Mitigating Greenhouse Gas Emissions from Winter Production of Agricultural Greenhouses

Consuming conventional fossil fuel, such as coal, natural gas, and oil, to heat agricultural greenhouses has contributed to the climate change and air pollutions regionally and globally, so the clean energy sources have been increasingly applied to replace fossil energies in heating agricultural greenhouses, especially in urban area. To assess the environment performance (e.g., greenhouse gas (GHG) emissions) of the ground source heat pump system (GSHPs) for heating agricultural greenhouses in urban area, a GSHPs using the shallow geothermal energy (SGE) in groundwater was applied to heat a Chinese solar greenhouse (G1) and a multispan greenhouse (G2) in Beijing (latitude 39°40′ N), the capital city of China. Emission rates of the GSHPs for heating the G1 and G2 were quantified to be 0.257–0.879 g CO2 eq. m−2 day−1. The total GHG emissions from heating greenhouses in Beijing with the GSHPs were quantified as 1.7–2.9 Gt CO2 eq. year−1 based on the electricity from the coal-fired power plant (CFPP) and the gas-fired power plant (GFPP). Among different stages of the SGE flow, the SGE promotion contributed most GHG emissions (66%) in total due to the higher consumption of electricity in compressors. The total GHG emissions from greenhouses heating with the coal-fired heating system (CFHs) and gas-fired heating system (GFHs) were quantified as 2.3–5.2 Gt CO2 eq. year−1 in Beijing. Heating the G1 and G2 with the GSHPs powered by the electricity from the CFPP, the equivalent CO2 emissions were 43% and 44% lower than directly burning coal with the CFHs but were 46% and 44% higher than the GFHs that burn natural gas. However, when using the GFPP-generated electricity to run the GSHPs, the equivalent CO2 emissions would be 84% and 47% lower than the CFHs and the GFHs, respectively

Effects of Comparative Metabolism on Tomato Fruit Quality under Different Levels of Root Restriction

In a soilless culture (perlite substrate), root restriction cannot only reduce production costs but also improve fruit quality. Therefore, this study used different levels of root restriction [T1: 0.5 L, T2: 4 L, nonrestriction treatment (CK): 35 L] on tomatoes to explore their impact on quality. Results showed that total soluble solids (TSS), glucose, fructose, and sucrose contents were increased, whereas L-tryptophan, L-tyrosine, and titratable acidity were decreased under two restriction treatments. Meanwhile, root restriction also promoted the accumulation of phenylalanine and proline. For lycopene and flavonoid biosynthesis (prunin, naringin, naringenin), the restriction groups were significantly higher than those in the control group. Overall, T1 and T2 treatment had a better effect than CK treatment. This study provided an idea for improving substrate use efficiency and tomato quality

Applications of functional near-infrared spectroscopy in non-drug therapy of traditional Chinese medicine: a review

Non-drug therapies of traditional Chinese medicine (TCM), including acupuncture, massage, tai chi chuan, and Baduanjin, have emerged as widespread interventions for the treatment of various diseases in clinical practice. In recent years, preliminary studies on the mechanisms of non-drug therapies of TCM have been mostly based on functional near-infrared spectroscopy (fNIRS) technology. FNIRS is an innovative, non-invasive tool to monitor hemodynamic changes in the cerebral cortex. Our review included clinical research conducted over the last 10 years, establishing fNIRS as a reliable and stable neuroimaging technique. This review explores new applications of this technology in the field of neuroscience. First, we summarize the working principles of fNIRS. We then present preventive research on the use of fNIRS in healthy individuals and therapeutic research on patients undergoing non-drug therapies of TCM. Finally, we emphasize the potential for encouraging future advancements in fNIRS studies to establish a theoretical framework for research in related fields

An Analysis on Leaf Traits of 22 Helianthus tuberosus Germplasm Resources Introduced from Abroad

