Siregar IZ, Muharam KF, Purwanto YA, Sudrajat DJ. 2020. Seed germination characteristics in different storage time of Gmelina arborea treated with ultrafine bubbles priming. Biodiversitas 21: 4558-4564. Gmelina (Gmelina arborea) seed collected from tropical Indonesian forest experience seed deterioration during storage which is relatively faster than the gmelina seeds originating from temperate regions, such as India and Myanmar. Various treatments have been made to improve the seed viability and vigor after storage through various invigoration techniques. However, the utilization of promising novel technology such as ultrafine bubbles (UFB) has not been evaluated yet. The objective of this study was to determine the effect of seed priming using UFB, polyethylene glycol (PEG), and gibberellic acid (GA3) on the viability and vigor of gmelina seeds that have been stored for one and two years. This study was conducted by employing Completely Randomized Design (CRD) using three replicates. The study showed priming treatment had significant effect and formed average germination capacity of 80% for the seed stored for 1 year. On the other hand, the priming treatment using PEG-0.8 MPa was the best treatment for germination capacity of 74.67% on 2 years stored seeds. UFB had significant effect on germination capacity, germination rate, growth uniformity, and germination value. This result was expected due to reactive oxygen species (ROS) produced by micro-nano bubbles that could increase physiological activity of the seed cells.

To effectively reduce illegal timber trade, law enforcers need forensic methods to independently verify claims of wood origin. Multi-element analysis of traded plant material has the potential to be used to trace the origin of commodities, but for timber it has not been tested at relevant large scales. Here we put this method to the test, by evaluating its tracing accuracy for three economically important tropical timbers: Azobé and Tali in Central Africa (22 sites) and Red Meranti on Borneo (9 sites). Wood samples from 991 trees were measured using Inductively Coupled Plasma Mass Spectrometry and element concentrations were analysed to chemically group similar sites (clustering) and assess accuracy of tracing samples to their origin (Random Forest models). For all three timbers, we found distinct spatial differences in chemical composition. In Central Africa, tracing accuracy was 86%–98% for regional clusters of chemically similar sites, with accuracy depending on the tracing question. These clusters were 50–800 km apart and tracing accuracy was highest when combining the two timbers. Tracing accuracy of Red Meranti on Borneo was 88% at the site level. This high accuracy at a small scale may be related to the short distances at which differences in soil type occur on Borneo. A blind sample analysis of 46 African timber samples correctly identified the origin of 70%–72% of the samples, but failed to exclude 70% of the samples obtained from different species or outside the study area. Overall, these results illustrate a high potential for multi-element analysis to be developed into a timber tracing tool which can identify origin for multiple species and can do so at a within-country scale. To reach this potential, reference databases need to cover wider geographic areas and represent more timbers.

Cacao (Theobroma cacao) is a commodity that plays an important role in supporting economic and social development. However, cacao production can also be a major contributor to carbon emissions, which has stimulated various efforts toward sustainable cacao farm management. There remains a gap in knowledge regarding the links between carbon stocks and carbon footprints, which can serve as indicators of environment “friendliness.” In this study, we investigated carbon stocks and carbon footprints in two cacao cultivation systems, agroforests and monocultural systems, and the biophysical aspects (biotic and abiotic factors) that might contribute to the variability of carbon levels. System inventories, soil samples, and farmer interviews identified the characteristics and management practices of two cacao production systems. Results show that cacao agroforests accumulated more carbon stocks than cacao monocultures, 134.4 Mg C ha⁻¹ and 104.7 Mg C ha⁻¹, respectively, while cacao monocultural systems had higher carbon footprints than cacao agroforests, 1914.4 kg CO₂e ha⁻¹ and 932.1 ± 251.6 kg CO₂e ha⁻¹, respectively. Canopy cover, tree density, and soil organic carbon were the biophysical aspects that showed a significantly positive correlation with carbon stock levels, while canopy cover had a significantly negative correlation with carbon footprint levels. These results suggest that cacao agroforests are more climate-friendly management systems due to their ability to maintain high carbon stock levels while producing low carbon footprints.

