scholarly journals Methyl Salicylate and Sesquiterpene Emissions Are Indicative for Aphid Infestation on Scots Pine

Forests ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 573
Author(s):  
Minna Kivimäenpää ◽  
Aishat B. Babalola ◽  
Jorma Joutsensaari ◽  
Jarmo K. Holopainen
Keyword(s):  
Scots Pine ◽  
Methyl Salicylate ◽  
Plant Pathogens ◽  
Early Stage ◽  
Emission Rates ◽  
Aphid Infestation ◽  
Biotic Stresses ◽  
Aphid Density ◽  
Pine Trees ◽  
Non Destructive

Biotic stresses on forest trees are caused by various pest insects and plant pathogens. Attack by these parasites is known to induce the emissions of various biogenic volatile organic compounds (BVOCs), and the profile of these emissions often differs between infested and healthy plants. This difference in emission profile can be used for the non-destructive early-stage diagnosis of the stressor organism. We studied how phloem feeding by a large pine aphid (Cinara pinea Mordvilko) on the branch bark of Scots pine (Pinus sylvestris L.) affects BVOC emissions compared to those of healthy plants in two experiments. We found that in aphid-infested plants, methyl salicylate (MeSA) emissions significantly increased, and the emission rates were dependent on aphid density on the studied branch. Aphid infestation did not significantly affect total monoterpene emission, while the emissions of total sesquiterpenes were substantially higher in aphid-infested saplings than in uninfested plants. Sesquiterpene (E, E)-α-farnesene was emitted at increased rates in both experiments, and the aphid alarm pheromone sesquiterpene (E)-β-farnesene, only in the experiment with higher aphid pressure. We conclude that the rapid increase in MeSA emissions is the most reliable indicator of aphid infestation in pine trees together with (E, E)-α-farnesene.

scholarly journals Semi-Automatic Method for Early Detection of Xylella fastidiosa in Olive Trees Using UAV Multispectral Imagery and Geostatistical-Discriminant Analysis

2020 ◽  
Vol 13 (1) ◽  
pp. 14
Author(s):  
Annamaria Castrignanò ◽  
Antonella Belmonte ◽  
Ilaria Antelmi ◽  
Ruggiero Quarto ◽  
Francesco Quarto ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Early Detection ◽  
Plant Pathogens ◽  
Early Stage ◽  
Xylella Fastidiosa ◽  
Mediterranean Countries ◽  
Parametric Classification ◽  
Aerial Vehicle ◽  
Olive Groves ◽  
Olive Trees

Xylella fastidiosa subsp. pauca (Xfp) is one of the most dangerous plant pathogens in the world. Identified in 2013 in olive trees in south–eastern Italy, it is spreading to the Mediterranean countries. The bacterium is transmitted by insects that feed on sap, and causes rapid wilting in olive trees. The paper explores the use of Unmanned Aerial Vehicle (UAV) in combination with a multispectral radiometer for early detection of infection. The study was carried out in three olive groves in the Apulia region (Italy) and involved four drone flights from 2017 to 2019. To classify Xfp severity level in olive trees at an early stage, a combined method of geostatistics and discriminant analysis was implemented. The results of cross-validation for the non-parametric classification method were of overall accuracy = 0.69, mean error rate = 0.31, and for the early detection class of accuracy 0.77 and misclassification probability 0.23. The results are promising and encourage the application of UAV technology for the early detection of Xfp infection.

scholarly journals Early detection of pine wilt disease in Pinus tabuliformis in North China using a field portable spectrometer and UAV-based hyperspectral imagery

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Run Yu ◽  
Lili Ren ◽  
Youqing Luo
Keyword(s):  
Early Stage ◽  
Vegetation Indices ◽  
Pine Wilt Disease ◽  
Wilt Disease ◽  
Pinus Tabulaeformis ◽  
Pine Tree ◽  
Preventative Measures ◽  
Pine Wilt ◽  
Pine Trees ◽  
Airborne Vehicle

