Estimating peanut and soybean photosynthetic traits using leaf spectral reflectance and advance regression models.

MAIN CONCLUSION: By combining hyperspectral signatures of peanut and soybean, we predicted Vcmax and Jmax with 70 and 50% accuracy. The PLS was the model that better predicted these photosynthetic parameters. One proposed key strategy for increasing potential crop stability and yield centers on exploitation of genotypic variability in photosynthetic capacity through precise high-throughput phenotyping techniques. Photosynthetic parameters, such as the maximum rate of Rubisco catalyzed carboxylation (Vc,max) and maximum electron transport rate supporting RuBP regeneration (Jmax), have been identified as key targets for improvement. The primary techniques for measuring these physiological parameters are very time-consuming. However, these parameters could be estimated using rapid and non-destructive leaf spectroscopy techniques. This study compared four different advanced regression models (PLS, BR, ARDR, and LASSO) to estimate Vc,max and Jmax based on leaf reflectance spectra measured with an ASD FieldSpec4. Two leguminous species were tested under different controlled environmental conditions: (1) peanut under different water regimes at normal atmospheric conditions and (2) soybean under high [CO2] and high night temperature. Model sensitivities were assessed for each crop and treatment separately and in combination to identify strengths and weaknesses of each modeling approach. Regardless of regression model, robust predictions were achieved for Vc,max (R2 = 0.70) and Jmax (R2 = 0.50). Field spectroscopy shows promising results for estimating spatial and temporal variations in photosynthetic capacity based on leaf and canopy spectral properties.

Global warming potential of typical rural domestic waste treatment modes in China: a case study in Ankang.

The global problem of domestic waste management increases with rapid population growth and with economic and urban development. In developing countries, treatment of rural domestic waste (RDW) is distinguished from urban waste. Quantitative assessment of greenhouse gas emissions from RDW disposal treatment is needed to achieve carbon neutrality. Reliable global warming potential (GWP) assessments of RDW are not differentiated in the widely accepted "urban-rural integration" centralized disposal model. We considered five different scenarios for RDW management. Scenario 1 (S1), unsanitary landfill (open-air dump); scenario 2 (S2), sanitary landfill; scenario 3 (S3), incineration; scenario 4 (S4), biological + incineration; and scenario 5 (S5), classification + composting + sanitary landfill + recycling. Life cycle assessment was used for GWP, and sensitivity analysis was calculated to point out the sensitive parameter. We found that the mean GWP ranged from 5.14 × 104 to 2.31 × 105 kg CO2-equivalents. Pollution from untreated RDW with landfill gas emissions led to large contributions under all scenarios. The collection and transportation ratio was sensitive to all scenarios, and we found that, if the recyclable materials separated at source were not used efficiently, the impact on GWP would be greater than under the unclassified waste scenarios. A "new urban-rural integration" mode (S5) that included household classification, village collection, town transfer, and county and urban disposal was introduced for RDW management. These quantitative results have a great potential for promoting effective RDW management in China and other developing countries.

Migration characteristics and toxicity evaluation of heavy metals during the preparation of lightweight aggregate from sewage sludge.

A lightweight aggregate (LWA) was manufactured from municipal sewage sludge, gangue, and coal ash. The product performance and environmental safety of the sintered material were evaluated by changing the sludge blending ratio and sintering temperature. The distribution and migratory transformation characteristics of heavy metals in LWA were examined by BCR sequential extraction in combination with inductively coupled plasma optical emission spectrometry (ICP-OES). The environmental safety performance of LWA was comprehensively evaluated by the OPTI index for the first time. The leaching concentration of the heavy metals Pb, Ni, Cu, and Zn in raw materials without sintering reached 1.17, 1.6, 7.84, and 7.56 mg/L, respectively, far exceeding the regulatory threshold value. At 1250 °C, sintering with 60% sludge content resulted in Cu and Zn leaching concentrations of only 0.41 mg/L and 0.37 mg/L, respectively. Furthermore, a big portion of heavy metals were in the residual fraction of sintered LWA. The proportion of comprehensive pollutant toxicity index is only 199.17. Additionally, the mechanical properties of sintered LWA exceed the standards stipulated in the GB/T1743.1-2010 standard. Using sewage sludge to manufacture lightweight aggregate is not only environmentally safe but also produces LWA with good engineering characteristics.