Impacts of ozone on the biomass and yield of rice in open top chambers

The impacts of different 03 concentration on the biomass and yield of rice were studied by using OTC-1 open-top chambers. Experimental treatments included the activated charcoal-filtered air. (CFA), 50 nl/L (CF50), 100 nl/L ( CF100) and 200 nl/L (CF200) concentrations of O-3. The O-3 treatments significantly decreased the total biomass per plant. The. elevated O-3 exposure resulted in a more decrease in the root growth than in the shoot growth. Assessments of yield characteristics at the final harvest revealed an O-3-induced decrease in the number of grains per plant, resulting from fewer ears per plant, fewer grains per ear and more unfilled grains per ear. The 1000 grain dry weight and the harvest index (HI) were not changed significantly under 50 nl/L or 100 nl/L O-3 exposure, but reduced by 17.0% and 4.8% by 200nl/L O-3 treatment, respectively. Compared to the CFA treatment, CF50, CF100 and CF200 treatments caused a 8.2%, 26.1%, 49.1% decrease of the grain yield per plant, and a 14.2%, 31.7%, 51.7% decrease of the total biomass per plant, respectively. Linear regression showed that the 7h - daily mean O-3 concentration exposure for 3 months ( July-September) and AOT40 ( cunulative exposure accumulation over threshold 40 nl/L) were well correlated with the relative grain yield. A yield loss of 10% was estimated to be at 46.9 nl/L O-3 for 7h-daily mean O-3 concentration exposure or at 12930nl/(L(.)h) O-3 for AOT40.

Biomass-Based Rice (Oryza sativa L.) Aboveground Architectural Parameter Models

To quantify the relationships between rice plant architecture parameters and the corresponding organ biomass, and to research on functional structural plant models of rice plant, this paper presented a biomass-based model of aboveground architectural parameters of rice （Oryza sativa L.） in the young seedling stage, designed to explain effects of cultivars and environmental conditions on rice aboveground morphogenesis at the individual leaf level. Various model variables, including biomass of blade and blade length, were parameterized for rice based on data derived from an outdoor experiment with rice cv. Liangyou 108, 86You 8, Nanjing 43, and Yangdao 6. The organ dimensions of rice aboveground were modelled taking corresponding organ biomass as an independent variable. Various variables in rice showed marked consistency in observation and simulation, suggesting possibilities for a general rice architectural model in the young seedling stage. Our descriptive model was suitable for our objective. However, they can set the stage for connection to physiological model via biomass and development of functional structural rice models （FSRM）, and start with the localized production and partitioning of assimilates as affected by abiotic growth factors. The finding of biomass-based rice architectural parameter models also can be used in morphological models of blade, sheath, and tiller of the other stages in rice life.

Biomass and dominance of conservative species drive above-ground biomass productivity in a mediterranean-type forest of Chile

Background: Forest productivity has a pivotal role in human well-being. Vegetation quantity, niche complementarity, mass-ratio, and soil resources are alternative/complementary ecological mechanisms driving productivity. One challenge in current forest management depends on identifying and manipulating these mechanisms to enhance productivity. This study assessed the extent to which these mechanisms control aboveground biomass productivity(AGBP) of a Chilean mediterranean-type matorral. AGBP measured as tree aboveground biomass changes over a 7-years period, was estimated for twelve 25 m × 25 m plots across a wide range of matorral compositions and structures. Variables related to canopy structure, species and functional diversity, species and functional dominance, soil texture, soil water and soil nitrogen content were measured as surrogates of the four mechanisms proposed. Linear regression models were used to test the hypotheses. A multimodel inference based on the Akaike’s information criterion was used to select the best models explaining AGBP and for identifying the relative importance of each mechanism.Results: Vegetation quantity(tree density) and mass-ratio(relative biomass of Cryptocarya alba, a conservative species) were the strongest drivers increasing AGBP, while niche complementarity(richness species) and soil resources(sand, %) had a smaller effect either decreasing or increasing AGBP, respectively. This study provides the first assessment of alternative mechanisms driving AGBP in mediterranean forests of Chile. There is strong evidence suggesting that the vegetation quantity and mass-ratio mechanisms are key drivers of AGBP, such as in other tropical and temperate forests. However, in contrast with other studies from mediterranean-type forests, our results show a negative effect of species diversity and a small effect of soil resources on AGBP.Conclusion: AGBP in the Chilean matorral depends mainly on the vegetation quantity and mass-ratio mechanisms.The findings of this study have implications for matorral restoration and management for the production of timber and non-timber products and carbon sequestration.

