The present study investigated the growth of Capsicum annuum L. (pepper) in an outdoor pot experiment. Changes in the plants’ aboveground and root biomass, leaf area, plant height, stem thickness, and yield, as a response to different doses of biochar amendments were observed. During the 12.5-week-long study, four treatments with biochar amounts of 0, 0.5%, 2.5%, and 5.0% (by weight) were added to silt loam soil. Photochemical responses of plants, the plants photochemical reflectance index (PRI) modified by the different doses of biochar were continuously monitored. Plant height and fruit yield were initially the highest for BC5.0; however, by the end of the experiment, both parameters showed higher values for BC2.5, e.g., 15.9 and 9.1% higher plant height and 32.5 and 22.6% higher fruit yield for BC2.5 and BC5.0 compared to control, respectively. By the end of the experiment the BC2.5 treatments had significantly higher stem thickness (p < 0.001) compared to all other amendments. Root dry matter in biochar treatments increased relative to controls with the highest values (54.9% increase) observed in the BC2.5 treatment. Biochar treatment increased leaf area index (LAI) values for the higher doses (1.58, 1.59, 2.03, and 1.89 for C, BC0.5, BC2.5, and BC5.0, respectively). Significant differences between control and biochar amended soils’ PRI measurements were observed (p < 0.001), showing less plant sensitivity to environmental changes when biochar was applied to the soil. While biochar amendment could greatly enhance plant growth and development, there is an optimal amount of biochar after which additional amount might not result in substantial differences, or even can result in lower fruit yield as found in the present study.
Gridded model assessments require at least one climatic and one soil database for carrying out the simulations. There are several parallel soil and climate database development projects that provide sufficient, albeit considerably different, observation based input data for crop model based impact studies. The input database related uncertainty of the Biome-BGCMuSo agro-environmental model outputs was investigated using three and four different gridded climatic and soil databases, respectively covering an area of nearly 100.000 km 2 with 1104 grid cells. Spatial, temporal, climate and soil database selection related variances were calculated and compared for four model outputs obtained from 30-year-long simulations. The choice of the input database introduced model output variability that was comparable to the variability the year-to-year change of the weather or the spatial heterogeneity of the soil causes. Input database selection could be a decisive factor in carbon sequestration related studies as the soil carbon stock change estimates may either suggest that the simulated ecosystem is a carbon sink or to the contrary a carbon source on the long run. Careful evaluation of the input database quality seems to be an inevitable and highly relevant step towards more realistic plant production and carbon balance simulations.
Leaf Area Index (LAI) is an important plant parameter for both farmers and plant scientists to monitor and/or model the growth and the well-being of plants. Since direct LAI measurement techniques are relatively laborious and time-consuming, various indirect methods have been developed and widely used since the early 1990s. The LP-80 ceptometer uses a linear array of PAR (photosynthetically active radiation) sensors for non-destructive LAI measurements that is backed by 15 years of research. Despite this, considerable discrepancy can be found between the expert opinions regarding the optimal illumination conditions recommended for the measurement. The sensitivity of ceptometer-based LAI values to PAR was investigated, and a simple method was devised to correct raw ceptometer data collected under non-ideal light conditions. Inadequate light conditions (PAR < 1700 µmol m−2 s−1) could cause an underestimation of LAI. Using the corrected LAI values, the ceptometer data showed a significantly better fit (higher R2, smaller mean average error and closer to zero mean signed error values) to the destructive LAI data for both wheat and maize. With the help of the correction equations, the use of the LP-80 ceptometer could be extended to days when light conditions are not ideal.
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