Foliage Area Research Articles

Новый подход к оценке площади поверхности хвои пихты сибирской

Новый подход к оценке площади поверхности хвои пихты сибирской

Leaf area index estimation using top-of-canopy airborne RGB images

Leaf Area Index (LAI) is one of the most important biophysical properties of a crop, used in detecting long-term water stress, estimating biomass, and identifying crop growth stage. Remote sensing based LAI estimation techniques perform well for early growth stages but tend to produce high error during the crop reproductive stage due to canopy closure. Moreover, estimation of the true LAI from individual leaf measurements remains a challenge. Consequently, two alternate methods have been developed and compared for estimating the LAI of a maize crop using top-of-canopy RGB images collected throughout the growing season using a hexacopter. Both methods used the RGB images to estimate the canopy height and the green-canopy cover together with a ‘vertical leaf area distribution factor’ (VLADF) from allometric relations (using crop height from RBG images and days after sowing). The first method used an empirical approach to estimate the LAI from training a linear function of the above inputs to Licor canopy analyser values of LAI. The method was trialled for a research farm located in a semi-arid area of southern peninsula India and found to have validation results with an R2 of 0.84 and RMSE of 0.36 for the unused portion of the Rabi (post-monsoon) season data of 2018–19, and R2 of 0.77 and RMSE of 0.45 for the Rabi 2019–20 season data when compared with Licor LAI values. While seemingly acceptable, the Licor canopy analyser gives a foliage area index and so the accuracy of this model was very low (R2 of 0.56 and RMSE of 1.34) when evaluated with true LAI from manual measurements of the leaf area. Consequently, a refinement was introduced using only VLADF, green-canopy cover estimates from the RBG images, and a field measured top leaf angle. The output derived from this conceptual model had an R2 of ~0.6 and RMSE of 0.73 when compared with the true LAI values. Importantly, the LAI from this conceptual model was found to be unaffected by canopy closure during the reproductive stage of the crop.

Forest site conditions and the threat for insect outbreaks in the Scots pine stands of Polissya

Abstract Scots pine (Pinus sylvestris L.) is the most spread forest tree species in Polissya and the most damaged by foliage browsing and stem insects. The aim of this study was to reveal the changes in the distribution of different forest site conditions for 2010–2019 in Scots pine forests of the selected forestry enterprises of Polissya and possible consequences for the spread of foliage browsing insects. Database of Production Association ‘Ukrderzhlisproekt’ (by 2010 and 2019) was analysed for five State Forest Enterprises (FE) that are located in the Central (Zhytomyr Region) and Western (Rivne and Volyn Regions) Polissya, where the large scale outbreaks of stem pests were registered last decade. The types of forest site conditions were designated in accordance with the Ukrainian typology. Distribution of the forest area by trophotops and hygrotops was evaluated for the forest-covered area, for Scots pine stands, and for pure Scots pine stands in 2010 and in 2019. For 2010–2019, the area of all Scots pine forests and its proportion in the forest-covered area has significantly decreased in the most of analysed forest enterprises. The change for 2010–2019 in the distribution both by the tropho-tops and by hygrotops of the entire forest-covered area, the area of all Scots pine forests and pure pine forests is not statistically significant. However, in assessment year 2019, the proportion of stands in the moist types of forest site conditions slightly increased. It may be the result of the stands’ mortality in the driest sites after an outbreak of bark beetles. A greater decrease in the proportion of Scots pine forest area in the dry poor, fresh poor, and dry relatively poor forest site conditions was found in the western direction. Therefore, the noted decrease in the foci areas of foliage browsing insects in Polissya in 2010–2012 compared to the 2000–2002 could be associated with a decrease in the most preferred stands, namely the poorest and driest types of forest site conditions.