Abstract Background Pine wilt disease (PWD) is a major ecological concern in China that has caused severe damage to millions of Chinese pines (Pinus tabulaeformis). To control the spread of PWD, it is necessary to develop an effective approach to detect its presence in the early stage of infection. One potential solution is the use of Unmanned Airborne Vehicle (UAV) based hyperspectral images (HIs). UAV-based HIs have high spatial and spectral resolution and can gather data rapidly, potentially enabling the effective monitoring of large forests. Despite this, few studies examine the feasibility of HI data use in assessing the stage and severity of PWD infection in Chinese pine. Method To fill this gap, we used a Random Forest (RF) algorithm to estimate the stage of PWD infection of trees sampled using UAV-based HI data and ground-based data (data directly collected from trees in the field). We compared relative accuracy of each of these data collection methods. We built our RF model using vegetation indices (VIs), red edge parameters (REPs), moisture indices (MIs), and their combination. Results We report several key results. For ground data, the model that combined all parameters (OA: 80.17%, Kappa: 0.73) performed better than VIs (OA: 75.21%, Kappa: 0.66), REPs (OA: 79.34%, Kappa: 0.67), and MIs (OA: 74.38%, Kappa: 0.65) in predicting the PWD stage of individual pine tree infection. REPs had the highest accuracy (OA: 80.33%, Kappa: 0.58) in distinguishing trees at the early stage of PWD from healthy trees. UAV-based HI data yielded similar results: the model combined VIs, REPs and MIs (OA: 74.38%, Kappa: 0.66) exhibited the highest accuracy in estimating the PWD stage of sampled trees, and REPs performed best in distinguishing healthy trees from trees at early stage of PWD (OA: 71.67%, Kappa: 0.40). Conclusion Overall, our results confirm the validity of using HI data to identify pine trees infected with PWD in its early stage, although its accuracy must be improved before widespread use is practical. We also show UAV-based data PWD classifications are less accurate but comparable to those of ground-based data. We believe that these results can be used to improve preventative measures in the control of PWD.

scholarly journals Interacting effects of insect and ungulate herbivory on Scots pine growth

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Michelle Nordkvist ◽  
Maartje J. Klapwijk ◽  
La rs Edenius ◽  
Christer Björkman
Keyword(s):  
Plant Growth ◽  
Scots Pine ◽  
Growth Response ◽  
Insect Herbivory ◽  
Additive Effects ◽  
Significant Interaction Effect ◽  
Ungulate Herbivory ◽  
Pine Trees ◽  
Multiple Species ◽  
Species Specific

AbstractMost plants are subjected to damage from multiple species of herbivores, and the combined impact on plant growth can be non-additive. Since plant response to herbivores tends to be species specific, and change with repeated damage, the outcome likely depend on the sequence and number of attacks. There is a high likelihood of non-additive effects on plant growth by damage from mammals and insects, as mammalian herbivory can alter insect herbivore damage levels, yet few studies have explored this. We report the growth response of young Scots pine trees to sequential mammal and insect herbivory, varying the sequence and number of damage events, using an ungulate-pine-sawfly system. Combined sawfly and ungulate herbivory had both additive and non-additive effects on pine growth—the growth response depended on the combination of ungulate browsing and sawfly defoliation (significant interaction effect). Repeated sawfly herbivory reduced growth (compared to single defoliation) on un-browsed trees. However, on browsed trees, depending on when sawfly defoliation was combined with browsing, trees exposed to repeated sawfly herbivory had both higher, lower and the same growth as trees exposed to a single defoliation event. We conclude that the sequence of attacks by multiple herbivores determine plant growth response.

