Article
Environmental Sciences
Bongokuhle Sibiya, Romano Lottering, John Odindi
Summary: Commercial forest species discrimination using second-order image texture combinations showed better accuracy with the SPLS-DA model than the PLS-DA model. The study demonstrates the value of second-order image texture combinations in discriminating commercial forest species.
GEOCARTO INTERNATIONAL
(2022)
Article
Environmental Sciences
Kiara Brewer, Romano Lottering, Kabir Peerbhay
Summary: The presence of invasive alien plants has a significant impact on ecosystems, affecting productivity and biodiversity. This study demonstrates the utility of remote sensing techniques and machine learning algorithms in detecting and mapping invasive alien wattle.
REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT
(2022)
Article
Chemistry, Analytical
Ana M. Jimenez-Carvelo, Sandra Martin-Torres, Fidel Ortega-Gavilan, J. Camacho
Summary: Conventional PLS-DA and sparse sPLS-DA were effectively used to authenticate avocado samples by analyzing lipid chromatographic fingerprints. The concatenated classification models successfully resolved multiclass problems in food authentication, with performance metrics around 0.95 for both multivariate classification methods.
Article
Food Science & Technology
Sara Leon-Ecay, Ainara Lopez-Maestresalas, Maria Teresa Murillo-Arbizu, Maria Jose Beriain, Jose Antonio Mendizabal, Silvia Arazuri, Carmen Jaren, Phillip D. Bass, Michael J. Colle, David Garcia, Miguel Romano-Moreno, Kizkitza Insausti
Summary: This research aimed to create a model using hyperspectral imaging (HSI) to classify beef samples according to their tenderness degree. Two strategies were used to obtain different textures, and classification models were created using partial least squares discriminant analysis (PLS-DA) method. The results showed that HSI technology combined with chemometrics has the potential to differentiate and classify meat samples based on their textural characteristics.
Article
Energy & Fuels
Tebogo Mphatlalala Mokgehle, Ntakadzeni Edwin Madala, Wilson Mugera Gitari, Nikita Tawanda Tavengwa
Summary: The study aimed at optimizing extraction techniques for solasonine and solamargine from Solanum mauritianum biomass. The one-pot microwave-assisted aqueous two-phase extraction (MA-ATPE) method showed the highest yields of both compounds, indicating its potential for efficient extraction of medicinally important metabolites from plant biomass.
BIOMASS CONVERSION AND BIOREFINERY
(2021)
Article
Agriculture, Multidisciplinary
Judith Ssali Nantongo, Samuel Edgar Tinyiro, Mariam Nakitto, Edwin Serunkuma, Prossy Namugga, Oluwatoyin Ayetigbo, Sarah Mayanja, Mukani Moyo, Reuben Ssali, Thiago Mendes
Summary: This study aims to improve the acceptance, adoption, and discrimination of potato genotypes by considering the preferences of end users. The priority quality traits of boiled potatoes were determined using the G+ tool, and instrument-based texture parameters were found to be significantly associated with sensory attributes. Near-infrared spectroscopy shows strong potential to predict potato color.
JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE
(2023)
Article
Chemistry, Multidisciplinary
Maria Lasalvia, Vito Capozzi, Giuseppe Perna
Summary: Vibrational spectroscopy combined with multivariate analysis techniques has considerable potential for establishing reliable diagnostic models.
APPLIED SCIENCES-BASEL
(2022)
Article
Horticulture
J. Villena, C. Moreno, S. Rosello, J. Beltran, J. Cebolla-Cornejo, M. M. Moreno
Summary: This study used the Spanish variety Moruno as a model to investigate the relationship between sensory perception and fruit composition in tomato landraces. By growing 30 different populations in various environments and evaluating them through a consumer panel, partial least square models were developed to identify the relationships between determinant flavor descriptors and compositional variables. The study provided new insights that were not uncovered by previous analyses and identified populations with a good combination of yield and sensory traits.