Silver birch aboveground biomass allocation pattern, stem and foliage traits with regard to intraspecific crown competition

Abstract In the conditions of Central Europe, silver birch (Betula pendula Roth) has so far not been an important species for commercial purposes but might be relevant from ecological point of view. For instance, prompt succession by birch and other pioneer tree species at large-scale post-disturbance areas is necessary to compensate for previous carbon losses by natural disasters. Therefore, our attention was focused on 14-year-old birch trees growing at the wind-thrown area in the High Tatra Mts. (northern Slovakia). We sampled aboveground biomass of 20 silver birch trees representing four classes of crown competition: 0 – competition free crowns, 1 – crowns under mild competition, 2 – crowns under moderate competition, 3 – crowns under severe competition. We studied biomass allocated to stems, branches and foliage, and basic properties of stems and foliage. The crown-competition free birches were nearly 13 m high, and their aboveground tree biomass was 150 kg. The biomass of birches under severe competition was five times lower. Crown competition modified biomass ratios of foliage to branch as well as of branch to stem. Our results showed that birches under severe competition stress invest more in height than in diameter. At the same time, crown competition modified foliage weight and specific leaf area (SLA), which was clear mostly in the upper part of the crowns. However, foliage area was influenced by crown competition only to a negligible extent. Our main finding is that foliage position (upper, middle or lower third of crown) affected foliage properties more than intraspecific crown competition. Finally, we pointed out that silver birch is a rather productive species that is not ecologically demanding. Therefore, it might be a prospective tree species under the ongoing climate change and the present period of intensification in renewable resources utilisation.

Biomass Allocation into Woody Parts and Foliage in Young Common Aspen (Populus tremula L.)—Trees and a Stand-Level Study in the Western Carpathians

Our research of common aspen (Populus tremula L.) focused on the forested mountainous area in central Slovakia. Forest stands (specifically 27 plots from 9 sites) with ages between 2 and 15 years were included in measurements and sampling. Whole tree biomass of aspen individuals was destructively sampled, separated into tree components (leaves, branches, stem, and roots), and then dried and weighed. Subsamples of fresh leaves from three crown parts (upper, middle, and lower) were scanned, dried, and weighed. Allometric biomass models with stem base diameter as an independent variable were derived for individual tree components. Basic foliage traits, i.e., leaf mass, leaf area, and specific leaf area, were modelled with regard to tree size and leaf position within the crown. Moreover, biomass stock of the woody parts and foliage as well as the leaf area index were modelled using mean stand diameter as an independent variable. Foliage traits changed with both tree size and crown part. Biomass models showed that foliage contribution to total tree biomass decreased with tree size. The total foliage area of a tree increased with tree size, reaching its maximum value of about 12 m2 for a tree with a diameter of 120 mm. Leaf area index increased with mean stand diameter, reaching a maximum value of 13.5 m2 m−2. Since no data for biomass allocation for common aspen had been available at either the tree or stand levels, our findings might serve for both theoretical (e.g., modelling of growth processes) and practical (forestry and agro-forestry stakeholders) purposes.

Rising CO2 in the field does not offset warming or drought constraints on leaf growth of a C3 forage

AbstractThe regrowth of a C3 forage Stylosanthes capitata in a rain-fed field provided the weekly data collection in the southeast of Brazil during a heat event in autumn. A system named Trop-T-FACE simulated the free-air carbon dioxide enrichment and the enhanced temperature in four climatic regimes: current atmospheric conditions (Control), CO2 enrichment (600 ppm, eC), warming (2 °C above ambient canopy temperature, eT), and a combination of eC + eT. The area and biomass of foliage per shoot decreased, and the number of flowers per shoot and flowered ramification increased under single eC treatment besides the increment in palisade parenchyma of leaves. Increased investment in flowering in eC occurred notably when the soil water content was higher than 0.30 m3 m–3. Single eT treatment also impaired the area or biomass of foliage production per shoot, raised the shoot mortality, and promoted the increment of the spongy leaf parenchyma. There was some mitigation of the adverse effects of foliage production of eT or eC in eC + eT, but under this combined treatment, the shoot mortality also increased. Changes in leaf tissues under eC or eT or some mitigation of adverse effects in eC + eT did not offset the constraints on leaf growth per shoot. The harmful impact on foliage production by eC, eT, or eC + eT under rain-fed conditions indicated no advantages for feeding the livestock with the C3 forage S. capitata in expected climate change under field conditions.

