Application of BP neural network model with fuzzy optimization in retrieval of biomass parameters

The retrieval of the biomass parameters from active/passive microwave remote sensing data （10.2 GHz） is performed based on an iterative inversion of BP neural network model with fuzzy optimization. The BP neural network is trained by a set of the measurements of active and passive remote sensing and the ground truth data versus Day of Year during growth. Once the network training is complete, the model can be used to retrieve the temporal variations of the biomass parameters from another set of observation data. The model was used in weights and microware observation data of wheat growth in 1989 to retrieve biomass parameters change of wheat growth this year. The retrieved biomass parameters correspond well with the real data of the growth, which shows that the BP model is scientific and sound.

Development of monitoring and assessment of forest biomass and carbon storage in China

Addressing climate change has become a common issue around the world in the 21st century and equally an important mission in Chinese forestry.Understanding the development of monitoring and assessment of forest biomass and carbon storage in China is important for promoting the evaluation of forest carbon sequestration capacity of China.The author conducts a systematic analysis of domestic publications addressing＂monitoring and assessment of forest biomass and carbon storage＂in order to understand the development trends,describes the brief history through three stages,and gives the situation of new development.Towards the end of the 20th century,a large number of papers on biomass and productivity of the major forest types in China had been published,covering the exploration and efforts of more than 20 years,while investigations into assessment of forest carbon storage had barely begun.Based on the data of the 7th and 8th National Forest Inventories,forest biomass and carbon storage of the entire country were assessed using individual tree biomass models and carbon conversion factors of major tree species,both previously published and newly developed.Accompanying the implementation of the 8th National Forest Inventory,a program of individual tree biomass modeling for major tree species in China was carried out simultaneously.By means of thematic research on classification of modeling populations,as well as procedures for collecting samples and methodology for biomass modeling,two technical regulations on sample collection and model construction were published as ministerial standards for application.Requests for approval of individual tree biomass models and carbon accounting parameters of major tree species have been issued for approval as ministerial standards.With the improvement of biomass models and carbon accounting parameters,thematic assessment of forest biomass and carbon storage will be gradually changed into a general monitoring of forest biomass and carbon storage,in order to realize their dynamic monitoring in national forest inventories.Strengthening the analysis and assessment of spatial distribution patterns of forest biomass and carbon storage through application of remote sensing techniques and geostatistical approaches will also be one of the major directions of development in the near future.

Ultraviolet-B Radiation Alters Soybean Growth and Seed Quality

Research on the effects of ultraviolet-B (UV-B) radiation on soybean seed quality is limited. The objective of this study was to quantify UV-B doses, 0, 5, 10 & 15 kJ•m–2•d–1, on soybean growth and seed quality. The experiment was conducted in the Soil-Plant-Atmosphere-Research (SPAR) facility. Chambers located at the R.R. Foil Plant Science Research Facility of Mississippi State University, Mississippi, USA, were used. Each SPAR chamber consists of a steel soil bin to accommodate the root system, a Plexiglas chamber to accommodate plant canopy and a heating, and cooling system connected to air ducts that pass conditioned air to cause leaf flutter through the plant canopy. The SPAR units, supported by an environmental monitoring and control systems, are networked to provide automatic acquisition and storage of the data, monitored every 10 seconds throughout the day and night. Soybean cultivar Pioneer 93Y92 (maturity group IV, Roundup Ready) was used in the study. The desired UV-B radiation was supplied by square-wave UV-B supplementation systems under near ambient PAR and delivered to plants for eight hours, each day, from 08:00 to 16:00 h by eight fluorescent UV-313 lamps. The results showed that increased UV-B did not influence many of the growth parameters because the treatments were imposed at mid-fruiting period. Seed quality parameters that are important for seed industry and human and animal nutrition were all affected by UV-B. Protein and palmitic and oleic acids declined linearly, while oil and linoleic and linolenic acid contents increased with increased UV-B. Sucrose, stachyose, and stearic acid contents showed quadratic trends, increased to about 4 - 5 kJ of UV-B and declined at higher doses. Thus, both current and projected UV-B radiation levels can modify soybean growth and seed quality. The functional algorithms developed in this study could be useful to develop UV-B- specific sub-models for soybean farm management and in policy decision areas.