Freeze-preservation of buds from Scots pine trees

1991 ◽  
Vol 27 (1) ◽  
pp. 89-93 ◽  
Author(s):  
Tero Kuoksa ◽  
Anja Hohtola
Keyword(s):  
Scots Pine ◽  
Pine Trees

scholarly journals Scots pine (Pinus sylvestris) dynamics in the Welsh Marches during the mid to late-Holocene

The Holocene ◽  
2021 ◽  
pp. 095968362199465
Author(s):  
Dael Sassoon ◽  
William J Fletcher ◽  
Alastair Hotchkiss ◽  
Fern Owen ◽  
Liting Feng
Keyword(s):  
Pinus Sylvestris ◽  
Scots Pine ◽  
Late Holocene ◽  
British Isles ◽  
Loss On Ignition ◽  
Peat Core ◽  
New Information ◽  
Pine Trees ◽  
Pollen Records

Around 4000 cal yr BP, Scots pine ( Pinus sylvestris) suffered a widespread demise across the British Isles. This paper presents new information about P. sylvestris populations found in the Welsh Marches (western central Britain), for which the long-term history and origins are poorly known. Two new pollen records were produced from the Lin Can Moss ombrotrophic bog (LM18) and the Breidden Hill pond (BH18). The LM18 peat core is supported by loss-on-ignition, humification analysis and radiocarbon dating. Lead concentrations were used to provide an estimated timeframe for the recent BH18 record. In contrast to many other Holocene pollen records from the British Isles, analysis of LM18 reveals that Scots pine grains were deposited continuously between c. 6900–300 cal yr BP, at frequencies of 0.3–5.4%. It is possible that individual Scots pine trees persisted through the wider demise on thin soils of steep drought-prone crags of hills or the fringes of lowland bogs in the Welsh Marches. At BH18, the record indicates a transition from broadleaved to mixed woodland, including conifer species introduced around AD 1850 including Picea and Pinus. The insights from BH18 suggest that the current populations may largely be the result of planting. Comparison of the LM18 findings with other regional pollen records highlights consistent patterns, including a Mid-Holocene maximum (ca. 7000 cal yr BP), long-term persistence at low pollen percentages and a Late-Holocene minimum (ca. 3000 cal yr BP). These distinctive trends encourage further studies on refugial areas for Scots pine in this region and elsewhere.

scholarly journals Seasonal variation of mono- and sesquiterpene emission rates of Scots pine

2006 ◽  
Vol 3 (1) ◽  
pp. 93-101 ◽  
Author(s):  
H. Hakola ◽  
V. Tarvainen ◽  
J. Bäck ◽  
H. Ranta ◽  
B. Bonn ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
Scots Pine ◽  
Early Summer ◽  
Emission Rates ◽  
High Concentration ◽  
Temperature Dependent ◽  
Emission Pattern ◽  
Defensive Role ◽  
Monoterpene Emission

Abstract. The seasonal variation of mono-and sesquiterpene emission rates of Scots pine was measured from April to October in 2004. The emission rates were measured daily in the afternoons with the exception of weekends. Emissions were measured from two branches; one of them was debudded in May (branch A), while the other was allowed to grow new needles (branch B). The monoterpene emission pattern remained almost constant throughout the measurement period, Δ3-carene being the dominant monoterpene (50-70% of the VOC emission). The standard monoterpene emission potential (30°C) was highest during early summer in June (the average of the two branches 1.35 µg g-1h-1) and lowest during early autumn in September (the average of the two branches 0.20 µg g-1h-1. The monoterpene emission potential of branch A remained low also during October, whereas the emission potential of branch B was very high in October. The sesquiterpenes were mainly emitted during mid summer, the dominant sesquiterpene being β-caryophyllene. Branch A had a higher sesquiterpene emission potential than branch B and the emission maximum occurred concomitant with the high concentration of airborne pathogen spores suggesting a potential defensive role of the sesquiterpene emissions. The sesquiterpene emissions were well correlated with linalool and 1,8-cineol emissions, but not with monoterpenes. Sesquiterpene and 1,8-cineol emissions were equally well described by the temperature dependent and the temperature and light dependent algorithms. This is due to the saturation of the light algorithm as the measurements were always conducted during high light conditions.