“Diminishing Returns” in the Scaling between Leaf Area and Twig Size in Three Forest Communities Along an Elevation Gradient of Wuyi Mountain, China

Background and aims: The “diminishing returns” hypothesis postulates that the scaling exponent governing the lamina area versus lamina mass scaling relationships has, on average, a numerical value less than one. Theoretically, a similar scaling relationship may exist at the twig level. However, this possibility has not been explored empirically. Methods: We tested both hypotheses by measuring the lamina area and mass, petiole mass of individual leaves, and the total foliage area and stem mass of individual current-year shoots (twigs) of 64 woody species growing in three characteristic forest community types: (1) Evergreen broad-leaved, (2) mixed coniferous and broad-leaved, and (3) deciduous. Key results: The results demonstrate that lamina area vs. mass and lamina area vs. petiole mass differ significantly among the three forest types at both the individual leaf and twig levels. Nevertheless, the scaling exponents of lamina area vs. mass were <1.0 in each of the three community types, as were the corresponding exponents for lamina area vs. petiole mass, both within and across the three community types. Similar trends were observed at the individual twig level. The numerical values of the scaling exponent for lamina area vs. petiole mass and total foliage area vs. stem mass per twig decreased with increased elevation. Conclusions: These data support the “diminishing returns” hypothesis at both the individual leaf level and at the individual twig level, phenomena that can inform future inquiries into the mechanistic basis of biomass allocation patterns to physiological (leaf) and mechanical (stem) plant organs.

Comparing direct and indirect leaf area measurements for Scots pine and Norway spruce plantations in Sweden

The area of foliage absorbing solar radiation is often expressed as leaf area index (LAI). In this study, specific leaf area (SLA), leaf area at tree level (LA) and LAI at stand level were measured on eight experimental plots of Norway spruce (Picea abies) and Scots pine (Pinus sylvestris), together with tree and stand measurements from biomass harvest. Both projected area and half total surface area were measured, and a model of the relationship between the units was constructed. SLA was larger for pine (61.62 cm2 g−1) compared to spruce (50.2 cm2 g−1) and showed a trend of decreasing higher up in the crown. Leaf area was significantly higher for Norway spruce compared to Scots pine on both tree and stand level. Models were constructed using diameter at breast height, tree height and stand basal area to estimate LA. The models were general site-independent models that can be used for easy estimations of single tree leaf area. Indirect measurement of LAI (LAIe) was shown to underestimate LAI with on average 30–73% depending on species and measurement technique. Using the extensive data collected, conversion models were constructed for estimating LAI from LAIe together with basal area, stem number and stand height. These species-specific conversion models will allow for more accurate estimations of LAI that can be used in mechanistic models of forest growth and for future estimates of LAI from remote sensing data.

Shading on Yield and Quality of Lettuce Cultivars in Semiarid Conditions

Lettuce is a crop originating from temperate climate, and for this reason, when cultivated in semiarid region, characterized by high luminosity and temperature, major losses in productivity and quality occur. The objective of this work was to evaluate the influence of different levels of shade on yield and quality of lettuce cultivars in semiarid conditions. The experiment was conducted under field conditions at the Human and Agricultural Sciences Center at State University of Paraiba, Brazil, in randomized blocks with parcels divided into 4 × 4 factorial space, and four repetitions. The parcels received different shading levels (0, 30, 50 and 70%) with black polypropylene screen and sub parcels by lettuce cultivars: ‘Americana Irene’, ‘White Boston’, ‘Regina de Verão’ and ‘Green Salad Bowl’. The shading promoted higher performance in height, stem diameter, root length, pH and dry mass of lettuce plants when compared to those grown in the open-air, being the shading of 70% the more efficient. The ‘Americana Irene’ cultivar was distinguished in terms of plant height, foliage area, leaves dry mass and soluble solids, independently from the cultivation environment. With the shading, this cultivar improved the aerial shoot-root ratio and root dry mass.

Large leaves in warm, moist environments confer an advantage in seedling light interception efficiency.

