scholarly journals Thinning effect on understory community and photosynthetic characteristics in a subtropical Pinus massoniana plantation

2017 ◽  
Vol 47 (8) ◽  
pp. 1104-1115 ◽  
Author(s):  
Chuanpeng Cheng ◽  
Yidong Wang ◽  
Xiaoli Fu ◽  
Mingjie Xu ◽  
Xiaoqin Dai ◽  
...  
Keyword(s):  
Carbon Fixation ◽  
Chlorophyll Concentration ◽  
Basal Area ◽  
Wiener Index ◽  
Pinus Massoniana ◽  
Leaf Length ◽  
Photosynthetic Characteristics ◽  
Leaf Chlorophyll ◽  
Fern Species ◽  
Fixation Capacity

Thinning forest stands changes biotic and abiotic conditions, subsequently altering understory communities including their photosynthetic characteristics. We investigated the effects of thinning (25% basal area decrease) in a subtropical Pinus massoniana Lamb. plantation at two post-thinning times: 0.5 years (PT0.5) and 2.5 years (PT2.5). Thinning (PT0.5 and PT2.5) significantly increased understory density (+104.9% and +142.4%, respectively), aboveground biomass (+191.1% and +239.2%, respectively), the Shannon–Wiener index, and the Pielou index and decreased the Simpson index (p < 0.05). Species richness significantly increased at PT0.5 and decreased at PT2.5 (p < 0.05). Photosynthetic characteristics of new and old leaves of three dominant species (Woodwardia japonica (Linn. f.) Sm., Dryopteris championii (Benth.) C. Chr., and Dicranopteris dichotoma (Thunb.) Bernh.) showed different variations at 0.5 and 2.5 years after thinning, depending on their various adaptive strategies. Generally, thinning improved leaf carbon fixation capacity of these dominant plants (except W. japonica old leaves). Leaf photosynthetic characteristics of these species exhibited some common changes with respect to leaf morphological attributes and chlorophyll content. Thinning increased new-leaf length (or width) and reduced old-leaf chlorophyll b concentration at PT0.5 but reduced new-leaf length, specific leaf area, and all-leaf chlorophyll concentration at PT2.5. In conclusion, thinning is a useful tool for increasing understory abundance and carbon fixation capacity of some fern species.

scholarly journals Tolerance of Prunus Rootstock to Potassium Carbonate-induced Chlorosis

1995 ◽  
Vol 120 (2) ◽  
pp. 283-285 ◽  
Author(s):  
Yan Shi ◽  
D. H. Byrne
Keyword(s):  
Prunus Persica ◽  
Chlorophyll Concentration ◽  
Commercial Fertilizer ◽  
Nutrient Source ◽  
Solution Ph ◽  
Tolerance Level ◽  
Leaf Chlorophyll ◽  
Standardized Screening ◽  
Fe Chlorosis ◽  
Leaf Chlorophyll Concentration

A standardized screening procedure for tolerance to bicarbonate-induced Fe chlorosis using a commercial fertilizer mix (Plantex) as the nutrient source, high solution pH (8.5) and 1.5 m m bicarbonate to simulate a calcareous soil situation was used with a 1 vermiculite:1 perlite (v/v) support media, small pots and topping (pinching back the tops of shoots). The tolerance level of peach [Prunus persica (L.) Batsch] rootstock could be assessed by leaf visual-chlorosis ratings and Spad-502 chlorophyll readings instead of extractable leaf-chlorophyll concentration or plant Fe concentration. Although most of the tolerant genotypes had almond [P. amygdalus (Mill.) D.A. Webb] in their parentage, a few peaches (`Swat', NJ672281007) showed high to moderate levels of tolerance.

scholarly journals Growth and Photosynthetic Response of Two Persimmon Rootstocks (Diospyros kaki and D. virginiana) under Different Salinity Levels

2014 ◽  
Vol 42 (2) ◽  
pp. 386-391 ◽  
Author(s):  
Meral INCESU ◽  
Berken CIMEN ◽  
Turgut YESILOGLU ◽  
Bilge YILMAZ
Keyword(s):  
Gas Exchange ◽  
Leaf Gas Exchange ◽  
Chlorophyll Concentration ◽  
Dry Mass ◽  
Diospyros Kaki ◽  
Gas Exchange Parameters ◽  
Leaf Chlorophyll ◽  
Salinity Levels ◽  
Leaf Chlorophyll Concentration ◽  
Exchange Parameters