Biomasses in Different Organs of Rice Cultivars Developed During Recent Forty-Seven Years in Jilin Province, China

To understand the changes in yield, harvest index （HI） and biomass of aboveground parts of rice, 33 japonica rice cultivars released from 1958 to 2005 were planted. During the 47 years, the grain yield increased from 9 118.36 to 15 060.1 kg/hm2 and HI from 0.46 to 0.55. In the genetic improvement, the total number of tillers per plant decreased, and the biomass per unit area slightly increased at the harvest stage. The increases of yield and HI resulted from the increased biomasses of effective tillers and single stem, and the increase of biomass per stem was related to the increased biomasses of different organs along with the genetic improvement. The stem and sheath biomass at heading and the leaf biomass at 30 days after heading showed the highest increase, up by 75.17% and 49.94%, respectively. The biomasses of leaf and stem-sheath at 10 days after heading, and biomass per stem at 30 days after heading were obviously correlated with the yield. The results indicate that the genetic improvement has resulted in the increase of yield and HI. This increase is correlated with the decrease of total tiller number per plant, and increase of biomasses of effective tillers and single stem. The leaf biomass after heading and the stem and sheath biomass at 10 days after heading can be used as selection criteria for breeding high yielding rice cultivars.

Estimating canopy closure density and above-ground tree biomass using partial least square methods in Chinese boreal forests

Boreal forests play an important role in global environment systems. Understanding boreal forest ecosystem structure and function requires accurate monitoring and estimating of forest canopy and biomass. We used partial least square regression （PLSR） models to relate forest parameters, i.e. canopy closure density and above ground tree biomass, to Landsat ETM＋ data. The established models were optimized according to the variable importance for projection （VIP） criterion and the bootstrap method, and their performance was compared using several statistical indices. All variables selected by the VIP criterion passed the bootstrap test （p〈0.05）. The simplified models without insignificant variables （VIP 〈1） performed as well as the full model but with less computation time. The relative root mean square error （RMSE%） was 29% for canopy closure density, and 58% for above ground tree biomass. We conclude that PLSR can be an effective method for estimating canopy closure density and above ground biomass.

Estimating above-ground biomass by fusion of LiDAR and multispectral data in subtropical woody plant communities in topographically complex terrain in North-eastern Australia

We investigated a strategy to improve predicting capacity of plot-scale above-ground biomass （AGB） by fusion of LiDAR and Land- sat5 TM derived biophysical variables for subtropical rainforest and eucalypts dominated forest in topographically complex landscapes in North-eastern Australia. Investigation was carried out in two study areas separately and in combination. From each plot of both study areas, LiDAR derived structural parameters of vegetation and reflectance of all Landsat bands, vegetation indices were employed. The regression analysis was carded out separately for LiDAR and Landsat derived variables indi- vidually and in combination. Strong relationships were found with LiDAR alone for eucalypts dominated forest and combined sites compared to the accuracy of AGB estimates by Landsat data. Fusing LiDAR with Landsat5 TM derived variables increased overall performance for the eucalypt forest and combined sites data by describing extra variation （3% for eucalypt forest and 2% combined sites） of field estimated plot-scale above-ground biomass. In contrast, separate LiDAR and imagery data, andfusion of LiDAR and Landsat data performed poorly across structurally complex closed canopy subtropical minforest. These findings reinforced that obtaining accurate estimates of above ground biomass using remotely sensed data is a function of the complexity of horizontal and vertical structural diversity of vegetation.

