clones TG1 and TG3 and seminal material) and planting site (Nova Maringá and Água Boa, Mato Grosso, Brazil) on morphological parameters (heartwood, sapwood, bark, pith proportions, and pith eccentricity), physical properties (shrinkage and air-dry density), and mechanical properties (static bending strength—fm, compressive strength—fc0, Janka hardness—fH90, and shear strength—fv0). For this purpose, we sampled five trees aged 13 years per genetic material from commercial plantations. In Nova Maringá, trees exhibited, on average, 56.07% heartwood, while in Água Boa, this value was less than 50%. Seminal material showed the lowest percentage of heartwood (49.2%). The pith percentage was significantly greater in Água Boa than in Nova Maringá, regardless of the genetic material. We observed the highest standard deviation (5.61) in pith eccentricity for the seminal material. Both the planting site and genetic material influenced the air-dry density (~12% moisture content), which ranged from 0.535 to 0.618 g·cm−3. Trees grown in Nova Maringá produced wood with higher dimensional stability than those from Água Boa, exhibiting a 14% lower radial shrinkage and a 6% lower volumetric variation. In Nova Maringá, the wood from the seminal material exhibited greater resistance. On the other hand, in Água Boa, that material showed lower resistance (fv0, fm, and fc0), or there was no significant difference (fH90) compared to the clonal materials. When comparing the clonal materials (TG1 and TG3) at each planting site, they demonstrated similar mechanical properties. The variability in physical and mechanical properties among different genetic materials and planting locations highlights the need to select appropriate teak genetic materials for each region. We concluded that more productive teak clones can be selected without compromising the physical and mechanical properties of the wood.

A GIS-based catastrophe approach for optimal site selection for installation of solar power plants, East Azerbaijan province case study, Iran.

Due to depletion of fossil fuels and environmental issues, renewable energy consumption is increasingly growing. Solar energy as the most abundant renewable energy source available is becoming more popular around the world. In the current study, the optimal sites for solar photovoltaic power plants in East Azerbaijan province, Northwest Iran, were investigated. A total of 17 variables were categorized into four groups: climatic, geomorphological, environmental, and access-economic. In order to integrate the variables, a model based on catastrophe theory in the context of GIS was applied. The relative importance and weight of the criteria are computed based on the internal mechanism of the catastrophic system, thus greatly reducing subjectivism and uncertainties of the decision-making process. Five optimal sites located in the western part of the province within the counties of Malekan, Bonab, Ajabshir, Shabestar, and Tabriz were identified as suitable sites for the construction of solar photovoltaic power plants, where there are ideal conditions in terms of many environmental-human variables such as high potential of solar energy, high sunshine hours, low relative humidity, suitable slope, poor vegetation, distance to protected areas, proximity to the population centers, excellent access to the roads and to the main power lines.

Pine needle gasification-based electricity production: Understanding the effect of supply chain.

Pine needles (pine tree leaves), found abundantly across continents such as North America, Asia, Europe, South America, Africa, and parts of the Southern Hemisphere, are a significant global concern due to their high susceptibility to catching fire, especially in dry and hot climates. The same issue persists in the Uttarakhand state of India, which boasts ample pine forests, yielding a substantial 1.67 × 109kg of pine needles annually. In the present study, the annual potential emissions from forest fires in Uttarakhand were estimated to be 58.37 × 109kg of CO2 equivalent. Therefore, the present research aims to unlock pine needles' potential via gasification for green electricity and biochar production, offering an alternative to coal-based plants while reducing forest fire frequencies. Nevertheless, obstacles hindering pine needle gasification include an unsteady supply chain, limited collection windows (100days), and plant expenses, including transportation and operational costs. The primary focus of the research is to design and assess the performance of a gasification-based supply chain for pine needles in the Almora District of Uttarakhand. Ten plant capacity scenarios were considered, ranging from 25 to 250kW. The study incorporated critical factors, encompassing diverse losses within the supply chain, selecting potential plant sites, minimizing transportation distance, and evaluating the supply chain's economic and environmental performance. The economic analysis revealed that the 250-kW plant scenario exhibited a minimum discounted payback period (DPP) of 3.93years, alongside an internal rate of return (IRR) of 19% and a net present value (NPV) of 653.32 million INR without government subsidies. With subsidies included, the DPP decreased to 1.30years, improving the IRR to 69% with an NPV of 916.17 million INR. The emission analysis indicated that gasification plant capacity scenarios could potentially reduce 44.63 × 106 to 46.16 × 106kg of CO2 equivalent emissions annually compared to grid electricity while meeting nearly 5.5% of the electricity demand of Almora district. The present study aligns with SDG-7 (Affordable and Clean Energy), SDG-13 (Climate Action), SDG-9 (Industry, Innovation, and Infrastructure), SDG-11 (Sustainable Cities and Communities), SDG-3 (Good Health and Well-being), and SDG-15 (Life on Land).

