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Prescribed burning and pyric herbivory play pivotal roles in mitigating wildfire risks, underscoring the imperative of consistent biomass monitoring for assessing fuel load reductions. Drone-derived surface models promise uninterrupted biomass surveillance but require complex photogrammetric processing. In a Mediterranean mountain shrubland burning experiment, we refined a Structure from Motion (SfM) and Multi-View Stereopsis (MVS) workflow to diminish biases in 3D modeling and RGB drone imagery-based surface reconstructions. Given the multitude of SfM-MVS processing alternatives, stringent quality oversight becomes paramount. We executed the following steps: (i) calculated Root Mean Square Error (RMSE) between Global Navigation Satellite System (GNSS) checkpoints to assess SfM sparse cloud optimization during georeferencing; (ii) evaluated elevation accuracy by comparing the Mean Absolute Error (MAE) of six surface and thirty terrain clouds against GNSS readings and known box dimensions; and (iii) complemented a dense cloud quality assessment with density metrics. Balancing overall accuracy and density, we selected surface and terrain cloud versions for high-resolution (2 cm pixel size) and accurate (DSM, MAE = 57 mm; DTM, MAE = 48 mm) Digital Elevation Model (DEM) generation. These DEMs, along with exceptional height and volume models (height, MAE = 12 mm; volume, MAE = 909.20 cm3) segmented by reference box true surface area, substantially contribute to burn impact assessment and vegetation monitoring in fire management systems.

We propose an optimized Structure-from-Motion (SfM) Multi-View Stereopsis (MVS) workflow, based on minimizing different errors and inaccuracies of historical aerial photograph series (1945, 1979, 1984, and 2008 surveys), prior to generation of elevation-calibrated historical Digital Surface Models (hDSM) at 1 m resolution. We applied LiDAR techniques on Airborne Laser Scanning (ALS) point clouds (Spanish PNOA LiDAR flights of 2014 and 2019) for comparison and validation purposes. Implementation of these products in multi-temporal analysis requires quality control due to the diversity of sources and technologies involved. To accomplish this, (i) we used the Mean Absolute Error (MAE) between GNSS-Validation Points and the elevations observed by DSM-ALS to evaluate the elevation accuracy of DSM-ALS generated with the LAScatalog processing engine; (ii) optimization of the SfM sparse clouds in the georeferencing step was evaluated by calculating the Root Mean Square Error (RMSE) between the Check Points extracted from DSM-ALS and the predicted elevations per sparse cloud; (iii) the MVS clouds were evaluated by calculating the MAE between ALS-Validation Points and the predicted elevations per MVS cloud; iv) the accuracy of the resulting historical SfM-MVS DSMs were assessed using the MAE between ALS-Validation Points and the observed elevations per historical DSM; and (v) we implemented a calibration method based on a linear correction to reduce the elevation discrepancies between historical DSMs and the DSM-ALS 2019 reference elevations. This optimized workflow can generate high-resolution (1 m pixel size) hDSMs with reasonable accuracy: MAE in z ranges from 0.41 m (2008 DSM) to 5.21 m (1945 DSM). Overall, hDSMs generated using historical images have great potential for geo-environmental processes monitoring in different ecosystems and, in some cases (i.e., sufficient image overlapping and quality), being an acceptable replacement for LiDAR data when it is not available.

Qymyz is a traditional acidic and ethanolic beverage in central Asian countries made from mare milk fermentation with lactic acid bacteria (LAB) and yeasts. Modeling the growth of microorganisms during fermentation is one of the methods used to control the quality of fermented products. The objective of the study was, firstly, to model the growth kinetics of Kazachstania unispora found in qymyz, and, secondly, to understand their interaction with Lacticaseibacillus casei and Lactobacillus kefiri during the fermentation of mare milk. The K. unispora optimum values of pH and temperature were 4.81 ± 0.22 and 30.16 ± 0.53 °C, respectively, with an optimal growth rate (µopt) of 0.56 ± 0.02 h−1. K. unispora had an ethanol production rate of 6.1 × 10−8 mg·CFU−1. Growth, in terms of limiting substrates showed a lower Ks value for galactose at 0.13 ± 0.04 mg·mL−1 with µopt of 0.45 ± 0.01 h−1, while, for glucose, the Ks was 0.24 ± 0.03 mg·mL−1 with the same µopt. Cocultures of K. unispora were conducted with L. casei and L. kefiri in a synthetic medium and mare milk. The results showed that K. unispora growth was limited and, thus, its ethanol production capacity was inhibited. VOC analysis of mare milk fermented with the studied strains and their cocultures resulted in 37 major volatile compounds. Statistical analysis of the VOC profiles showed that K. unispora modulates the aroma production in coculture with LAB.