Evaluation and Selection of High Biomass Rice (<i>Oryza sativa L.</i>) for Drought Tolerance

Biomass production is important in increasing yield not only for food but also for bio-fuel production that depends on high dry matter. Due to climate change, occurrence of drought may be prevalent and this affects both grain and biomass yields in crops including rice. The objectives of this study were to determine the performance of selected high biomass breeding rice lines to different levels of drought and use several drought tolerance indices to identify best genotypes that could be grown in unfavorable water stressed areas. A rainfed and flooded trial was conducted to evaluate 20 selected breeding lines for biomass production and ten entries from the same set were grown in the greenhouse at three different field capacities (FC, 50%, 75%, 100%). Most of the genotypes performed well under non-stressed conditions (flooded and 100% FC) but some genotypes performed well in water stressed condition. The plants had lower plant height, tiller plant-1, and total biomass at maturity under rainfed conditions and their flowering was delayed compared to flooded conditions. In the greenhouse, water stress slowed the rate of increase in height, and produced lower shoot and root weight, percent dry matter (% DM) and total biomass. However, drought enhanced the rate of tiller production. Two genotypes were found to more tolerant to drought stress and could be used for cultivation under water stress condition to get optimum biomass yields. These genotypes can be identified using drought tolerance indices, particularly stress tolerance index (STI), geometric mean productivity (GMP), mean productivity (MP) and harmonic mean (HARM), as these have a similar ability to separate drought sensitive and tolerant genotypes. Genetic and molecular analyses, and detailed characterization of these genotypes will help understand their inheritance pattern and the number of genes controlling the traits and determine specific leaves and root traits important in developing high biomass rice.

Estimation of the Above-ground Biomass of Tamarix Species along a Transect at the Tarim River's Middle Reaches

[Objective] The purpose was to research the distribution characteristics of Tamarix species above-ground biomass of Tarim River＇s middle reaches and to find out best-fit linear-regression model of Tamarix species in this area.[Method] By dint of the most common sampling method PCQ,five samples in the middle reaches of Tarim River were collected.The best-fit linear-regression model of Tamarix species of this area was set up,based on the fieldwork and the model of Evangelista and obtained the distribution rules of Tamarix species of Tarim River＇s middle reaches.[Result] The result indicated that this model fitted for the estimation of aboveground biomass of the study area.According to the distribution rules of aboveground biomass,it was clear that underground water was the major element which decided the distribution of aboveground biomass.[Conclusion] The study provided theoretical basis for the calculation of biomass of Tamarix.

Plant cover as an estimator of above-ground biomass in semi-arid woody vegetation in Northeast Patagonia,Argentina

The quantification of carbon storage in vegetation biomass is a crucial factor in the estimation and mitigation of CO2 emissions.Globally,arid and semi-arid regions are considered an important carbon sink.However,they have received limited attention and,therefore,it should be a priority to develop tools to quantify biomass at the local and regional scales.Individual plant variables,such as stem diameter and crown area,were reported to be good predictors of individual plant weight.Stand-level variables,such as plant cover and mean height,are also easy-to-measure estimators of above-ground biomass(AGB)in dry regions.In this study,we estimated the AGB in semi-arid woody vegetation in Northeast Patagonia,Argentina.We evaluated whether the AGB at the stand level can be estimated based on plant cover and to what extent the estimation accuracy can be improved by the inclusion of other field-measured structure variables.We also evaluated whether remote sensing technologies can be used to reliably estimate and map the regional mean biomass.For this purpose,we analyzed the relationships between field-measured woody vegetation structure variables and AGB as well as LANDSAT TM-derived variables.We obtained a model-based ratio estimate of regional mean AGB and its standard error.Total plant cover allowed us to obtain a reliable estimation of local AGB,and no better fit was attained by the inclusion of other structure variables.The stand-level plant cover ranged between 18.7%and 95.2%and AGB between about 2.0 and 70.8 Mg/hm^(2).AGB based on total plant cover was well estimated from LANDSAT TM bands 2 and 3,which facilitated a model-based ratio estimate of the regional mean AGB(approximately 12.0 Mg/hm^(2))and its sampling error(about 30.0%).The mean AGB of woody vegetation can greatly contribute to carbon storage in semi-arid lands.Thus,plant cover estimation by remote sensing images could be used to obtain regional estimates and map biomass,as well as to assess and monitor the impact of land-use change on the carbon balance,for arid and semi-arid regions.