SCIENTIA HORTICULTURAE
(2023)
Article
Chemistry, Multidisciplinary
Steve Tsham Mpinda Ataky, Diego Saqui, Jonathan de Matos, Alceu de Souza Britto Junior, Alessandro Lameiras Koerich
Summary: This paper applies the Gaussian-Laplacian pyramid to treat different spatial frequency bands of a texture and aggregates features extracted from gray and color texture images using various texture descriptors. Experimental results demonstrate the advantages of the proposed method and emphasize the importance of multiscale image analysis.
APPLIED SCIENCES-BASEL
(2023)
Article
Chemistry, Applied
Laurence Souza Vieira, Camila Assis, Maria Eliana Lopes Ribeiro de Queiroz, Antonio Augusto Neves, Andre Fernando de Oliveira
Summary: This study successfully developed a model using FT-NIR and PLS-DA to efficiently distinguish the authenticity of extra virgin olive oil and differentiate adulterated samples. Different models showed strong performance in classifying olive oils and various types of adulterants, with high accuracy and specificity values. Reliable and robust models were built allowing for differentiation between seven adulterants and genuine extra virgin olive oils.
Article
Chemistry, Analytical
Juliana Melo Duarte, Nadia Gabrielle Silva Sales, Jez Willian Batista Braga, Candice Bridge, Mark Maric, Marcelo Henrique Sousa, Juliano de Andrade Gomes
Summary: The aim of this study was to develop a methodology to distinguish automotive paint samples based on the make of the vehicle and its color shade. In-situ analysis of 143 white samples was conducted using Fourier transform infrared spectroscopy and coupled microscopy. Principal component analysis and partial least squares discriminant analysis were used for data analysis, resulting in high classification accuracy.
Article
Spectroscopy
Hao Yuan, Cailing Liu, Hongying Wang, Liangju Wang, Lei Dai
Summary: This study demonstrates that Vis-NIR spectroscopy can be used to distinguish the gestational sac from other abdominal tissues in rabbits. The raw spectra of tissues were analyzed using PCA and pre-processed using various techniques. The results show that the combination of Vis-NIR spectroscopy and PLS-DA can effectively discriminate the gestational sac from other abdominal tissues.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2022)
Article
Engineering, Chemical
D. Castro-Reigia, I. Garcia, S. Sanllorente, L. A. Sarabia, J. M. Amigo, M. C. Ortiz
Summary: This study aims to develop an efficient technology using near infrared spectroscopy and partial least squares discriminant analysis to determine the fermentation state of bread loaves in the bakery industry. A new methodology is proposed to replicate the knowledge of a Master Baker through a NIR spectrometer. The results demonstrate high sensitivity and specificity in predicting the fermentation state of dough.
JOURNAL OF FOOD ENGINEERING
(2024)
Article
Food Science & Technology
Marina De Gea Neves, Ronei Jesus Poppi, Marcia Cristina Breitkreitz
Summary: The study developed a non-invasive and rapid method using NIR and chemometric tools to determine the authenticity of plant-based protein powders and classify possible adulterations. By combining OC-PLS for authentication and PLS2-DA for adulterant classification, the methodology showed high sensitivity and specificity in detecting adulterants such as soy, whey, and wheat in the protein powders.
Article
Food Science & Technology
Lilija Duckena, Reinis Alksnis, Ieva Erdberga, Ina Alsina, Laila Dubova, Mara Duma
Summary: In this study, visible and near-infrared (Vis-NIR) spectroscopy was used to analyze the internal quality attributes of tomatoes. The results showed that Vis-NIR spectroscopy can accurately predict the taste index, lycopene, flavonoids, beta-carotene, total phenols, and dry matter content of tomatoes.
Article
Environmental Sciences
Shenelle Lottering, Paramu Mafongoya, Romano Lottering
Summary: Under changing climatic conditions, drought has become more frequent in Sub Saharan Africa. This study tested a newly proposed Temperature-Vegetation Water Stress Index (T-VWSI) using Landsat data and found that 2016 experienced the most severe drought. SPI was used to confirm the findings of the T-VWSI index and identified 2016 as a year of severe drought in uMsinga.