The growth characteristics of two strains of lactic acid bacteria (LAB), Lacticaseibacillus casei and Lactobacillus kefiri, isolated from qymyz, a traditional fermented mare milk beverage, were studied and modeled, including the effect of different carbohydrates, pH, and temperature. Along with population, substrates, and metabolites, lactic acid and ethanol were monitored by HPLC. Growth parameters were obtained from mono- and biphasic logistic growth models that fit the population evolution of L. casei and L. kefiri, respectively. The effect of temperature and pH on the growth rate was represented with the gamma concept model, while the effect of the limiting substrate was evaluated according to the Monod equation. Lastly, a simplified Luedeking and Piret equation was used to represent metabolite production. The optimum values of pH and temperature were 6.69 ± 0.20, 38.63 ± 0.32 °C, 5.93 ± 0.08, and 33.15 ± 0.53 °C, with growth rate values of 0.66 ± 0.01 h−1 and 0.29 ± 0.01 h−1 for L. casei and L. kefiri, respectively. L. casei had a homofermentative pathway, while L. kefiri was heterofermentative, with an ethanol production rate of 2.90 × 10−9 mg·CFU−1. The Monod model showed that L. casei had the lowest Ks value for lactose, while for L. kefiri, it was the highest among milk carbohydrates. These results show that the population of the two LAB strains and therefore the concentrations of acid and ethanol can be controlled by the fermentation conditions and that our model can help to significantly improve the production of qymyz.

The effect of Akpan (yoghurt-like product) consumption on the human intestinal microbiota was examined. The prebiotic potential of Akpan was assessed by in vitro fermentation using, as inocula, individual probiotic strains and faecal samples from three healthy donors. In this latter case, the prebiotic activity was assessed through the quantification of short chain fatty acid (SCFA) production, the evolution of the pH and the evaluation of dynamic bacterial population by fluorescent in situ hybridization (FISH). Results demonstrated that Akpan was metabolized after 44 h of fermentation, exerting a prebiotic effect, similar to that observed for fructooligosaccharides (FOS). All the considered bacterial groups significantly increased after Akpan and FOS fermentation. Under the tested conditions, no significant differences between the SCFA concentration produced by Akpan and FOS after of incubation were detected. Our findings contribute to support the utilization of Akpan as a functional food with potential beneficial effects on gastrointestinal health.

Sequências do DNA de uma região em comum de múltiplos indiví­duos de uma população podem revelar polimorfismos que permitem o estudo da evolução do genoma e suas histórias de seleções, migrações e recombinações. Adicionando-se a esses polimorfismos da população informações quanto origem geográfica, viabiliza-se um estudo filogeográfico que permite a elaboração de cenários de evolução após a domesticação; bem como quais eventos (mutações ou recombinações) mais influenciaram a diversidade genética (DG) desta população, para aquela região do DNA em estudo. Por outro lado, a associação desses polimorfismos das sequências com as caracterí­sticas de interesse estabelece um estudo de associação. Neste contexto, este trabalho visou mostrar a aplicação do polimorfismo de sequências de DNA em um estudo de filogeografia e de associação. Para ambos os estudos foram utilizados dezenove segmentos de seis genes candidatos (Sh2, Bt2, Sssl, Ael, Wx e 02) em uma coleção de sorgo (Sorghum bicolor L. Moench), composta por 210 acessos. Os genes Sh2, Bt2, Sssl, Ael e Wx estão envolvidos na sí­ntese do amido e o gene 02 na sí­ntese de proteí­nas de reserva. A DG foi menor nos genes Sh2, Bt2 e Sssl; e maior para Ael, Wx e 02. Os testes estatí­sticos revelaram um elevado número de associações falso-positivas em função da estruturação da coleção, porém foram mantidas várias associações corroboradas pela co-localização com QTLs de sorgo e de milho.

A global model of the lactic fermentation step of gowé was developed by assembling blocks hosting models for bacterial growth, lactic acid production, and the drop of pH during fermentation. Commercial strains of Lactobacillus brevis and of Lactobacillus plantarum were used; their growth was modeled using Rosso’s primary model and the gamma concept as a secondary model. The optimum values of pH and temperature were 8.3 ± 0.3, 44.6 ± 1.2 °C and 8.3 ± 0.3, 3.2 ± 37.1 °C with μmax values of 1.8 ± 0.2 and 1.4 ± 0.1 for L. brevis and L. plantarum respectively. The minimum inhibitory concentration of undissociated lactic acid was 23.7 mM and 35.6 mM for L. brevis and L. plantarum, respectively. The yield of lactic acid was five times higher for L. plantarum than for L. brevis, with a yield of glucose conversion to lactic acid close to 2.0 for the former and 0.8 for the latter. A model was developed to predict the pH drop during gowé fermentation. The global model was partially validated during manufacturing of gowé. The global model could be a tool to aid in the choice of suitable starters and to determine the conditions for the use of the starter.