Effects of Carbon and Nitrogen Additions on Soil Microbial Biomass Carbon and Enzyme Activities Under Rice Straw Returning

The effects of different amounts of carbon and nitrogen sources on the soil microbial biomass carbon,dissolved organic carbon and related enzyme activities were studied by the simulation experiment of rice straw returning to the field,and the mechanism of the decomposition of rice straw returning to the field was discussed.Completely randomized experiment of the two factors of the three levels was designed,and a total of nine treatments of indoor soil incubation tests were conducted.Full amount of rice straw was applied to the soil in this simulation experiment and different amounts of brown sugar and urea were added in the three levels of 0(no carbon source and nitrogen source),1(low levels of carbon and nitrogen sources)and 2(high levels of carbon and nitrogen sources),respectively.The results showed that the addition of different amounts of carbon and nitrogen sources to the rice straw could increase the soil carbon content.Compared with T0N0,the microbial biomass carbon of T2N2 was increased significantly by 170.48%;the dissolved organic carbon content of T1N2 was significantly increased by 58.14%and the free humic acid carbon contents of T0N2,T1N1 and T2N0 were significantly increased by 56.16%and 45.55%and 47.80%,respectively;however,there were no significant differences among those of treatments at later incubation periods.The addition of different carbon and nitrogen sources could promote the soil enzyme activities.During the incubation period,all of the soil enzyme activities of adding sugar and urea were higher than those of T0N0 treatment.Therefore,the addition of different amounts of carbon and nitrogen sources to rice straw returning could improve soil microbial biomass carbon content,dissolved organic carbon and soil enzyme activities.

Potential aspect of rice husk biomass in Australia for nanocrystalline cellulose production

Nanocrystalline cellulose(NCC) was produced from rice husk biomass(Oryza sativa) by a chemical extraction process to explore the potential aspect of agro-waste biomass in Australia. In this work, the delignified rice husk pulp(D-RHP) was produced by alkaline delignification of raw rice husk biomass(R-RHB) using 4 mol·L^(-1) alkali solutions(Na OH) in a jacketed glass reactor under specific experimental conditions. D-RHP was bleached using 15% sodium hypochlorite, and the bleached rice husk pulp was coded as B-RHP. Finally,raw suspension of NCC was produced by the acid hydrolysis of B-RHP using 4 mol·L^(-1) sulphuric acid. The raw suspension of NCC was neutralized by a buffer solution and analyzed by TAPPI, FT-IR, XRD, SEM, AFM, and TEM. FT-IR spectra of NCC are different to R-RHB but similar with B-RHP and D-RHP. From XRD results, the crystallinity of NCC was found to be approximately 65%. In AFM analysis particle thicknesses have been confirmed to be in the range of(25 ± 15.14) nm or(27 ± 15.14) nm which is almost the same. From TEM analysis particle dimensions have been confirmed to be in the range of(50 ± 29.38) nm width and(550 ± 302.75) nm length with the aspect ratio ~ 11:1(length/diameter) at a 500 nm scale bar. On the other hand, at a 200 nm scale bar the particle dimensions have been confirmed to be in the range of(35 ± 17) nm width and(275 ± 151.38)nm length with the aspect ratio ~ 8:1. The aspect ratio of individual crystalline domain was determined in TEM analysis which is 10:1(100/10). Therefore the aspect ratios and dimensions of nanoparticles in NCC suspension are almost the same and in nano-meter scale, as confirmed from both AFM and TEM results. The yield of NCC from B-RHP was found to be approximately 95%, and the recovery of cellulose from R-RHB is about 90%.

