CRESCIMENTO VEGETATIVO DA MORINGA EM DISTINTOS REGIMES DE IRRIGAÇÃO ASSOCIADOS A COMPOSIÇÕES DE DIFERENTES SUBSTRATOS

CRESCIMENTO VEGETATIVO DA MORINGA EM DISTINTOS REGIMES DE IRRIGAÇÃO ASSOCIADOS A COMPOSIÇÕES DE DIFERENTES SUBSTRATOS VALDIR MOURA DE OLIVEIRA JUNIOR1; THAYS SOUSA LOPES1; JOÃO VALDENOR PEREIRA FILHO1; JAILDO RIBEIRO BARBOSA1; ROBERT WILLIAM FERREIRA SOARES1; CARMEM CRISTINA MARECO DE SOUSA PEREIRA2 1Centro Integrado de Ensino Superior, Universidade Estadual do Piauí (UESPI), Rua Almir Benvindo, s/n, bairro Aeroporto, 64860-000, Uruçuí, Piauí, Brasil. [email protected]; [email protected]; [email protected]; [email protected]; [email protected] 2 Departamento de Engenharia Agrícola, Universidade Federal Rural de Pernambuco (UFRPE), Rua Dom Manuel de Medeiros, s/n - Dois Irmãos, 52171-900, Recife, Pernambuco, Brasil. [email protected] 1 RESUMO A moringa possui ampla adaptabilidade e se condiciona, com muita facilidade, ao clima e solo do Nordeste brasileiro. Ainda são escassas as informações sobre a produção de mudas desta espécie sob composições de substratos associados a regimes de irrigação. Desta forma, o objetivo desse trabalho foi caracterizar o comportamento vegetativo de plantas de moringa submetidas a distintas composições de substratos e regimes de irrigação. O experimento foi realizado em ambiente telado, no período de setembro a outubro de 2020, na área experimental da Universidade Estadual do Piauí, Uruçuí. Adotou-se um delineamento experimental em esquema fatorial, sendo, o primeiro fator, dois regimes de irrigação (50 e 100% da ETo) e o segundo fator, cinco substratos (SB1 = latossolo vermelho; SB2 = substrato comercial; SB3 = solo + esterco; SB4 = solo + cinza vegetal; SB5 = solo + borra de café), com 5 repetições. Aos 45 dias após a semeadura (DAS) foram avaliadas a altura de plantas e o diâmetro do caule. Os parâmetros de crescimento inicial da cultura da moringa foram afetados significativamente pela interação (regimes de irrigação x substratos), sendo os melhores resultados obtidos, na maioria dos substratos utilizados, com a aplicação do regime hídrico de 100% da ETo. Palavras-chave: Moringa oleifera Lam, produção de mudas, déficit hídrico. OLIVEIRA JUNIOR, V. M.; LOPES, T. S.; PEREIRA FILHO, J. V.; BARBOSA, J. R.; SOARES, R. W. F.; PEREIRA, C. C. M. S. VEGETATION GROWTH OF MORINGA IN DIFFERENT IRRIGATION REGIMES ASSOCIATED WITH COMPOSITIONS OF DIFFERENT SUBSTRATES 2 ABSTRACT Moringa has wide adaptability and is very easily conditioned to the climate and soil of northeastern Brazil. Information on the production of seedlings of this species under compositions of substrates associated with irrigation regimes is still scarce. Thus, this work aimed to characterize the vegetative behavior of moringa plants submitted to different compositions of substrates and irrigation regimes. The experiment was carried out in a screened environment, from September to October 2020, in the experimental area of ​​the State University of Piauí, Uruçuí. An experimental design was adopted in a factorial scheme, the first factor being two irrigation regimes (50 and 100% of ETo) and the second factor, five substrates (SB1 = red oxisol; SB2 = commercial substrate; SB3 = soil + manure; SB4 = soil + vegetable ash; SB5 = soil + coffee grounds), with 5 repetitions. At 45 days after sowing (DAS), plant height and stem diameter was evaluated. The initial growth parameters of the moringa crop were significantly affected by the interaction (irrigation regimes x substrates), with the best results obtained, in most of the substrates used, with the application of the water regime of 100% of ETo. Keywords: Moringa oleifera Lam, seedling production, water deficit.