Leaf size varies conspicuously along environmental gradients. Small leaves help plants cope with drought and frost, because of the effect of leaf size on boundary layer conductance; it is less clear what advantage large leaves confer in benign environments. We asked if large leaves give species of warm climates an advantage in seedling light interception efficiency over small-leaved species from colder environments. We measured seedling leaf, architectural and biomass distribution traits of 18 New Zealand temperate rainforest evergreens; we then used a 3-D digitiser and the Yplant program to model leaf area display and light interception. Species associated with mild climates on average had larger leaves and larger specific leaf areas (SLA) than those from cold climates, and displayed larger effective foliage areas per unit of aboveground biomass, indicating higher light interception efficiency at whole-plant level. This reflected differences in total foliage area, rather than in self-shading. Our findings advance the understanding of leaf size by showing that large leaves enable seedlings of species with highly conductive (but frost-sensitive) xylem to deploy large foliage areas without increasing self-shading. Leaf size variation along temperature gradients in humid forests may therefore reflect a trade-off between seedling light interception efficiency and susceptibility to frost.

Effect of nitrogen fertilization on structure and tillering dynamics of Piata palisade grass during the deferment period

Nitrogen fertilization can increase the appearance of new tillers, which can improve the structure of deferred sward, since the deferral period is not long. Thus, the objective of this study was to estimate the effects of nitrogen fertilization on structure and tillering dynamics of Piata palisade grass (Brachiaria brizantha cv. Piata) during deferment. We evaluated three nitrogen fertilization levels (none - 0 kg ha -1; medium - 75 kg ha -1; and high - 150 kg ha -1) associated with deferment periods (1, 30, 60, 90, and 120 days). The experimental design was set in completely randomised blocks in a split-plot arrangement, with three replications. The deferment period influenced foliage area index quadratically (p < 0.01) at all fertilization levels. The improvement in nitrogen fertilization levels increased light interception and reduced the foliage angle, but it did not affect tillering dynamics of Piata palisade grass during the deferment period. Appearance and mortality rates, the balance between tiller appearance and mortality and the stability index of the population of aerial and basal tillers of Piata palisade grass were higher at the beginning of the pasture deferment period. Nitrogen fertilization does not stimulate appearance of tillers on deferred Piata palisade grass. Tiller population stability, however, is only high at the beginning of deferment, decreasing after this initial period.

Effects on Berry Shrinkage in Vitis vinifera. L cv. ‘Merlot’ From Changes in Canopy/Root Ratio: A Preliminary Approach

A trial was conducted to find a possible relationship between the canopy/root ratio and the incidence and severity of premature berry shrinkage, and to propose an alternative to avoid this phenomenon in ‘Merlot’ grapevines. The ratio was changed by cutting foliage at a certain height 15 days before veraison, and by delaying the removal of trunk shoots. Treatments were the control (T1), 50% foliage area of control (T2), 75% foliage area of control (T3), and delayed trunk shoot removal (T4). Foliage area and the canopy/root ratio were lower in the T2 and T3 treatments. T4 was ineffective in changing the parameters. The incidence of berry shrinkage was lower for the T2 and T3 treatments, with the percentage of affected plants dropping from the 52% of the control to 22.9% and 31.3% for T2 and T3 respectively, and from 52.4% of the affected bunches to 16.6% and 21.2% for the same treatments respectively. The percentage of affected bunches falling into the range of moderate to severe damage fell from the 24% of the control to 5.2% and 3.9% for T2 and T3 respectively. Therefore, it is possible to avoid the incidence and severity of berry shrinkage by decreasing the canopy/root ratio in ‘Merlot’ grapevines.

札幌市郊外の落葉広葉樹林における現存量に関する諸量の推定(I) : 林分現存量と葉面積の垂直分布について(会員研究発表論文)

札幌市郊外の落葉広葉樹林における現存量に関する諸量の推定(I) : 林分現存量と葉面積の垂直分布について(会員研究発表論文)

Estimation of coniferous forest aboveground biomass with aggregated airborne small-footprint LiDAR full-waveforms.