Model-based estimation of above-ground biomass in the miombo ecoregion of Zambia

Background：Information on above-ground biomass（AGB） is important for managing forest resource use at local levels,land management planning at regional levels,and carbon emissions reporting at national and international levels.In many tropical developing countries,this information may be unreliable or at a scale too coarse for use at local levels.There is a vital need to provide estimates of AGB with quantifiable uncertainty that can facilitate land use management and policy development improvements.Model-based methods provide an efficient framework to estimate AGB.Methods：Using National Forest Inventory（NFI） data for a^1,000,000 ha study area in the miombo ecoregion,Zambia,we estimated AGB using predicted canopy cover,environmental data,disturbance data,and Landsat 8 OLI satellite imagery.We assessed different combinations of these datasets using three models,a semiparametric generalized additive model（GAM） and two nonlinear models（sigmoidal and exponential）,employing a genetic algorithm for variable selection that minimized root mean square prediction error（RMSPE）,calculated through cross-validation.We compared model fit statistics to a null model as a baseline estimation method.Using bootstrap resampling methods,we calculated 95% confidence intervals for each model and compared results to a simple estimate of mean AGB from the NFI ground plot data.Results：Canopy cover,soil moisture,and vegetation indices were consistently selected as predictor variables.The sigmoidal model and the GAM performed similarly;for both models the RMSPE was -36.8 tonnes per hectare（i.e.,57% of the mean）.However,the sigmoidal model was approximately 30% more efficient than the GAM,assessed using bootstrapped variance estimates relative to a null model.After selecting the sigmoidal model,we estimated total AGB for the study area at 64,526,209 tonnes（＋/- 477,730）,with a confidence interval 20 times more precise than a simple designbased estimate.Conclusions：Our findings demonstrate that NFI data may be combined with freely available satellite imagery and soils data to estimate total AGB with quantifiable uncertainty,while also providing spatially explicit AGB maps useful for management,planning,and reporting purposes.

Variation of Soil Microbial Biomass and Enzyme Activities at Different Growth Stages of Rice (Oryza sativa)

A pot experiment was conducted under submerged conditions with hybrid rice Zhenong 7 to study the variation in the soil microbial biomass carbon （Cmic）, soil microbial biomass nitrogen （Nmic）, soil respiration rate, soil microbial metabolic quotient, soil enzyme activities, chlorophyll content, proline content and peroxidase activity （POD） in rice leaf at different growth stages. The soil Cmic, Nmic and soil respiration rate significantly increased at the early stage and then declined during rice growth, but ascended slightly at maturity. However, soil metabolic quotient declined at all the stages. Soil urease activity increased at first and then decreased, while acid phosphatase and dehydrogenase activities descended before ascended and then descended again. Soil urease activity and acid phosphatase activity showed a peak value at the tillering stage about 30 days after rice transplanting, but the peak value of dehydrogenase activity emerged at about 50 days after rice transplanting and the three soil enzymatic activities were significantly different at the different developmental stages. As rice growing, chlorophyll content in rice leaf descended at the early stage then ascended and a peak value appeared at about the 70th after rice transplanting, after that declined drastically, while POD activity increased gradually, but proline content declined gradually. There was a slight relation between rice physiological indices and soil biochemical indices, which indicated that soil biochemical characteristics were affected significantly by rice growth in the interaction system of the rice. soil and microorganisms.

Assessment of tree diversity and above-ground biomass in coffee agroforest dominated tropical landscape of India's Central Western Ghats

The purpose of this study was to quantify the changes in tree diversity and above-ground biomass associated with six land-use types in Kodagu district of India's Western Ghats. We collected data on species richness,composition and above-ground biomass(AGB) of trees,shrubs and herbs from 96 sample plots of 0.1 ha. Totals of83 species from 26 families were recorded across the landuses. Tree species richness, diversity and composition were significantly higher in evergreen forest(EGF) than in other land-uses. Similarly, stem density and basal area were greater in EGF compared to other land-uses. Detrended correspondence analysis(DCA) yielded three distinct groups along the land-use intensities and rainfall gradient on the first and second axes, respectively. The first DCA axis accounted for 45% and second axis for 35% of the total variation in species composition. Together the first two axes accounted for over 2/3 of the variation in species composition across land-use types. Across the land-uses,AGB ranged from 58.6 Mg ha-1 in rubber plantation to327.3 Mg ha-1 in evergreen forest. Our results showed that species diversity and AGB were negatively impacted bythe land-use changes. We found that coffee agroforests resembled natural forest and mixed species plantation in terms of tree diversity and biomass production, suggesting that traditional coffee farms can help to protect tree species, sustain smallholder production and offer opportunities for conservation of biodiversity and climate change mitigation.