Hurricanes Substantially Reduce the Nutrients in Tropical Forested Watersheds in Puerto Rico

Because nutrients including nitrogen and phosphorus are generally limited in tropical forest ecosystems in Puerto Rico, a quantitative understanding of the nutrient budget at a watershed scale is required to assess vegetation growth and predict forest carbon dynamics. Hurricanes are the most frequent disturbance in Puerto Rico and play an important role in regulating lateral nitrogen and phosphorus exports from the forested watershed. In this study, we selected seven watersheds in Puerto Rico to examine the immediate and lagged effects of hurricanes on nitrogen and phosphorous exports. Our results suggest that immediate surges of heavy precipitation associated with hurricanes accelerate nitrogen and phosphorus exports as much as 297 ± 113 and 306 ± 70 times than the long-term average, respectively. In addition, we estimated that it requires approximately one year for post-hurricane riverine nitrogen and phosphorus concentrations to recover to pre-hurricane levels. During the recovery period, the riverine nitrogen and phosphorus concentrations are 30 ± 6% and 28 ± 5% higher than the pre-hurricane concentrations on average.

Recognition of Areca Leaf Yellow Disease Based on PlanetScope Satellite Imagery

Areca yellow leaf disease is a major attacker of the planting and production of arecanut. The continuous expansion of arecanut (Areca catechu L.) planting areas in Hainan has placed a great need to strengthen the monitoring of this disease. At present, there is little research on the monitoring of areca yellow leaf disease. PlanetScope imagery can achieve daily global coverage at a high spatial resolution (3 m) and is thus suitable for the high-precision monitoring of plant pest and disease. In this paper, PlanetScope images were employed to extract spectral features commonly used in disease, pest and vegetation growth monitoring for primary models. In this paper, 13 spectral features commonly used in vegetation growth and pest monitoring were selected to form the initial feature space, followed by the implementation of the Correlation Analysis (CA) and independent t-testing to optimize the feature space. Then, the Random Forest (RF), Backward Propagation Neural Network (BPNN) and AdaBoost algorithms based on feature space optimization to construct double-classification (healthy, diseased) monitoring models for the areca yellow leaf disease. The results indicated that the green, blue and red bands, and plant senescence reflectance index (PSRI) and enhanced vegetation index (EVI) exhibited highly significant differences and strong correlations with healthy and diseased samples. The RF model exhibits the highest overall recognition accuracy for areca yellow leaf disease (88.24%), 2.95% and 20.59% higher than the BPNN and AdaBoost models, respectively. The commission and omission errors were lowest with the RF model for both healthy and diseased samples. This model also exhibited the highest Kappa coefficient at 0.765. Our results exhibit the feasible application of PlanetScope imagery for the regional large-scale monitoring of areca yellow leaf disease, with the RF method identified as the most suitable for this task. Our study provides a reference for the monitoring, a rapid assessment of the area affected and the management planning of the disease in the agricultural and forestry industries.

Stock Influence on Growth, Morphological and Biochemical Leaf Parameters Prunus domestica L.

Vegetation growth peculiarities and morphological and physical-biochemical features of Prunus domestica L. Utro and Yaichnaya Sinyaya varieties leaves grafted on different growing strength rootstocks were studied. Low-growing clonal rootstocks 140–1 and Novinka decreased the trees growing strength on 15–20% in comparison with strong-growing stocks; medium-growing rootstocks OPA-15-2 and OP-23-23 reduced it on 10%. The longest growing activity and the largest sprouts length was stated on these rootstocks as well, i.e. 1.3–1.4 times more than on other ones. Stable sprouts average length decrease was registered on grafted stocks 140–1 and Novinka. Leaf surface index value on the trees grafted on clonal rootstocks OPA-15-2 and OP-23-23 was on 40% higher than on control, i.e. 4.3 leaves m2/crown projection area m2. Optimal values of total increment, sprouts average length, leaves area and the largest part of physiological-biochemical parameters were stated at medium-growing clonal rootstocks OPA-15-2 and OP-23-23 use. Plum leaves blades were hypostomatic; numerous stomata were located on the abaxial (bottom) side of leaves. Stomata were located in interveinal space irregularly. Stomata length size varied from 14.6 μm (Utro/seedlings) to 22.1 μm (Yaichnaya Sinyaya/OP-23-23). The rootstock has influence on the process of photosynthesis, antioxidant activity, accumulation of minerals and metabolic answerin the leaves.