scholarly journals CHRONIC IRRADIATION OF SCOTS PINE TREES (PINUS SYLVESTRIS) IN THE CHERNOBYL EXCLUSION ZONE: DOSIMETRY AND RADIOBIOLOGICAL EFFECTS

2011 ◽  
Vol 101 (4) ◽  
pp. 393-408 ◽  
Author(s):  
Vasyl I. Yoschenko ◽  
Valery A. Kashparov ◽  
Maxim D. Melnychuk ◽  
Svjatoslav E. Levchuk ◽  
Yulia O. Bondar ◽  
...  
Keyword(s):  
Pinus Sylvestris ◽  
Scots Pine ◽  
Chronic Irradiation ◽  
Exclusion Zone ◽  
Pine Trees ◽  
Radiobiological Effects

Prediction of Stilbene Content from Heartwood Increment Cores of Scots Pine Using near Infrared Spectroscopy Methodology

2016 ◽  
Vol 24 (6) ◽  
pp. 517-528 ◽  
Author(s):  
Susanna Pulkka ◽  
Vincent Segura ◽  
Anni Harju ◽  
Tarja Tapanila ◽  
Johanna Tanner ◽  
...  
Keyword(s):  
Scots Pine ◽  
High Throughput ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Tree Breeding ◽  
Decay Resistance ◽  
Increment Core ◽  
Automatic Selection ◽  
Non Destructive ◽  
Selection Of

High-throughput and non-destructive methods for quantifying the content of the stilbene compounds of Scots pine ( Pinus sylvestris L.) heartwood are needed in the breeding for decay resistance of heartwood timber. In this study, near infrared (NIR) spectroscopy calibrations were developed for a large collection of solid heartwood increment core samples in order to predict the amount of the stilbene pinosylvin (PS), its monomethyl ether (PSM) and their sum (STB). The resulting models presented quite accurate predictions in an independent validation set with R2V values ranging between 0.79 and 0.91. The accuracy of the models strongly depended on the chemical being calibrated, with the lowest accuracy for PS, intermediate accuracy for PSM and highest accuracy for STB. The effect of collecting one, two or more (up to five) spectra per sample on the calibration models was studied and it was found that averaging multiple spectra yielded better accuracy as it may account for the heterogeneity of wood along the increment core within and between rings. Several statistical pretreatments of the spectra were tested and an automatic selection of wavenumbers prior to calibration. Without the automatic selection of wavenumbers, a first derivative of normalised spectra yielded the best accuracies, whereas after the automatic selection of wavenumbers, no particular statistical pretreatment appeared to yield better results than any other. Finally, the automatic selection of wavenumbers slightly improved the accuracy of the models for all traits. These results demonstrate the potential of NIR spectroscopy as a high-throughput and non-destructive phenotyping technique in tree breeding for the improvement of decay resistance in heartwood timber.

scholarly journals Chemodiversity of a Scots pine stand and implications for terpene air concentrations

2012 ◽  
Vol 9 (2) ◽  
pp. 689-702 ◽  
Author(s):  
J. Bäck ◽  
J. Aalto ◽  
M. Henriksson ◽  
H. Hakola ◽  
Q. He ◽  
...  
Keyword(s):  
Scots Pine ◽  
Atmospheric Chemistry ◽  
Bimodal Distribution ◽  
Atmospheric Modeling ◽  
Emission Data ◽  
Intermediate Group ◽  
Pine Trees ◽  
Seed Origin ◽  
Atmospheric Concentrations ◽  
Air Concentrations