Forest aboveground biomass (AGB) is critical for assessing forest productivity and evaluating carbon sequestration rates. Discrete-return LiDAR has been widely used to estimate forest AGB, however, fewer studies have estimated the coniferous forest AGB using airborne small-footprint full-waveform LiDAR data. The objective of this study was to extract a suite of newly proposed metrics from airborne small-footprint full-waveform LiDAR data and to evaluate the ability of these metrics in estimating coniferous forest AGB. To achieve this goal, each waveform was first preprocessed, including de-noising, smoothing, and normalization. Next, all the waveforms within each plot were aggregated into a large pseudo waveform and the return energy profile was generated. Then, the foliage profile was retrieved from the return energy profile based on the Geometric Optical and Radiative Transfer (GORT) model. Finally, a series of new return energy profile metrics and foliage profile metrics were extracted to estimate forest AGB. Simple linear regression was conducted to assess the correlation between each LiDAR metric and forest AGB. Stepwise multiple regression analysis was then carried out to select important prediction metrics and establish the optimal forest AGB estimation model. Results indicated that both return energy profile and foliage profile based height-related metrics were strongly correlated to forest AGB. The energy weighted canopy height (HEweight) (R = 0.88) and foliage area weighted height (HFweight) (R = 0.89) all had the highest correlation coefficients with forest AGB in return energy profile metrics and foliage profile metrics respectively. Energy height percentiles and foliage height percentiles also had the ability to explain AGB variation. The energy-related metrics, foliage area-related metrics, and bounding volume-related metrics derived from the return energy profile and foliage profile were not all sensitive to forest AGB. This study also concluded that combining return energy profile metrics and foliage profile metrics could improve the accuracy of forest AGB estimation, and the optimal model contained the metrics of HFweight, HEweight, and VolumemaxHE, which is the product of the maximum canopy return energy profile amplitude (maxCE) and the maximum height of return energy profile (maxHE).

Estimating structural parameters of agricultural crops from ground-based multi-angular digital images with a fractional model of sun and shade components

Accurate and efficient in situ measurement methods of leaf area index (LAI) and leaf angle distribution (LAD) are needed to estimate the fluxes of water and energy in agricultural settings. However, available methods: to estimate these two parameters, especially LAD, are limited. In this study, we propose a field measurement method using multi-angular digital images to estimate LAI and LAD simultaneously from the area proportions of: (i) sunlit soil; (ii) sunlit leaves; (iii) shaded soil; and (iv) shaded leaves. A new expression of the fraction of sunlit leaves is developed based on the radiative transfer theory. Coupling the measured and modeled fractions with an optimization scheme, LAI and the LAD parameters are derived from inverting a fractional model of sunlit and shaded leaves and soil. Through four tests using simulated scenes and in situ measurements for row crops, it is determined that our method performs well. The absolute error of LAI estimation is less than 0.1 when LAI is low (i.e., <1.2), and the absolute deviations of LAI estimates are approximately 0.5 when the reference LAI is 3.5. The estimation errors of LAI and the G function (a representative of LAD which quantifies the projection of unit foliage area) for in situ measurements are respectively less than 0.2 and 0.06 in general. In addition, the accuracy of estimation is even higher when leaves are simulated as randomly distributed disks or observations from multiple azimuth planes are used. One of the most interesting features of this method is its ability to estimate reasonable LAD directly from the fractions of sunlit and shaded leaves, even when LAI is high (i.e., >3), so little background soil is seen. The sensitivity and uncertainty analysis is consistent with the estimation errors. Theoretically, the application of this method is not limited to row crops or to field measurement, as the derived formulae of sunlit and shaded components can be used for other types of vegetation by introducing the clumping index and can be used in the modeling of canopy vegetation parameters (e.g., canopy reflectance).