Atomic absorption spectrophotometry, sulfuric acid and potassium dichromate oxidation method and ultraviolet spectrophotometry, were used to determine mineral elements, fiber, the content of chlorogenic acid and flavones in leaves of 24 Helianthus tuberosus Linn. resources, and the characteristics of the leaf introduced from abroad were evaluated. The results showed that the highest water content of 22 species was F12 (27.58%), and the lowest was F16 (19.02%). The difference in mean water content between the species from Denmark and France was small, but it was lower than that of Qingyu 3 and Qingyu 4. There were 3 orbicular leaves, 1 long oval-shaped leaf and 18 oval leaves. The highest K content in the leaves was F19 (30.62 mg/g), which was 2.5 times than Qingyu 3. The highest Mg content was D8 (14.17 mg/g). The Fe content had little difference, ranging from 0.09 mg•g−1 to 0.19 mg/g. The highest Ca content was D8 (26.87 mg/g). The highest level of chlorogenic acid and flavones was F7, 2.55% and 1.24 g/100 g respectively. The highest fiber content was F9 (16.7%), and the lowest was F19 (7.36%). Through the analysis of the main component and the clustering analysis, when the genetic distance was 0.65, the 24 resources can be divided into three major categories. The first category of leaves were mainly oval and orbicular; the second category of leaves were long oval-shaped; the third category of leaves were oval. There was a difference between the various indexes in the leaf of different kinds of Helianthus tuberosus Linn. resources. Finally, F19, D8, F9, F7, D14 and D11, 6 specific species (F19, D8, F9, F7, D14 and D11) were screened out for further studies in the future

Effect of Irrigation on Growth, Yield, and Chemical Composition of Two Green Bean Cultivars

A study was conducted in an environmentally controlled greenhouse to evaluate two green bean cultivars, ‘Bronco’ and ‘Paulista’, under three application volumes of irrigation water based on replacing 100, 80, and 60% of evapotranspiration (ET). The experiment was in a split-plot design with three replications, recording vegetative growth, yield, pod parameters, water use efficiency (WUE), and chemical content of pods. The results showed that there were no differences between 80% ET and 100% ET for most parameters. In addition, 80% of ET increased the pod yield and improved the pod parameters and chemical composition. Therefore, this irrigation treatment can increase green bean productivity and improve pod quality. Reducing water application from 100 to 60% of ET progressively increased WUE. The ‘Bronco’ cultivar had a higher plant height, pod yield, WUE, pod weight, pod diameter, and total fiber amount than ‘Paulista’, while the ‘Paulista’ cultivar was superior in total chlorophyll, number of pods per plant, pod length, P, Ca, Mg, Fe, Cu, protein, vitamin C, titratable acid, and soluble sugar

Do NH4:NO3 ratio and harvest time affect celery (Apium graveolens) productivity and product quality?

Due to the remarkable health benefits of celery (Apium graveolens), its consumption has increased over time. A partial substitution of NO3− with NH4+ is recommended to limit the accumulation of NO3− in leafy vegetables. Hence, a factorial experiment with two factors, consisting of six treatments as combinations of three NH4:NO3 ratios (0:100, 20:80 and 40:60) in nutrient solutions and two harvesting times (in the morning and in the evening), was conducted on celery plants in a soilless culture system. The results showed that 100% NO3 as a sole N source significantly increased plant height, leaf number, chlorophyll, fresh weight, N, K, Ca, Mg, Fe, Mn, Zn, protein, dietary fibre, soluble sugars, nitrate, vitamin C, α-carotene, β-carotene and lutein of celery plants compared to either 80 or 60% NO3. However, this increase was not significant compared to 20% NH4:80% NO3 in terms of leaf number, fresh yield, N, Mg, Mn, protein, soluble sugars, vitamin C and α-carotene. Harvesting in the evening significantly increased K, Mg, Fe, soluble sugars, α-carotene and β-carotene, and lowered the nitrate level in celery plants. In conclusion, partial replacement of 20% NO3-N with 20% NH4-N and evening harvesting are recommended for a greater fresh yield, higher quality, and lower nitrate level

