Simulating soil salinity dynamics, cotton yield and evapotranspiration under drip irrigation by ensemble machine learning

Cotton is widely used in textile, decoration, and industry, but it is also threatened by soil salinization. Drip irrigation plays an important role in improving water and fertilization utilization efficiency and ensuring crop production in arid areas. Accurate prediction of soil salinity and crop evapotranspiration under drip irrigation is essential to guide water management practices in arid and saline areas. However, traditional hydrological models such as Hydrus require more variety of input parameters and user expertise, which limits its application in practice, and machine learning (ML) provides a potential alternative. Based on a global dataset collected from 134 pieces of literature, we proposed a method to comprehensively simulate soil salinity, evapotranspiration (ET) and cotton yield. Results showed that it was recommended to predict soil salinity, crop evapotranspiration and cotton yield based on soil data (bulk density), meteorological factors, irrigation data and other data. Among them, meteorological factors include annual average temperature, total precipitation, year. Irrigation data include salinity in irrigation water, soil matric potential and irrigation water volume, while other data include soil depth, distance from dripper, days after sowing (for EC and soil salinity), fertilization rate (for yield and ET). The accuracy of the model has reached a satisfactory level, R2 in 0.78-0.99. The performance of stacking ensemble ML was better than that of a single model, i.e., gradient boosting decision tree (GBDT); random forest (RF); extreme gradient boosting regression (XGBR), with R2 increased by 0.02%-19.31%. In all input combinations, other data have a greater impact on the model accuracy, while the RMSE of the S1 scenario (input without meteorological factors) without meteorological data has little difference, which is -34.22%~19.20% higher than that of full input. Given the wide application of drip irrigation in cotton, we recommend the application of ensemble ML to predict soil salinity and crop evapotranspiration, thus serving as the basis for adjusting the irrigation schedule

Simulating soil salinity dynamics, cotton yield and evapotranspiration under drip irrigation by ensemble machine learning

We thank the China Scholarship Council (CSC) for providing a scholarship (202206710073) to Zewei Jiang. This work was supported by the Fundamental Research Funds for the Central Universities (B220203009), the Postgraduate Research & Practice Program of Jiangsu Province (KYCX22_0669), the Water Conservancy Science and Technology Project of Jiangxi Province (201921ZDKT06, 202124ZDKT09), the National Natural Science Foundation of China (51879076), the Fundamental Research Funds for the Central Universities (B210204016), Science & Technology Specific Projects in Agricultural High-tech Industrial Demonstration Area of the Yellow River Delta, Grant No: 2022SZX01.Peer reviewedPublisher PD

Poly(sulfur-random-(1,3-diisopropenylbenzene)) Based Mid-Wavelength Infrared Polarizer: Optical Property Experimental and Theoretical Analysis

Development of polymer based mid-wavelength infrared (MWIR) optics has been limited mainly due to high optical loss of organic polymers used in general optical components. In this study, a MWIR polarization grating based on a sulfuric polymer poly(sulfur-random-(1,3-diisopropenylbenzene)) with a low loss in the MWIR range was fabricated using a simple two-step process: imprint and metal deposition. Fourier-transform infrared (FTIR) spectroscopy measurement showed that this polymeric MWIR polarizer selectively transmitted the polarized IR in transverse magnetic (TM) mode over the transverse electric (TE) mode at normal incidence. The measured extinction ratios (  = The ratio of transmissions in TM and TE) were 208, 176, and 212 at the wavelength of 3, 4, and 5 μm, respectively. The computational simulation and analytical model confirmed that the enhanced TM transmission efficiency and followed a Fabry-Pérot (FP) resonance mode within the created sulfuric polymer film. This polymeric MWIR polarizer demonstrated a great potential for broader applications in IR photonics to realize low-cost and durable optical components

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

A Trade-Off between the Growing Performance and Sowing Density of Sunflower (<i>Helianthus annuus</i> L.) under Fertigation in an Arid Saline Area

Sunflower is one of the pioneer crops cultivated in salt-affected arid areas. The influences of sowing density on the growth performance of this crop under fertigation conditions have not been well studied. This study arranged four sowing density treatments, 41,667, 35,714, 31,250, and 27,778 plants ha−1, marked as D30, D35, D40, and D45, respectively, to reveal the relationships between soil salinity, growth performance, and sowing density under drip fertigation conditions. The results showed that the electrical conductivity of saturated paste extracts (ECe) decreased during the growing seasons but increased on the topsoil during the non-growing seasons in all of the treatments. The sowing densities had remarkable influences on the ECe in the 0–40 cm soil layer (ECe-40). The average ECe-40 during the two seasons for treatments D30–D45 correspondingly decreased by 7.0%, 33.9%, 11.1%, and 15.8% when compared to the original value. The soil pH in the 0–40 cm soil layer during the two seasons for treatments D30–D45 correspondingly decreased by −0.03, 0.20, 0.20, and 0.27 when compared to the original value. Increasing the spacing in the rows could promote the stem diameter, plant biomass, and proportion of biomass allocated underground. The yield and related yield components in this experiment under fertigation were significantly higher than those under surface irrigation. A sowing density between 31,250 and 35,714 plants ha−1 could ensure both the high yield and high morphological quality of the seeds, which could be recommended for sunflower cultivation under drip fertigation conditions

