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Soybean in relay intercropping is initially exposed to a shade environment, followed by exposure to full sunlight after the harvesting of primary crops, e.g., maize. Therefore, soybean's ability to acclimate to this changing light environment determines its growth and yield formation. However, the changes in soybean photosynthesis under such light alternations in relay intercropping are poorly understood. This study compared the photosynthetic acclimation of two soybean varieties with contrasting shade tolerance, i.e., Gongxuan1 (shade-tolerant) and C103 (shade-intolerant). The two soybean genotypes were grown in a greenhouse under full sunlight (HL) and 40% full sunlight (LL) conditions. Subsequently, after the fifth compound leaf expanded, half of the LL plants were transferred to a high-sunlight environment (LL-HL). Morphological traits were measured at 0 and 10 days, while chlorophyll content, gas exchange characteristics and chlorophyll fluorescence were assayed at 0, 2, 4, 7 and 10 days after transfer to an HL environment (LL-HL). Shade-intolerant C103 showed photoinhibition 10 days after transfer, and the net photosynthetic rate (Pn) did not completely recover to that under a high light level. On the day of transfer, the shade-intolerant variety, C103, exhibited a decrease in net photosynthetic rate (Pn), stomatal conductance (Gs) and transpiration rate (E) in the low-light (LL) and low-light-to-high-light (LL-HL) treatments. Additionally, intercellular CO2 concentration (Ci) increased in low light, suggesting that non-stomatal factors were the primary limitations to photosynthesis in C103 following the transfer. In contrast, the shade-tolerant variety, Gongxuan1, displayed a greater increase in Pn 7 days after transfer, with no difference observed between the HL and LL-HL treatments. Ten days after transfer, the shade-tolerant Gongxuan1 exhibited 24.1%, 10.9% and 20.9% higher biomass, leaf area and stem diameter than the intolerant C103. These findings suggest that Gongxuan1 possesses a higher capacity to adapt to variations in light conditions, making it a potential candidate for variety selection in intercropping systems. [ABSTRACT FROM AUTHOR]

The target region and diameter of maize stems are important phenotyping parameters for evaluating crop vitality and estimating crop biomass. To address the issue that the target region and diameter of maize stems obtained after transplantation may not accurately reflect the true growth conditions of maize, a phenotyping monitoring technology based on an internal gradient algorithm is proposed for acquiring the target region and diameter of maize stems. Observations were conducted during the small bell stage of maize. First, color images of maize plants were captured by an Intel RealSense D435i camera. The color information in the color image was extracted by the hue saturation value (HSV) color space model. The maximum between-class variance (Otsu) algorithm was applied for image threshold segmentation to obtain the main stem of maize. Median filtering, image binarization, and morphological opening operations were then utilized to remove noise from the images. Subsequently, the morphological gradient algorithm was applied to acquire the target region of maize stems. The similarity between the three types of gradient images and the manually segmented image was evaluated by pixel ratio extraction and image quality assessment indicators. Evaluation results indicated that the internal gradient algorithm could more accurately obtain the target region of maize stems. Finally, a checkerboard was employed as a reference for measurement assistance, and the stem diameter of maize was calculated by the pinhole imaging principle. The mean absolute error of stem diameter was 1.92 mm, the mean absolute percentage error (MAPE) was 5.16%, and the root mean square error (RMSE) was 2.25 mm. The R² value was 0.79. With an R² greater than 0.7 and a MAPE within 6%, the phenotyping monitoring technology based on the internal gradient algorithm was proven to accurately measure the diameter of maize stems. The application of phenotyping monitoring technology based on the internal gradient algorithm in field conditions provides technological support for smart agriculture. [ABSTRACT FROM AUTHOR]

Solving the problem of the stem contour extraction of maize is difficult under open field conditions, and the stem diameter cannot be measured quickly and nondestructively. In this paper, maize at the small and large bell stages was the object of study. An adaptive threshold segmentation algorithm based on the color space model was proposed to obtain the stem contour and stem diameter of maize in the field. Firstly, 2D images of the maize stem in the field were captured with an RGB-D camera. Then, the images were processed by hue saturation value (HSV) color space. Next, the stem contour of the maize was extracted by maximum between-class variance (Otsu). Finally, the reference method was used to obtain the stem diameter of the maize. Scatter plots and Dice coefficients were used to compare the contour extraction effects of the HSV + fixed threshold algorithm, the HSV + Otsu algorithm, and the HSV + K-means algorithm. The results showed that the HSV + Otsu algorithm is the optimal choice for extracting the maize stem contour. The mean absolute error, mean absolute percentage error (MAPE), and root mean square error (RMSE) of the maize stem diameter at the small bell stage were 4.30 mm, 10.76%, and 5.29 mm, respectively. The mean absolute error, MAPE, and RMSE of the stem diameter of the maize at the large bell stage were 4.78 mm, 12.82%, and 5.48 mm, respectively. The MAPE was within 10–20%. The results showed that the HSV + Otsu algorithm could meet the requirements for stem diameter measurement and provide a reference for the acquisition of maize phenotypic parameters in the field. In the meantime, the acquisition of maize phenotypic parameters under open field conditions provides technical and data support for precision farming and plant breeding. [ABSTRACT FROM AUTHOR]

Blue and red light are essential light signals used to regulate stomatal development and leaf structure. In the present study, stomatal and leaf traits that respond to blue and red light were studied at two light intensities (400 and 100 µmol m−2 s−1) in soybeans. The stomatal traits and leaf characteristics were determined. Furthermore, their contribution to the operational maximum stomatal conductance (gopmax) was evaluated using the rdacca.hp R package. With the light intensity significantly reduced, the stomatal size (SZ) under blue light did not change. Similarly, the decrease in light intensity did not influence the stomatal density (SD), specific leaf weight (SLW) or gopmax under red light. These results implied that the regulation of SD and SLW depended on blue light and that SZ was highly sensitive to red light. In addition, SLW was strongly correlated with SD. The SLW and SD had the highest contribution rates (19.43% and 19.5%, respectively) to gopmax, as compared with the other parameters. In conclusion, these results suggested that in long-term exposure to blue light, the enhancements in gopmax were primarily due to the synergistic promotion of SLW and SD. [ABSTRACT FROM AUTHOR]