A Complete Environmental Intelligence System for LiDAR-Based Vegetation Management in Power-Line Corridors

This paper presents the first complete approach to achieving environmental intelligence support in the management of vegetation within electrical power transmission corridors. Contrary to the related studies that focused on the mapping of power lines, together with encroaching vegetation risk assessment, we realised predictive analytics with vegetation growth simulation. This was achieved by following the JDL/DFIG data fusion model for complementary feature extraction from Light Detection and Ranging (LiDAR) derived data products and auxiliary thematic maps that feed an ensemble regression model. The results indicate that improved vegetation growth prediction accuracy is obtained by segmenting training samples according to their contextual similarities that relate to their ecological niches. Furthermore, efficient situation assessment was then performed using a rasterised parametrically defined funnel-shaped volumetric filter. In this way, RMSE≈ 1 m was measured when considering tree growth simulation, while a 0.37 m error was estimated in encroaching vegetation detection, demonstrating significant improvements over the field observations.

The Evaluation of the Success of the Growth of Vegetation in Conservation Efforts at the Area Tanjung Bastian Kabupaten Timor Tengah Utara

Pengelolaan terhadap sumberdaya alam menjadi point penting terutama dalam menjaga manfaat, kesinambungan dan berkelanjutan sumber alam. Potensi sumberdaya alam yang tersedia dengan pengelolaan yang baik dapat memberikan manfaat bagi kehidupan manusia. Potensi sumberdaya alam dapat menjadi daya tarik masyarakat dan dapat dijadikan sebagai tempat wisata. Kawasan Tanjung Bastian merupakan salah satu kawasan wisata yang berada di Kab. TTU. yang identik dengan pantai serta juga arena pacuan kuda dan pemandangan alam. Dalam pengelolaannya upaya mempertahankan kondisi ekologi di wisata Tanjung Bastian seperti kegiatan penanaman vegetasi diareal kawasan wisata sebagai upaya konservasi lahan sebagai regerasi vegetasi. Kelangsungan hidup vegetasi dapat tumbuh pada kondisi pertumbuhan yang stabil dan mampu bersaing dengan kondisi fisik lingkungan dan iklim yang ekstrim. Tujuan dari penelitian ini untuk mengetahui tingkat keberhasilan vegetasi dan faktor-faktor penyebab kerusakan pertumbuhan vegetasi. Berdasarkan hasil observasi tanaman yang berhasil hidup sebanyak 53 tanaman yang terdiri dari 6 spesies, dengan jumlah yang hidup terbanyak terdapat pada spesies Delonix regia sebanyak 15 tanaman, dan spesies yang paling sedikit ialah spesies Senna siamea dengan jumlah 3 tanaman. Klasifikasi kriteria penilaian keberhasilan vegetasi bahwa tingkat keberhasilan vetegasi di kawasan tanjung bastian termasuk dalam kategori agak rusak dengan nilai 57,3%.ABSTRACTResources management nature becoming point to important especially in maintaining benefits, continuity and sustainable natural source.Natural resource potential available with proper management would be of avail for human life. Natural resource potential can be attraction the community and can be used as tourist destinations. The area of tanjung bastian is one of the area who was in District North Central Timor are identical to the beach and also the racetrack and natural scenery. In its management efforts to maintain ecological conditions in Tanjung Bastian tourism such as planting tourism areas as an effort to conserve land as vegetation regeneration. The survival of vegetation can grow in stable growth conditions and be able to compete with extreme environmental and climatic conditions. The purpose of this study was to determine the success rate of vegetation and the factors causing damage to vegetation growth. Based on the results of observation plants who succeeded life 53 a plant consisting of 6 species with the numbers of life most there are to a species Delonix regia as many as 15 plants and the least species is Senna siamea with 3 plants. The classification of the assessment criteria vegetation that the level of success of success in the vetegasi tanjung bastian included in a category in quite poor repair the % 57,3.