Ebony (Diospyros celebica Bakh.) is an endemic plant on Celebes (Sulawesi) island. Extractive compounds within ebony wood cause it to have durability, strength, and beautiful patterns. In this study, we used near-infrared (NIR) spectroscopy to discriminate between ebony wood samples, based on their origins at different growth sites on Celebes island, and to develop quantitative models to predict the extractive content of ebony wood. A total of 45 wood meal samples from 11 sites located in West, Central, and South Celebes were collected in this study. NIR spectral data were acquired from hot water and ethanol–benzene soluble extracts from ebony wood in this study. The extractive content of the ebony was 10.408% and 10.774% based on hot water solubility and treatment with ethanol–benzene solvent, respectively. Multivariate analysis based on principal component analysis–discriminant analysis revealed that ebony wood from West Celebes differed from most of the wood from South Celebes; however, it was only slightly different from ebony wood from Central Celebes based on NIR spectra data. These findings were in line with the extractive contents obtained. Partial least square regression models based on wood meal spectra could potentially be used to estimate the hot water and ethanol–benzene extractive contents from ebony wood.

Rain tree (Samanea saman) is a dominant species commonly planted as a shade tree in urban landscapes in the tropics, including in Indonesia. This species is also targeted for routine inspection and monitoring within tree management systems. Management should particularly focus on tree health through assessment of tree growth conditions as well as tree stability. However, baseline information on the relationships of many key characteristics for the rain tree (e.g., growth, morphometrics, and biomechanics) is lacking. Therefore, an investigation was carried out to determine the relationship of morphometric parameters to tree growth, which included use of an acoustic tool to assess the elasticity of the tree stem. Fifty rain trees were selected for data collection and evaluated using stress wave velocity tools and visual morphometrics assessment. The results demonstrated that, in general, the trees had good vigor and stability. Statistical analysis showed a strong relationship between tree growth parameters and selected morphometric characteristics. The use of a nondestructive acoustic-based instrument enabled determining the modulus of elasticity, which provided equivalent results with the elasticity value obtained through a common method for determining tree stability. Only live crown ratio and tree slenderness parameters had a relationship with the dynamic modulus of elasticity. These results offer a means of measurement that is simpler, less expensive, and faster than current methods, although further testing is needed for different tree species and growth sites.

Ariawan I, Herdiyeni Y, Siregar IZ. 2020. Short Communication: Geometric morphometric analysis of leaves venation in Shorea spp. for identification using Digital Image Processing. Biodiversitas 21: 3303-3309. Shorea is one of the genera of the Dipterocarpaceae family which consists of more than 190 species. Massive exploitation of forests has threatened the sustainability of Shorea in nature. A total of 156 species has been listed on the IUCN (International Union for Conservation of Nature) red list. From the 156 species, 59.6% are in the critically endangered category, so urgent conservation is needed. However, during collection of Shorea at the seedling phase for conservation purposes, it is often difficult to distinguish among them that can cause errors in their collection process. To avoid these errors, identification needs to be done, usually based on plant leaf and flower morphology. Leaves are easier because they have the main features that distinguish each plant species, one of which is the venation structure. Geometric morphometric techniques are a modern approach recognized as useful for the identification of species in many plants. Geometric morphometrics analyzes the position of the venation point using coordinate geometry values. This research was aimed to extract venation features of Shorea leaves using a geometric morphometric approach. The extraction process result in some features, such as straightness, different angle, length ratio, scale projection, and secondary nerves. On extracted features, an analysis was then performed to find out the best features in classifying species of Shorea spp. The results of this study indicated that the geometric morphometric approach could extract the value of the features of straightness, different angle, length ratio, scale projection, and secondary nerves. The secondary nerve feature is the best feature because it can distinguish between fourcommonly planted species of Shorea spp. (S. acuminata, S. leprosula, S. ovalis, and S. selanica). By using the support vector machine classification technique to identify species of Shorea spp., the classification results obtained an average accuracy of 84.46%.