Early Age Assessment of a New Course of Irish Fly Ash as a Cement Replacement

This paper explores the potential of a new source of fly ash, deposited on the site of a coal-fired power plant in Ireland dating from 1985 to 1995, as a cement replacement material. A series of X-ray diffraction (XRD) analyses on binder samples with cement replacement levels of 0, 10, 25 and 35% was undertaken to determine the fly ash’s mineralogical composition and to determine its suitability as a supplemental cementitious material (SCM). The XRD results reveal a unique mineral composition with promising characteristics for enhancing the strength and durability of concrete. The experimental results were used to calibrate a thermodynamic model to predict changing phase assemblage and hydration behaviour over time and per replacement level. Thermodynamic models have been shown to give credible predictions of the long-term performance of cements, including SCMs. The initial experimental results’ thermodynamic modelling demonstrates the feasibility of this fly ash source as a sustainable alternative to traditional cement, paving the way for more eco-friendly construction. Ash deposits dating from 1995 to 2005 and from 2005 to the present will be presented in subsequent publications.

Self-Adaptive Incremental PCA-Based DBSCAN of Acoustic Features for Anomalous Sound Detection

In modern industry, maintaining continuous machine operations is important for improving production efficiency and reducing costs. Therefore, the smart technology of acoustic monitoring to detect anomalous machine conditions earlier before breakdowns works as part of predictive maintenance and is applied not only in industry fault detection but also in safety monitoring and surveillance systems. This paper proposes a self-adaptive unsupervised machine learning algorithm with dimension-reduction technology to detect anomalous sounds after extracting acoustic machine features. Technically, the automatic EPS calculation algorithm-based genetic algorithm optimizes the automatic clustering algorithm’s configuration for incremental principal component analysis and density-based spatial clustering algorithms with noise. IPCA is enhanced by the sequential Karhunen–Loeve (SKL) algorithm, and the condensation algorithm works as the second layer of the algorithm to reduce the number of effective components. This architecture could select an optimized set of parameters based on different test environments and keeps performance quality with fewer computational requirements. In the experiments, 228 sets of normal sounds and 100 sets of anomaly sounds are used. The sound files are collected from the same machine type (stepper motors) at a real plant site. We compare the proposed algorithm with K-means++, one-class SVM, agglomerative clustering, DCGAN and DCNN-Autoencoder, and this new algorithm performs best, with an AUC of 0.84 and the shortest execution time. The algorithm is generic and can be applied to detect anomalies in machines to provide early warning to people to avoid serious accidents or disasters.

Integrated metabolomic and metagenomic strategies shed light on interactions among planting environments, rhizosphere microbiota, and metabolites of tobacco in Yunnan, China.