Changes in understory vegetation during the reclamation of saline-alkali soil by drip irrigation for shelterbelt establishment in the Hetao Irrigation Area of China

A two-year experimental field study was conducted to monitor the changes in understory vegetation during reclamation of saline-alkali land by ridge cultivation with drip irrigation for the establishment of ecological shelterbelts in the Hetao Irrigation Area in northern China. The experiment carried out in 2019 and 2020, included four drip irrigation treatments, designated 0 (control, no irrigation, no trees), 1 (1 year of drip irrigation plus trees), 2 (2 years of drip irrigation plus trees), and 3 (3 years of drip irrigation plus trees). Treatments 1, 2, and 3 resulted in decreases in soil salinity (relative to the control) of 75.76%, 85.98%, and 85.58%, respectively, over a depth of 0-40 cm, and 51.65%, 81.85%, and 70.80%, respectively, over a depth of 0-120 cm. The pH of the saturated soil paste extract (pHe) of the 0-40 cm and 0-120 cm soil layer decreased from 9.68 and 9.54 in the first year to 9.07 and 8.44 in the third year, in response to drip irrigation. The coverage, plant species and plant density of understory vegetation (following natural germination of seeds from the seed bank under the shelterbelt trees) was increased significantly from treatment 0 to 3, with values of 5.7%, 2 and 15 plants/m2 (treatment 0), respectively, to 94.4%, 20 and 416 plants/m2, (treatment 3), respectively. The biomass of the understory vegetation increased dramatically (after treatment 1), then decreased slightly more (after treatment 2), until the maximum value occurred after treatment 3. The dominant species of the vegetation gradually changed from the halophytic annual herb Suaeda glauca to the halophytic perennial grass Leymus chinensis. The research showed that, when the electrical conductivity of the saturated soil paste extract (ECe) exceeded 4.5 dS/ m, there was sparse vegetation; At lower salinity (2.6 < ECe < 4.5 dS/m) and higher pH (8.9 < pHe < 9.2), the species diversity gradually increased but without a clearly dominant species; At ECe < 2.8 dS/m, and pHe < 8.6, the dominance of plants of the Poaceae and Asteraceae families became apparent with L. chinensis developing into the dominant plant species in this area. This study contributes to our understanding of revegetation of saline alkali soils vegetation construction by salt regulation using drip irrigation and can inform ecological reconstruction in saline alkali regions in the future

Soil water and salinity dynamics under the improved drip-irrigation scheduling for ecological restoration in the saline area of Yellow River basin

The drip-irrigation scheduled by different soil matric potential (SMP) thresholds at different stages according to soil water and salt management purposes was usually adopted for revegetation in saline-alkali land. To reveal the desalinization mechanism of this multi-stage drip-irrigation scheduling, a 3-year field trial, adopting this method for revegetation, was conducted in an arid saline area. The trial consisted of 5 irrigation treatments marked S1 S5, with their SMP that monitored directly under drip emitter at 0.2 m depth correspondingly controlled higher than -5, -10, -15, -20 and -25 kPa. Results showed the SMP threshold of 5 kPa during the unified irrigation stage induced a leaching fraction (LF) of 42.6% and a minimum recharge amount (MRA) from groundwater of zero, thus resulting the relative desalinization rate (RDR) of 91.8% in 0-120 cm soil layer. When treatment applied, the average electrical conductivity of the saturated soil extracts (ECe) in 0-40 cm among three growing seasons in S1-S5 treatments linearly increased from 0.90 to 1.73 dS/m as SMP threshold decreased from -5 to -25 kPa, resulting from the LF correspondingly decreasing from 18.4% to 2.5% and the MRA increasing from 0 to 21.4 mm. The inter-annual salt dynamic indicated a salt equilibrium state was formed in 80-120 cm soil layer when the SMP threshold was set higher than 10 kPa and that was formed in 40-80 cm soil layer if the SMP threshold was set between -20 and -15 kPa. This study found the SMP threshold controlled the LF and MRA, and eventually determined the dynamics of soil salinity, which explained the efficient desalinization mechanism under the multi-stage drip-irrigation scheduling. A key SMP threshold of 5 kPa for rapid soil leaching stage and that of -20 kPa for precise salt regulating stage were recommended for vegetation construction in the low-lying saline area

Process optimization of A356 aluminum alloy wheel hub fabricated by low-pressure die casting with simulation and experimental coupling methods

The aluminum alloy wheel hub is mainly produced by low-pressure die casting process (LPDC), in which casting quality is closely related to the process parameters. In this paper, the LPDC process of the A356 alloy wheel hub was numerically simulated by ProCAST software, and the forming quality of the wheel hub under different cooling processes has been studied. The result indicated that the liquid aluminum exhibited different solidification characteristics under three cooling processes of 300 L/h for 150 s, 400 L/h for 140 s and 500 L/h for 130 s. A sequential solidification state was obtained under the condition of 400 L/h for 140 s. By comparing the tensile properties of the rim under different cooling processes, it was found that the wheel hub casted under 400 L/h for 140 s had higher tensile strength and elongation, which were 178.9 MPa and 6.6%, respectively. The reduction of casting defects, microstructure refinement, and uniform distribution of eutectic Si particles in the wheel hub are the main reasons for the improvement of mechanical properties