Flixweed (Descurainia sophia) Shade Tolerance and Possibilities for Flixweed Management Using Rapeseed Seeding Rate

Brassicaceae weeds can be problematic in canola varieties that have not been modified to resist specific broad-spectrum herbicides. The overall objective of this study was to evaluate the potential for increased rapeseed seeding rate as a management strategy for flixweed. To accomplish this objective, a field study was conducted to determine crop seeding rate effects on canopy light transmission and rapeseed yield characteristics, as well as a greenhouse study to determine morphological and photosynthetic responses of flixweed to decreasing irradiance levels. Results from the field study indicated that light transmittance through the canopy decreased linearly as crop seeding rate increased from 1.8 to 9.0 kg ha-1. Increasing crop seeding rate did not influence rapeseed aboveground biomass, seed yield, and harvest index, but negatively affected rapeseed seed oil content in one of two site-years. Greenhouse study results indicated that declining irradiance levels caused reductions in flixweed biomass, root allocation, and photosynthetic light compensation point. Flixweed leaf allocation, foliage area ratio, and specific foliage area increased in response to decreasing irradiance levels. Combined results of field and greenhouse studies suggest that increasing rapeseed seeding rate can suppress flixweed growth while not causing yield penalties from increased intraspecific competition. However, increased rapeseed seeding rate might not be an adequate control strategy on its own because flixweed displays characteristics of a shade-tolerant species.

Airborne dust absorption by semi-arid forests reduces PM pollution in nearby urban environments

Dust storms are a major source of global atmospheric particulate matter (PM), having significant impacts on air pollution and human health. During dust storms, daily averages of atmospheric PM concentrations can reach high levels above the World Health Organization (WHO) guideline for air quality. The objective of this study was to explore the impact of forests on PM distribution following dust events in a region that is subjected to frequent dust storms (Northern Negev, Israel). Dust was measured in a forest transect including urban environments that are nearby the forest and at a distal location. During a background period, without dust events, the forest with its surrounding areas were characterized by lower monthly average of PM concentrations (38μg/m3) compared with areas that are not affected by the forest (54μg/m3). Such difference can be meaningful for long-term human health exposure. A reduction in PM levels in the forest transect was evident at most measured dust events, depending on the storm intensity and the locations of the protected areas. A significant reduction in PM2.5/PM10 during dust events, indicates the high efficiency of the forest trees to absorb airborne PM2.5. Analysis of dust particles absorbed on the foliage revealed a total dust deposits of 8.1–9.2g/m2, which is equal to a minimum of 418.2tons removed from the atmosphere per a forest foliage area (30km2). The findings can support environmental strategies to enhance life quality in regions that are subjected to dust storms, or under potential risk of dust-related PM due to land use and/or climate changes.

Application of 3D triangulations of airborne laser scanning data to estimate boreal forest leaf area index

We propose 3D triangulations of airborne Laser Scanning (ALS) point clouds as a new approach to derive 3D canopy structures and to estimate forest canopy effective LAI (LAIe). Computational geometry and topological connectivity were employed to filter the triangulations to yield a quasi-optimal relationship with the field measured LAIe. The optimal filtering parameters were predicted based on ALS height metrics, emulating the production of maps of LAIe and canopy volume for large areas. The LAIe from triangulations was validated with field measured LAIe and compared with a reference LAIe calculated from ALS data using logarithmic model based on Beer’s law. Canopy transmittance was estimated using All Echo Cover Index (ACI), and the mean projection of unit foliage area (β) was obtained using no-intercept regression with field measured LAIe. We investigated the influence species and season on the triangulated LAIe and demonstrated the relationship between triangulated LAIe and canopy volume. Our data is from 115 forest plots located at the southern boreal forest area in Finland and for each plot three different ALS datasets were available to apply the triangulations. The triangulation approach was found applicable for both leaf-on and leaf-off datasets after initial calibration. Results showed the Root Mean Square Errors (RMSEs) between LAIe from triangulations and field measured values agreed the most using the highest pulse density data (RMSE=0.63, the coefficient of determination (R2)=0.53). Yet, the LAIe calculated using ACI-index agreed better with the field measured LAIe (RMSE=0.53 and R2=0.70). The best models to predict the optimal alpha value contained the ACI-index, which indicates that within-crown transmittance is accounted by the triangulation approach. The cover indices may be recommended for retrieving LAIe only, but for applications which require more sophisticated information on canopy shape and volume, such as radiative transfer models, the triangulation approach may be preferred.

