Global Warming: Is It (Im)Possible to Stop It? The Systems Thinking Approach

An overview of image-based phenotyping as an adaptive 4.0 technology for studying plant abiotic stress: A bibliometric and literature review

Improving the tolerance of crop species to abiotic stresses that limit plant growth and productivity is essential for mitigating the emerging problems of global warming. In this context, imaged data analysis represents an effective method in the 4.0 technology era, where this method has the non-destructive and recursive characterization of plant phenotypic traits as selection criteria. So, the plant breeders are helped in the development of adapted and climate-resilient crop varieties. Although image-based phenotyping has recently resulted in remarkable improvements for identifying the crop status under a range of growing conditions, the topic of its application for assessing the plant behavioral responses to abiotic stressors has not yet been extensively reviewed. For such a purpose, bibliometric analysis is an ideal analytical concept to analyze the evolution and interplay of image-based phenotyping to abiotic stresses by objectively reviewing the literature in light of existing database. Bibliometricy, a bibliometric analysis was applied using a systematic methodology which involved data mining, mining data improvement and analysis, and manuscript construction. The obtained results indicate that there are 554 documents related to image-based phenotyping to abiotic stress until 5 January 2023. All document showed the future development trends of image-based phenotyping will be mainly centered in the United States, European continent and China. The keywords analysis major focus to the application of 4.0 technology and machine learning in plant breeding, especially to create the tolerant variety under abiotic stresses. Drought and saline become an abiotic stress often using image-based phenotyping. Besides that, the rice, wheat and maize as the main commodities in this topic. In conclusion, the present work provides information on resolutive interactions in developing image-based phenotyping to abiotic stress, especially optimizing high-throughput sensors in image-based phenotyping for the future development.

Efficient Photocatalytic Hydrogen Production over NiS-Modified Cadmium and Manganese Sulfide Solid Solutions

In this work, new photocatalysts based on Cd_1-xMn_xS sulfide solid solutions were synthesized by varying the fraction of MnS (x = 0.4, 0.6, and 0.8) and the hydrothermal treatment temperature (T = 100, 120, 140, and 160 °C). The active samples were modified with Pt and NiS co-catalysts. Characterization was performed using various methods, including XRD, XPS, HR TEM, and UV-vis spectroscopy. The photocatalytic activity was tested in hydrogen evolution from aqueous solutions of Na₂S/Na₂SO₃ and glucose under visible light (425 nm). When studying the process of hydrogen evolution using an equimolar mixture of Na₂S/Na₂SO₃ as a sacrificial agent, the photocatalysts Cd_0.5Mn_0.5S/Mn(OH)₂ (T = 120 °C) and Cd_0.4Mn_0.6S (T = 160 °C) demonstrated the highest activity among the non-modified solid solutions. The deposition of NiS co-catalyst led to a significant increase in activity. The best activity in the case of the modified samples was shown by 0.5 wt.% NiS/Cd_0.5Mn_0.5S (T = 120 °C) at the extraordinary level of 34.2 mmol g^-1 h^-1 (AQE 14.4%) for the Na₂S/Na₂SO₃ solution and 4.6 mmol g^-1 h^-1 (AQE 2.9%) for the glucose solution. The nickel-containing samples possessed a high stability in solutions of both sodium sulfide/sulfite and glucose. Thus, nickel sulfide is considered an alternative to depositing precious metals, which is attractive from an economic point of view. It worth noting that the process of photocatalytic hydrogen evolution from sugar solutions by adding samples based on Cd_1-xMn_xS has not been studied before.