Dynamic Compensation of Piezoresistive Pressure Sensor Based on Sparse Domain

In the process of transient test, due to the insufficient bandwidth of the pressure sensor, the test data is inaccurate. Firstly, based on the projection of the shock tube test signal in the sparse domain, the feature expression of the signal sample is obtained. Secondly, the problem of insufficient bandwidth is solved by inverse modeling of sensor dynamic compensation system based on swarm intelligence algorithm. In this paper, the method is used to compensate the shock tube test signals of the 85XX series pressure sensors made by the Endevco company of the United States, the working bandwidth of the sensor is widened obviously, the rise time of the pressure signal can be compensated to 12.5 μs, and the overshoot can be reduced to 8.96%. The repeatability of dynamic compensation is verified for the actual gun muzzle shock wave test data, the results show that the dynamic compensation can effectively recover the important indexes such as overpressure peak value and positive pressure action time, and the original shock wave signal is recovered from the high resonance data

Optimizing interlaminar toughening of carbon-based filler/polymer nanocomposites by machine learning

Currently, most designs for interlayer toughening of carbon-based filler/polymer nanocomposites are highly dependent on experimental iterative trial and error, and there is no rational design framework. This work uses machine learning to build a fast and accurate predictive model and assess the extent to which key features affect performance, giving researchers ideas for designing new materials and greatly improving efficiency. A training database is built by first collecting the features of the domain that affect the interlaminar performance. A stacking model fusion of the three machine learning models was then performed to construct a highly accurate fast prediction model. Besides, the importance of key features is evaluated during model training using the Random Forest Algorithm (RFA). Finally, by predicting the performance of materials and analyzing the importance of characteristics to guide material preparation, the development cycle is shortened and costs are reduced

Low Light Image Enhancement Based on Multi-Scale Network Fusion

At present, researchers have made great progress in the research of object detection, however, these studies mainly focus on the object detection of images under normal lighting, ignoring the target detection under low light. And images in the fields of automatic driving at night and surveillance are usually obtained in low-light environments. These images have problems such as poor brightness, low contrast, and obvious noise, which lead to a large amount of information loss in the image. And the performance of object detection in low light is reduced. In this paper, we propose a low-light image enhancement method based on multi-scale network fusion to solve the problems of images in low-light environments. Aiming at the problem that the effective information of low-light images is relatively small, we propose a preprocessing method for image nonlinear transformation and fusion, which improves the amount of available information in the light image. Then, in order to obtain a better enhancement effect, a multi-scale feature fusion method is proposed, which fuses features from different resolution levels in the network. The details of low-light areas in the image are improved, and the problem of feature loss caused by too deep network layers is solved. The experimental results show that our proposed method can achieve better enhancement effects on different datasets compared with the current mainstream methods. The average recall value of the object detection with our method is improved by 38.25%, which shows that our proposed method is effective and can promote the development of autonomous driving, monitoring, and other fields

Comprehensive Transcriptome Reveals an Opposite Regulatory Effect of Plant Growth Retardants in Controlling Seedling Overgrowth between Roots and Shoots

Seedling overgrowth always develops in undernourished plants due to biotic or abiotic stresses, which significantly decrease the yield of crops and vegetables. It is known that the plant growth retardants paclobutrazol (PBZ) and chlormequat chloride (CCC) are the most commonly used chemicals in controlling seedling height in plants by regulating the gibberellin (GA) biosynthesis pathway. However, the exact molecular regulation mechanism remains largely unknown. This study performed a comprehensive transcriptome profile to identify significantly differentially expressed genes after adding CCC and PBZ to the water culture seedling raising system for the first time. According to the obviously restrained shoots and roots, the GA biosynthesis genes were significantly decreased, as well as the endogenous GA content being reduced. Intriguingly, the GA signaling pathway genes were affected in opposite ways, increasing in roots but decreasing in shoots, especially regarding the phytochrome interacting factor SlPIF1 and the downstream genes expansins (SlEXPs), which promote cell wall remodeling. Further study found that the most down-regulated genes SlEXPA5 and SlEXPA15 were expressed specifically in shoot tissue, performing the function of repressing elongation, while the up-regulated genes SlEXPB2 and SlEXPB8 were proven to be root-specific expressed genes, which may promote horizontal elongation in roots. This research reported the comprehensive transcriptome profiling of plant growth retardants in controlling seedling overgrowth and restraining GA biosynthesis through the regulation of the GA signaling-related genes SlPIF1 and SlEXPs, with an opposite expression pattern between roots and shoots