Early Yield Prediction Using Image Analysis of Apple Fruit and Tree Canopy Features with Neural Networks

(1) Background: Since early yield prediction is relevant for resource requirements of harvesting and marketing in the whole fruit industry, this paper presents a new approach of using image analysis and tree canopy features to predict early yield with artificial neural networks (ANN); (2) Methods: Two back propagation neural network (BPNN) models were developed for the early period after natural fruit drop in June and the ripening period, respectively. Within the same periods, images of apple cv. “Gala” trees were captured from an orchard near Bonn, Germany. Two sample sets were developed to train and test models; each set included 150 samples from the 2009 and 2010 growing season. For each sample (each canopy image), pixels were segmented into fruit, foliage, and background using image segmentation. The four features extracted from the data set for the canopy were: total cross-sectional area of fruits, fruit number, total cross-section area of small fruits, and cross-sectional area of foliage, and were used as inputs. With the actual weighted yield per tree as a target, BPNN was employed to learn their mutual relationship as a prerequisite to develop the prediction; (3) Results: For the developed BPNN model of the early period after June drop, correlation coefficients (R2) between the estimated and the actual weighted yield, mean forecast error (MFE), mean absolute percentage error (MAPE), and root mean square error (RMSE) were 0.81, −0.05, 10.7%, 2.34 kg/tree, respectively. For the model of the ripening period, these measures were 0.83, −0.03, 8.9%, 2.3 kg/tree, respectively. In 2011, the two previously developed models were used to predict apple yield. The RMSE and R2 values between the estimated and harvested apple yield were 2.6 kg/tree and 0.62 for the early period (small, green fruit) and improved near harvest (red, large fruit) to 2.5 kg/tree and 0.75 for a tree with ca. 18 kg yield per tree. For further method verification, the cv. “Pinova” apple trees were used as another variety in 2012 to develop the BPNN prediction model for the early period after June drop. The model was used in 2013, which gave similar results as those found with cv. “Gala”; (4) Conclusion: Overall, the results showed in this research that the proposed estimation models performed accurately using canopy and fruit features using image analysis algorithms.

Preliminary study on integrated wireless smart terminals for leaf area index measurement

The last few decades have seen the emergence of many new methods for measuring leaf area index (LAI). One attractive method is to measure LAI by using a readily available simple instrument, such as a smartphone, as an alternative to traditional complicated and thus costly commercial instruments. We designed a novel integrated LAI measurement system, LAISmart, which is implemented by using two smart terminals communicating through a wireless connection in an integrated support infrastructure. The LAI is calculated by using the Beer gap fraction model on the assumption of spherical leaf angle distribution that takes the G value (the projection of unit foliage area on the plane perpendicular to the view direction θ) as constant at 0.5. The gap fraction is calculated by segmenting the image pixel into canopy and background. For the selection of image segment features, LAISmart provides two options, greenness index and blue band, which may be suited to different vegetation types. The proposed LAISmart was validated by measurements on four types of vegetation, i.e., Evergreen Needleleaf Forest (ENF), Deciduous Broadleaf Forest (DBF), Deciduous Needleleaf Forest (DNF), and broadleaf crop, on which 114 LAI values were calculated in the eight datasets. A pairwise comparison between LAISmart and LAI-2000 showed that the LAI values derived from LAISmart correlated strongly with those of the LAI-2000, with an R2 value of 0.97, and had high accuracy in total, with a root–mean–square error (RMSE) of 0.45m2/m2. The validation results revealed that the overestimation on LAI caused by underestimation of the G value might complement the bias caused by misclassification. Moreover, although there is no limitation on the shooting angle of LAISmart, it is recommended that LAISmart be used at the low zenith angle mode, e.g., upward- or downward-looking mode, rather than at the large zenith angle. Further validation will focus on other vegetation types such as grass and shrubs in order to improve the performance of LAISmart for different vegetation types.