Changes in climatic factors and rhizosphere microbiota led plants to adjust their metabolic strategies for survival under adverse environmental conditions. Changes in plant metabolites can mediate crop growth and development and interact with rhizosphere microbiota of the plant rhizosphere. To understand the interactions among environmental factors, rhizosphere microbiota, and metabolites of tobacco, a study was conducted by using integrated metagenomic and metabolomic strategies at four typical representative tobacco planting sites in Yunnan, China. The results showed that the agronomical and biochemical traits were significantly affected by temperature, precipitation (PREP), soil pH, and altitude. Correlation analyses revealed a significant positive correlation of temperature with length, width, and area of the leaf, while PREP correlated with plant height and effective leaf numbers. Furthermore, total sugar and reducing sugar contents of baked leaves were significantly higher, while the total nitrogen and total alkaloid levels were lower in tobacco leaves at site with low PREP. A total of 770 metabolites were detected with the highest number of different abundant metabolites (DMs) at Chuxiong (CX) with low PREP as compared to the other three sites, in which secondary metabolites were more abundant in both leaves and roots of tobacco. A total of 8,479 species, belonging to 2,094 genera with 420 individual bins (including 13 higher-quality bins) harboring 851,209 CDSs were detected. The phyla levels of microorganisms such as Euryarchaeota, Myxococcota, and Deinococcota were significantly enriched at the CX site, while Pseudomonadota was enriched at the high-temperature site with good PREP. The correlation analyses showed that the metabolic compounds in low-PREP site samples were positively correlated with Diaminobutyricimonas, Nissabacter, Alloactinosynnema, and Catellatospora and negatively correlated with Amniculibacterium, Nordella, Noviherbaspirillum, and Limnobacter, suggesting that the recruitment of Diaminobutyricimonas, Nissabacter, Alloactinosynnema, and Catellatospora in the rhizosphere induces the production and accumulation of secondary metabolites (SMs) (e.g., nitrogen compounds, terpenoids, and phenolics) for increasing drought tolerance with an unknown mechanism. The results of this study may promote the production and application of microbial fertilizers and agents such as Diaminobutyricimonas and Alloactinosynnema to assemble synthetic microbiota community or using their gene resources for better cultivation of tobacco as well as other crops in drought environments.

The Impact of Varying Stages of Maturity on the Chemical Composition and Antioxidant Activity of Yacon (Smallanthus sonchifolius) Leafy Vegetable

Yacon tubers are of global interest due to their prebiotic potential while yacon leaves contain phenolic compounds with potential health benefits. In Kenya, yacon is a newly introduced root crop that is of interest to consumers; however, their main challenge to consumption is determining the appropriate time to harvest the leaves. The chemical makeup of yacon leaves varies depending on the planting site, growing season, harvest time, and growth stages. The current research determined the impact of varying stages of maturity on the chemical composition and antioxidant potential of yacon leaves grown in a farm at Naromoru, Kenya. The leaves were harvested at 2, 3, 4, and 5 months of growth, then subjected to oven drying and stored at 4 °C awaiting analysis. The DPPH assay was used to measure radical scavenging activity, and the Folin–Ciocalteu method was followed in the determination of total phenolic content. Chemical composition was done by Kjedahl method (Crude protein), Soxhlet method (crude fat), and oven drying (moisture content). From the results, the level of maturity significantly (p < 0.05) influenced the levels of crude protein, fat and carbohydrates, TPC, and antioxidant activity in the harvested yacon leaves. The crude protein level was highest (28.45%) for the 2nd month of harvest and was lowest in the 5th month (16.75%), while crude fat increased from 3.51% in the 2nd month to 4.20% in the 5th month. Carbohydrates increased from 46.01% to 56.65% in 2nd month to the 5th month, respectively. Both the TPC and antioxidant activity decreased significantly (p < 0.05) as the leaves matured. TPC was highest in the 2nd month of harvest and lowest in the 5th month of harvest, 439.33 and 81.00 mgGAE/100 g, respectively. Thus, harvesting yacon leaves at the early stages of growth is crucial to fully benefit from the phytochemical and nutritional composition of the leaves.