Abstract. Atmospheric chemistry in background areas is strongly influenced by natural vegetation. Coniferous forests are known to produce large quantities of volatile vapors, especially terpenes. These compounds are reactive in the atmosphere, and contribute to the formation and growth of atmospheric new particles. Our aim was to analyze the variability of mono- and sesquiterpene emissions between Scots pine trees, in order to clarify the potential errors caused by using emission data obtained from only a few trees in atmospheric chemistry models. We also aimed at testing if stand history and seed origin has an influence on the chemotypic diversity. The inherited, chemotypic variability in mono- and sesquiterpene emission was studied in a seemingly homogeneous 48 yr-old stand in Southern Finland, where two areas differing in their stand regeneration history could be distinguished. Sampling was conducted in August 2009. Terpene concentrations in the air had been measured at the same site for seven years prior to branch sampling for chemotypes. Two main compounds, α-pinene and Δ3-carene formed together 40–97% of the monoterpene proportions in both the branch emissions and in the air concentrations. The data showed a bimodal distribution in emission composition, in particular in Δ3-carene emission within the studied population. 10% of the trees emitted mainly α-pinene and no Δ3-carene at all, whereas 20% of the trees where characterized as high Δ3-carene emitters (Δ3-carene forming >80% of total emitted monoterpene spectrum). An intermediate group of trees emitted equal amounts of both α-pinene and Δ3-carene. The emission pattern of trees at the area established using seeding as the artificial regeneration method differed from the naturally regenerated or planted trees, being mainly high Δ3-carene emitters. Some differences were also seen in e.g. camphene and limonene emissions between chemotypes, but sesquiterpene emissions did not differ significantly between trees. The atmospheric concentrations at the site were found to reflect the species and/or chemodiversity rather than the emissions measured from any single tree, and were strongly dominated by α-pinene. We also tested the effect of chemodiversity on modeled monoterpene concentrations at the site and found out that since it significantly influences the distributions and hence the chemical reactions in the atmosphere, it should be taken into account in atmospheric modeling.

scholarly journals CARS Algorithm-Based Detection of Wheat Moisture Content before Harvest

Symmetry ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 115
Author(s):  
Hong Ji ◽  
Wanzhang Wang ◽  
Dongfeng Chong ◽  
Boyang Zhang
Keyword(s):  
Moisture Content ◽  
Regression Model ◽  
Regression Models ◽  
Partial Least Squares Regression ◽  
Early Stage ◽  
Least Squares Regression ◽  
Calibration Sample ◽  
Non Destructive ◽  
Plsr Model ◽  
Variable Subset

To rapidly detect the wheat moisture content (WMC) without harm to the wheat and before harvest, this paper measured wheat and panicle moisture content (PMC) and the corresponding spectral reflectance of panicle before harvest at the Beijing Tongzhou experimental station of China Agricultural University. Firstly, we used correlation analysis to determine the optimal regression model of WMC and PMC. Secondly, we derived the spectral sensitive band of PMC before filtering the redundant variables competitive adaptive reweighted sampling (CARS) to select the variable subset with the least error. Finally, partial least squares regression (PLSR) was used to build and analyze the prediction model of PMC. At the early stage of wheat harvest, a high correlation existed between WMC and PMC. Among all regression models such as exponential, univariate linear, polynomial models, and the power function regression model, the logarithm regression model was the best. The determination coefficients of the modeling sample were: R2 = 0.9284, the significance F = 362.957, the determination coefficient of calibration sample R2v = 0.987, the root mean square error RMSEv = 3.859, and the relative error REv = 7.532. Within the range of 350–2500 nm, bands of 728–907 nm, 1407–1809 nm, and 1940–2459 nm had a correlation coefficient of PMC and wavelength reflectivity higher than 0.6. This paper used the CARS algorithm to optimize the variables and obtained the best variable subset, which included 30 wavelength variables. The PLSR model was established based on 30 variables optimized by the CARS algorithm. Compared with the all-sensitive band, which had 1103 variables, the PLSR model not only reduced the number of variables by 1073, but also had a higher accuracy in terms of prediction. The results showed that: RMSEC = 0.9301, R2c = 0.995, RMSEP = 2.676, R2p = 0.945, and RPD = 3.362, indicating that the CARS algorithm could effectively remove the variables of spectral redundant information. The CARS algorithm provided a new way of thinking for the non-destructive and rapid detection of WMC before harvest.

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