Allometric prediction of above-ground biomass of eleven woody tree species in the Sudanian savanna-woodland of West Africa

Allometric models are necessary for estimating biomass in terrestrial ecosystems. Generalized allometric relationship exists for many tropical trees, but species- and region-specific models are often lacking. We developed species-specific allometric models to predict aboveground biomass for 11 native tree species of the Sudanian savanna- woodlands. Diameters at the base and at breast height, with species means ranging respectively from 11 to 28 cm and 9 to 19 cm, and the height of the trees were used as predictor variables. Sampled trees spanned a wide range of sizes including the largest sizes these species can reach. As a response variable, the biomass of the trees was obtained through destructive sampling of 4 754 trees during wood harvesting. We used a stepwise multiple regression analysis with backward elimination procedure to develop models separately predicting, total biomass of the trees, stem biomass, and biomass of branches and twigs. All species- specific regression models relating biomass with measured tree dimen- sions were highly significant （p 〈 0.001）. The biomass of branches and twigs was less predictable compared to stem biomass and total biomass, although their models required fewer predictors and predictor interac- tions. The best-fit equations for total above-ground biomass and stem biomass bad R2 〉 0.70, except for the Acacia species; for branches including twig biomass, R2-values varied from 0.749 for Anogeissus leiocarpa to 0.183 for Acacia macrostachya. The use of these equations in estimating available biomass will avoid destructive sampling, and aid in planning for sustainable use of these species.

Land use and above-ground biomass changes in a mountain ecosystem,northern Thailand

The conversion of forests into agricultural lands is a major cause of deforestation,particularly in the mountain ecosystems of northern Thailand.It results in a rapid loss of biological diversity of both flora and fauna.In addition,the above-ground biomass(AGB),which can be a major source of carbon storage,is also decreased.This study aimed to predict the AGB in Doi Suthep-Pui National Park,Chiang Mai province,based on land-use/land cover(LULC)changes from 2000 to 2030.Landsat-5 TM(2000)and Landsat-8 TM(2015)satellite images were analyzed to predict LULC changes to 2030.Temporary plots(30 m 930 m)were established in each LULC type for AGB analysis;trees with diameters at breast height≥4.5 cm were identified and measured.AGB of all LULC types were analyzed based on specific allometric equations of each type.The results show that area of forest and nonforested areas fluctuated during the study period.Through the first 15 years(2000–2015),5%(2.9 km^2)of forest changed to either agriculture or urban lands,especially mixed deciduous forest and lower montane forest.There was a similar trend in the 2030 prediction,showing the effect of forest fragmentation and the resultant high number of patches.Total AGB tended to decrease over the 30-year period from 12.5 to 10.6 t ha^-1 in the first and second periods,respectively.Deforestation was the main factor influencing the loss of AGB(30.6 t ha^-1)related to LULC changes.Furthermore,habitat loss would be expected to result in decreased biological diversity.Consequently,a management plan should be developed to avoid unsustainable land use changes,which may adversely affect human well-being.

Quantification of Above-Ground Biomass and Carbon Sequestration Potential of Roadside Trees in the Plateau Department of Benin Republic

Roadside trees are effective natural solutions for mitigating climate change. Despite the usefulness of trees to carbon sequestration, there is a dearth of information on the estimation of biomass and carbon stock for roadside trees in the study area. This study aimed to estimate the carbon stock and carbon dioxide equivalent of roadside trees. A complete enumeration of trees was carried out in Kétou, Pobè and Sakété within the communes of the Plateau Department, Bénin Republic. Total height and diameter at breast height were measured from trees along the roads while individual wood density value was obtained from wood density database. The allometric method of biomass estimation was adopted for the research. The results showed that the total estimations for above-ground biomass, carbon stock and carbon equivalent from all the enumerated roadside trees were 154.53 mt, 72.63 mt and 266.55 mt, respectively. The results imply that the roadside trees contain a substantial amount of carbon stock that can contribute to climate change mitigation through carbon sequestration.