The discussion on employee burnout (BOT) has existed in academic literature for a long time. While BOT was identified as a personal issue, there is a lack of a system approach solution. In this regard, a milestone was achieved in 2019 when the World Health Organization (WHO) introduced a new definition of BOT, recognising it as an occupational phenomenon, thereby placing a greater responsibility on organisational leadership to manage it. Since then, different leadership models have been proposed by scholars to reduce the effect of BOT in an organisation. Humble leadership (HL), as a people-first approach, has recently gained importance in organisational management literature. Studies have indicated that HL significantly influences different employee outcomes. However, research on the significance of HL to mitigate BOT of employees was scarce—similarly, on the underlying mechanisms of how and why. While HL has the potential to reduce BOT in an organisation, little or no research has studied it. Acknowledging these knowledge gaps, the basic aim of this study is to enrich the existing body of knowledge by proposing HL as an effective organisational management strategy to reduce the effect of BOT in the healthcare sector. The study introduces two mediators, work engagement (WREN) and subjective wellbeing (SUBW), to explain the underlying mechanism between HL and BOT. The conditional indirect role of altruism (ALM) was also tested. The data were obtained from hospital employees by employing a survey method (questionnaire, n = 303). Structural equation model (SEM) was considered for testing the hypothesised model to study the interrelationships between variables. The results confirmed that the manifestation of HL in an organisation reduces BOT significantly, and WREN and SUBW mediate this relationship. The study also demonstrates the buffering effect of ALM in the above-proposed relationships. The empirical findings offer multiple contributions in theory and practice, among which the most important one was to realise the profound importance of HL in reducing the effect of BOT in healthcare management. [ABSTRACT FROM AUTHOR]

Cerebrospinal fluid (CSF) human immunodeficiency virus-1 (HIV-1) ribonucleic acid (RNA) at higher levels than in plasma has been observed in HIV-1-positive patients and defined as CSF/plasma discordance or CSF escape. Discordance is particularly seen in untreated patients with antiretroviral agents. Quantitative data regarding its association with blood–brain barrier (BBB) damage and intracranial co-infection with other pathogens are limited. Therefore, we used the CSF to plasma HIV-1 RNA ratio (HRR) to determine its relation to central nervous system (CNS) co-infection in HIV-1-positive treatment-naïve individuals. We retrospectively recruited the subjects with HIV-1-positive and potential neurological deficits. A lumbar puncture was performed before the antiretroviral therapy. The paired CSF/plasma HIV-1 RNA samples were analyzed. Univariate and multivariate logistic regression models and multiple spine regression analyses were performed to assess the association between the HRR and CNS co-infection. A total of 195 patients with 78% males (median age: 49 years) were included in this study, of whom 98 (50.2%) had CNS co-infection with other pathogens. The receiver-operating characteristic curve analysis showed that the optimal cutoff value for the HRR to predict the CNS co-infection was 1.00. Higher HRR (≥1) was significantly associated with tuberculous meningitis (OR 6.50, 95% CI 2.08–20.25, p = 0.001), cryptococcus meningitis (OR 7.58, 95% CI 2.10–27.32, p = 0.001), and multiple co-infection (OR 4.04, 95% CI 1.02–16.04, p = 0.047). Higher HRR (≥1) (OR 3.01, 95% CI 1.09–8.73, p = 0.032) was independently associated with the CNS co-infection after adjusting for covariates. No significant nonlinear association was found between the HRR and CNS co-infection in the multivariate spline regression (p > 0.05) and a positive relationship was found between the HRR and CNS co-infection when the HRR was ≥0.78. Higher HRR was associated with an increased risk of CNS co-infection in HIV-1-positive patients. The relationship between the HRR and CNS co-infection may be related to the BBB disturbance and warrants further investigation with a large, longitudinal cohort. [ABSTRACT FROM AUTHOR]

Intercropping improves land-use efficiency under conditions of limited land and resources, but no information is currently available pertaining to land-use efficiency and silage quality based on whole-plant utilization. Therefore, a two-year field experiment was conducted with the following conditions: three maize–soybean strip intercropping patterns (SIPs), comprising two maize rows along with two, three, or four soybean rows (2M2S, 2M3S, and 2M4S, respectively); and two sole cropping patterns of maize (SM) and soybean (SS). The aim was to evaluate the biomass yield and silage quality under each condition. Our results showed that all SIPs had a land equivalent ratio (LER) of over 1.6 based on both fresh and dry matter yield, and a higher whole plant yield, compared to sole cropping. Specifically, 2M3S exhibited the highest whole crop dry matter LER (1.8–1.9) and yield (24.6–27.2 t ha−1) compared to SM and SS (20.88–21.49 and 3.48–4.79 t ha−1, respectively). Maize–soybean mixed silages also showed better fermentation quality with higher lactic acid content (1–3%) and lower ammonia-N content (2–8%) compared to SS silages, and higher crude protein content (1–1.5%) with lower ammonia-N content (1–2%) compared to SM silage. Among the intercropping patterns, 2M3S had the highest fermentation quality index V-score (92–95). Consequently, maize–soybean strip intercropping improved silage quality and biomass yield, with 2M3S being recommended, due to its highest LER and biomass yield, and most optimal silage quality. [ABSTRACT FROM AUTHOR]