Salinity continues to be a major factor in reduced crop productivity and profit in many arid and semiarid regions. Seedlings of Diospyros kaki Thunb. and D. virginiana L. are commonly used as rootstock in persimmon cultivation. In this study we have evaluated the effects of different salinity levels on photosynthetic capacity and plant development of D. kaki and D. virginiana. Salinity was provided by adding 50 mM, 75 mM and 100 mM NaCl to nutrient solution. In order to determine the effects of different salinity levels on plant growth, leaf number, plant height, shoot and root dry mass were recorded. Besides leaf Na, Cl, K and Ca concentrations were determined. Also leaf chlorophyll concentration, chlorophyll fluorescence (Fv’/Fm’) and leaf gas exchange parameters including leaf net photosynthetic rate (PN), stomatal conductance (gS), leaf transpiration rate (E), and CO2 substomatal concentration (Ci) were investigated. Significant decrease of leaf number, shoot length and plant dry mass by increasing salinity levels was observed in both rootstocks. D. virginiana was less affected in terms of plant growth under salinity stress. Leaf chlorophyll concentration reduction was higher in the leaves of D. kaki in comparison to D. virginiana in 100 mM NaCl treatment. By increasing salinity levels PN, gS and E markedly decreased in both rootstocks and D. kaki was more affected from salinity in terms of leaf gas exchange parameters. In addition there was no significant difference but slight decreases were recorded in leaf chlorophyll fluorescences of both rootstocks.

scholarly journals Adaptation, Biometric Traits and Performances of Guayule Lines Grown in Two Mediterranean Environments

Agriculture ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 651
Author(s):  
Leonardo Sulas ◽  
Giuseppe Campesi ◽  
Simone Canu ◽  
Antonio M. Carroni ◽  
Antonio Dore ◽  
...  
Keyword(s):  
Survival Rate ◽  
Chlorophyll Concentration ◽  
Survival Rates ◽  
Photochemical Efficiency ◽  
Plant Survival ◽  
Trunk Diameter ◽  
Leaf Chlorophyll ◽  
Mediterranean Environments ◽  
Affected Plant ◽  
Perennial Shrub

The perennial shrub guayule (Parthenium argentatum A. Gray) has gained interest as a potential source of natural and hypoallergenic rubber in Southern Europe. Although, native to northern Mexico, it is suited to semi-arid and Mediterranean environments. A research study was conducted in Sardinia (Italy) to evaluate adaptation and biometric traits of introduced guayule lines and to determine the contents and yields of rubber and resin obtainable from its aboveground biomass. Seedlings of the accessions AZ-1, AZ-2, P803, and 11591 were field transplanted in 2015 at two locations of southern, and northern Sardinia, respectively, differing for annual precipitation. Plant survival rate, height and width, trunk diameter, leaf chlorophyll concentration and photosystem photochemical efficiency were monitored. Shoots were harvested at 30 months after transplanting and were partitioned into twigs and remaining stems and its rubber and resin contents were determined. Location markedly affected plant survival rates and biometric traits. Dry matter yield of aboveground components as well as contents of rubber and resin and plant rubber and resin yields differed significantly among accessions under comparison. We found that AZ1 and 11591 were the most successful accessions at southern Sardinia site, whereas 11591 was the only accession exhibiting a satisfactory plant survival rate in the northern location.

scholarly journals Quantifying Leaf Chlorophyll Concentration of Sorghum from Hyperspectral Data Using Derivative Calculus and Machine Learning

2020 ◽  
Vol 12 (13) ◽  
pp. 2082 ◽  
Author(s):  
Sourav Bhadra ◽  
Vasit Sagan ◽  
Maitiniyazi Maimaitijiang ◽  
Matthew Maimaitiyiming ◽  
Maria Newcomb ◽  
...  
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Least Squares ◽  
Chlorophyll Concentration ◽  
Feature Space ◽  
Hyperspectral Data ◽  
Leaf Chlorophyll ◽  
Reflectance Factor ◽  
Leaf Level ◽  
Leaf Chlorophyll Concentration

Leaf chlorophyll concentration (LCC) is an important indicator of plant health, vigor, physiological status, productivity, and nutrient deficiencies. Hyperspectral spectroscopy at leaf level has been widely used to estimate LCC accurately and non-destructively. This study utilized leaf-level hyperspectral data with derivative calculus and machine learning to estimate LCC of sorghum. We calculated fractional derivative (FD) orders starting from 0.2 to 2.0 with 0.2 order increments. Additionally, 43 common vegetation indices (VIs) were calculated from leaf spectral reflectance factor to make comparisons with reflectance-based data. Within the modeling pipeline, three feature selection methods were assessed: Pearson’s correlation coefficient (PCC), partial least squares based variable importance in the projection (VIP), and random forest-based mean decrease impurity (MDI). Finally, we used partial least squares regression (PLSR), random forest regression (RFR), support vector regression (SVR), and extreme learning regression (ELR) to estimate the LCC of sorghum. Results showed that: (1) increasing derivative order can show improved model performance until certain order for reflectance-based analysis; however, it is inconclusive to state that a particular order is optimal for estimating LCC of sorghum; (2) VI-based modeling outperformed derivative augmented reflectance factor-based modeling; (3) mean decrease impurity was found effective in selecting sensitive features from large feature space (reflectance-based analysis), whereas simple Pearson’s correlation coefficient worked better with smaller feature space (VI-based analysis); and (4) SVR outperformed all other models within reflectance-based analysis; alternatively, ELR with VIs from original reflectance yielded slightly better results compared to all other models.