Tree Allometry in Tropical Forest of Congo for Carbon Stocks Estimation in Above-Ground Biomass

The research was aimed to estimate the carbon stocks of above-ground biomass (AGB) in Lesiolouna forest in Republic of Congo. The methodology of Allometric equations was used to measure the carbon stock of Lesio-louna tropical rainforest. The research was done with six circular plots each 40 m of diameter, with a distance of 100 m between each plot, depending on the topography of the site of the installation of these plots. The six studied plots are divided in two sites, which are: Iboubikro and Ngambali. Thus, in the six plots, there are three plots in Iboubikro site and three plots in Ngambali site. The results of this study show that the average carbon stock of aboveground biomass (AGB) in six plots was 170.673 t C ha-1. So, the average of carbon stock of aboveground biomass (ABG) in Iboubikro site was 204.693 t C ha-1 and in the Ngambali site was 136.652 t C ha-1. In this forest ecosystem, the high stock of carbon was obtained in Plot 3, which was in Iboubikro site. Plot 3 contains 20 trees and an average DBH of 24.56 cm. However, the lowest carbon stock was obtained in Plot 4, which was in Ngambali site. Also, Plot 4 contains 11 trees and an average DBH of 31.86 cm. The results of this research indicate that, the forests in the study area are an important carbon reservoir, and they can also play a key role in mitigation of climate change.

Estimation of biomass in wheat using random forest regression algorithm and remote sensing data

Wheat biomass can be estimated using appropriate spectral vegetation indices.However,the accuracy of estimation should be further improved for on-farm crop management.Previous studies focused on developing vegetation indices,however limited research exists on modeling algorithms.The emerging Random Forest(RF) machine-learning algorithm is regarded as one of the most precise prediction methods for regression modeling.The objectives of this study were to(1) investigate the applicability of the RF regression algorithm for remotely estimating wheat biomass,(2) test the performance of the RF regression model,and(3) compare the performance of the RF algorithm with support vector regression(SVR) and artificial neural network(ANN) machine-learning algorithms for wheat biomass estimation.Single HJ-CCD images of wheat from test sites in Jiangsu province were obtained during the jointing,booting,and anthesis stages of growth.Fifteen vegetation indices were calculated based on these images.In-situ wheat above-ground dry biomass was measured during the HJ-CCD data acquisition.The results showed that the RF model produced more accurate estimates of wheat biomass than the SVR and ANN models at each stage,and its robustness is as good as SVR but better than ANN.The RF algorithm provides a useful exploratory and predictive tool for estimating wheat biomass on a large scale in Southern China.

Genotypic Differences in Growth and Physiological Responses to Transplanting and Direct Seeding Cultivation in Rice

The field experiments were conducted to investigate the growth and physiological responses of six super hybrid rice combinations to two planting methods, transplanting （TP） and direct seeding （DS） during 2006-2007 and 2007-2008. The 1000-grain weight and number of tillers per plant at the early growth stage, the maximum quantum yield of PSII （Fv/Fm） and transpiration rate （Tr） were higher in DS plants than in TP ones, whereas the grain yield, number of panicles per square meter, seed setting rate, net photosynthetic rate （Po） and stomatal conductance were lower in DS plants. However, little difference was detected in number of grains per panicle, stem （shoot） and leaf weight between the combinations in the two planting methods. The responses of plant growth and physiological traits to planting method differed greatly among the six combinations. In both planting methods, Chouyou 58 and Yongyou 6 had the highest and lowest panicle biomass and Pn, respectively. The higher yield of Chunyou 58 was associated with more numbers of panicles per square meter and grains per panicle in both planting methods. The results indicate that lower grain yield in DS relative to TP is attributed to more excessive tillers at the early stage, lower leaf biomass and photosynthetic rate at the late stage.