Quantifying Influences of Natural and Anthropogenic Factors on Vegetation Changes Based on Geodetector: A Case Study in the Poyang Lake Basin, China

Understanding the driving mechanism of vegetation changes is essential for vegetation restoration and management. Vegetation coverage in the Poyang Lake basin (PYLB) has changed dramatically under the context of climate change and human activities in recent decades. It remains challenging to quantify the relative contribution of natural and anthropogenic factors to vegetation change due to their complicated interaction effects. In this study, we selected the Normalized Difference Vegetation Index (NDVI) as an indicator of vegetation growth and used trend analysis and the Mann-Kendall test to analyze its spatiotemporal change in the PYLB from 2000 to 2020. Then we applied the Geodetector model, a novel spatial analysis method, to quantify the effects of natural and anthropogenic factors on vegetation change. The results showed that most regions of the basin were experiencing vegetation restoration and the overall average NDVI value in the basin increased from 0.756 to 0.809 with an upward yearly trend of +0.0026. Land-use type exerted the greatest influence on vegetation change, followed by slope, elevation, and soil types. Except for conversions to construction land, most types of land use conversion induced an increase in NDVI in the basin. The influence of one factor on vegetation NDVI was always enhanced when interacting with another. The interaction effect of land use types and population density was the largest, which could explain 45.6% of the vegetation change, indicating that human activities dominated vegetation change in the PYLB. Moreover, we determined the ranges or types of factors most suitable for vegetation growth, which can be helpful for decision-makers to optimize the implementation of ecological projects in the PYLB in the future. The results of this study could improve the understanding of the driving mechanisms of vegetation change and provide a valuable reference for ecological restoration in subtropical humid regions.

Multi-Model Estimation of Forest Canopy Closure by Using Red Edge Bands Based on Sentinel-2 Images

In remote sensing, red edge bands are important indicators for monitoring vegetation growth. To examine the application potential of red edge bands in forest canopy closure estimation, three types of commonly used models—empirical statistical models (multiple stepwise regression (MSR)), machine learning models (back propagation neural network (BPNN)) and physical models (Li–Strahler geometric-optical (Li–Strahler GO) models)—were constructed and verified based on Sentinel-2 data, DEM data and measured data. In addition, we set up a comparative experiment without red edge bands. The relative error (ER) values of the BPNN model, MSR model, and Li–Strahler GO model with red edge bands were 16.97%, 20.76% and 24.83%, respectively. The validation accuracy measures of these models were higher than those of comparison models. For comparative experiments, the ER values of the MSR, Li–Strahler GO and BPNN models were increased by 13.07%, 4% and 1.22%, respectively. The experimental results demonstrate that red edge bands can effectively improve the accuracy of forest canopy closure estimation models to varying degrees. These findings provide a reference for modeling and estimating forest canopy closure using red edge bands based on Sentinel-2 images.

A Handheld Grassland Vegetation Monitoring System Based on Multispectral Imaging

Monitoring grassland vegetation growth is of vital importance to scientific grazing and grassland management. People expect to be able to use a portable device, like a mobile phone, to monitor grassland vegetation growth at any time. In this paper, we propose a handheld grassland vegetation monitoring system to achieve the goal of monitoring grassland vegetation growth. The system includes two parts: the hardware unit is a hand-held multispectral imaging tool named ASQ-Discover based on a smartphone, which has six bands (wavelengths)—including three visible bands (450 nm, 550 nm, 650 nm), a red-edge band (750 nm), and two near-infrared bands (850 nm, 960 nm). The imagery data of each band has a size of 5120 × 3840 pixels with 8-bit depth. The software unit improves image quality through vignetting removal, radiometric calibration, and misalignment correction and estimates and analyzes spectral traits of grassland vegetation (Fresh Grass Ratio (FGR), NDVI, NDRE, BNDVI, GNDVI, OSAVI and TGI) that are indicators of vegetation growth in grassland. We introduce the hardware and software unit in detail, and we also experiment in five pastures located in Haiyan County, Qinghai Province. Our experimental results show that the handheld grassland vegetation growth monitoring system has the potential to revolutionize the grassland monitoring that operators can conduct when using a hand-held tool to achieve the tasks of grassland vegetation growth monitoring.