scholarly journals Estimation of total leaf area and D leaf area of pineapple from biometric characteristics

2018 ◽  
Vol 40 (6) ◽  
Author(s):  
Marlúcia Pereira dos Santos ◽  
Victor Martins Maia ◽  
Fernanda Soares Oliveira ◽  
Rodinei Facco Pegoraro ◽  
Silvânio Rodrigues dos Santos ◽  
...  
Keyword(s):  
Leaf Area ◽  
Regression Models ◽  
Carbon Fixation ◽  
Pearson Correlation ◽  
Leaf Length ◽  
Total Leaf Area ◽  
Total Leaf ◽  
Pearson Correlation Analysis ◽  
Biometric Measurements ◽  
Non Destructive

Abstract The estimation of pineapple total leaf area by simple, fast and non-destructive methods allow inferences related to carbon fixation estimative, biotic and abiotic damages and correlating positively with yield. The objective was to estimate D leaf area and total leaf area and of ‘Pérola’ pineapple plants from biometric measurements. For this purpose, 125 slips were selected and standardized by weight for planting in pots. Nine months after planting in a greenhouse, the plants were harvested to evaluate the total leaf area of the plant, D leaf area and D leaf length and width using a portable leaf area meter. Pearson correlation analysis was made and it was observed significative positive and strong correlation among the studied variables. Then, regression models were adjusted. It was observed that the D leaf area of ‘Pérola’ pineapple can be estimated from the length and width of this same leaf and the total leaf area can be estimated from the D leaf area.

scholarly journals Overstory Effects on the Understory of Aleppo Pine Plantations—Implications for Ecosystem Restoration

Forests ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 664 ◽  
Author(s):  
Patrizia Tartarino ◽  
Roberto Greco ◽  
Joaquim S. Silva
Keyword(s):  
Plant Density ◽  
Land Reclamation ◽  
Pinus Halepensis ◽  
Canopy Cover ◽  
Basal Area ◽  
Ecosystem Restoration ◽  
Wiener Index ◽  
Aleppo Pine ◽  
Pine Plantations ◽  
Mediterranean Countries

At the end of the 19th century and along the first half of the 20th century, public policies in Mediterranean countries and elsewhere in Europe strongly promoted pine afforestation for land reclamation and wood production. In many cases, the transition to native forests, more resilient and more diverse, was also foreseen. This study aims to find the overstory characteristics that are best related to the understory of Aleppo pine (Pinus halepensis) plantations, to assist ecosystem restoration goals. We installed 33 circular plots in mature Aleppo pine plantations located in the southeastern Salento peninsula, Apulia, Italy. We measured overstory characteristics and the corresponding understory on these plots. We assessed the effects of overstory variables on understory development (plant density, plant height, and the Magini regeneration index) and diversity (species richness and the Shannon–Wiener index) using linear mixed models (LMM). Understory development and diversity were positively correlated with the Hart–Becking spacing index and negatively correlated with basal area and canopy cover, the three overstory variables that best explained variance. We used polynomial fitting and the subsequent derivation of these functions to determine the values of the Hart–Becking index and of the canopy cover that corresponded to the maximum development (33.7% and 84.6%, respectively) and diversity (32.6% and 86.5%, respectively) of the understory. Redundancy analysis (RDA) showed that late-successional species, including Quercus coccifera, were associated with higher levels of understory development and stand spacing. These results may assist in the restoration of native ecosystems in Aleppo pine plantations installed in similar ecological conditions.

scholarly journals Relationship between Flag Leaf Characteristics and Main Yield Components in Oat (Avena sativa L.)

2019 ◽  
Vol 76 (1) ◽  
pp. 71
Author(s):  
Ionuṭ RACZ ◽  
Rozalia KADAR ◽  
Sorin VȂTCĂ ◽  
Ioana Virginia BERINDEAN ◽  
Adrian CECLAN ◽  
...  
Keyword(s):  
Grain Yield ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Avena Sativa ◽  
Yield Components ◽  
Flag Leaf ◽  
Chlorophyll Concentration ◽  
Area Index ◽  
Leaf Chlorophyll ◽  
Leaf Chlorophyll Concentration

The objective of this study was to investigate relationships between leaf area index, leaf chlorophyll concentration, yield components and grain yield in oat (Avena sativa L.). Ten oat varieties were analyzed in field conditions regarding those traits. Flag leaf chlorophyll concentration range between 451.51 and 747.79 units of μmol of chlorophyll per m2. Also, leaf area index range between 13.68 to 32.84 cm2. Significant correlation indices were highlighted between yield components and leaf area index, yield/yield components and chlorophyll concentration of flag leaf.

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