GEOCARTO INTERNATIONAL
(2022)
Article
Environmental Sciences
M. N. M. Buthelezi, R. T. Lottering, S. T. Hlatshwayo, K. Peerbhay
Summary: This study explored the utilization of rotation forests and extreme gradient boosting machine learning algorithms to classify drought damage in commercial forests in KwaZulu-Natal. The results demonstrate that both algorithms are capable of accurately detecting trees with drought damage and those without, especially when using conditional drought indices.
GEOCARTO INTERNATIONAL
(2022)
Article
Environmental Sciences
Bongokuhle Sibiya, Romano Lottering, John Odindi
Summary: Commercial forest species discrimination using second-order image texture combinations showed better accuracy with the SPLS-DA model than the PLS-DA model. The study demonstrates the value of second-order image texture combinations in discriminating commercial forest species.
GEOCARTO INTERNATIONAL
(2022)
Article
Green & Sustainable Science & Technology
Rodney T. Muringai, Paramu Mafongoya, Romano T. Lottering, Raymond Mugandani, Denver Naidoo
Summary: Approximately one-third of the global population suffering from chronic hunger are in sub-Saharan Africa. Fish, as a source of animal protein and essential micronutrients, plays a crucial role in improving food and nutrition security. Policymakers and development agencies should recognize the importance of the fisheries sector in combating hunger and undernutrition.
Article
Remote Sensing
Kabir Peerbhay, Ilaria Germishuizen, Romano Lottering, Rowan Naicker
Summary: This study successfully used Landsat 8 multispectral satellite imagery to monitor canopy defoliation caused by Uromycladium acacia (wattle rust) in black wattle plantations. The study demonstrated the effectiveness and cost-effectiveness of using multispectral remote sensing methodologies, specifically the Gradient Boosting Machine approach, for repeatable forest health monitoring in commercial forest plantations.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2022)
Article
Green & Sustainable Science & Technology
Rodney Tatenda Muringai, Paramu Mafongoya, Romano Trent Lottering
Summary: This study assesses fishers' perceptions of climate change and their adaptation strategies in the Zambezi River Basin. The findings reveal that fishers have observed changes in temperature and rainfall trends, which they believe have led to a decline in fish productivity and catches. To cope with this, fishers have adopted adaptation strategies such as changing fishing gear, targeting new fish species, and increasing fishing efforts.
Article
Geography
S. J. Lottering, P. Mafongoya, R. T. Lottering
Summary: Drought is a complex phenomenon that affects vulnerable communities globally, particularly small-scale farmers and rural communities. The study showed that individuals from different socio-economic backgrounds have different perceptions and adaptation strategies towards drought.
SOUTH AFRICAN GEOGRAPHICAL JOURNAL
(2023)
Article
Environmental Sciences
Mthokozisi Ndumiso Mzuzuwentokozo Buthelezi, Romano Trent Lottering, Sizwe Thamsanqa Hlatshwayo, Kabir Yunus Peerbhay
Summary: Southern African countries are prone to droughts and pest outbreaks, which significantly affect forest productivity. This study utilized machine learning algorithms and remote sensing data to effectively classify drought-damaged trees, providing a method for drought monitoring and management in high rainfall forest regions.
REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT
(2022)
Article
Forestry
Regardt Ferreira, Kabir Peerbhay, Josua Louw, Ilaria Germishuizen, Andrew Morris, Romano Lottering
Summary: Commercial forest plantations in South Africa are vulnerable to various risks and require intensive management. This study examines the use of deep learning neural networks to detect damage caused by baboons in pine plantations. By using high-resolution imagery from Dove nanosatellites, the study achieved accurate mapping of damage severity at the tree level.
SOUTHERN FORESTS-A JOURNAL OF FOREST SCIENCE
(2023)
Review
Chemistry, Multidisciplinary
Nokukhanya Mthembu, Romano Lottering, Heyns Kotze
Summary: This paper reviews the remote sensing methods for estimating leaf area index (LAI) across different forest ecosystems, crops, and grasslands in terms of remote sensing platforms, sensors, and models. The results show that remote sensing has been widely used for LAI estimation and mapping in crops and natural forests during the last decade, but there is still a lack of research in commercial forests and grasslands. Among the 84 studies related to forests, 60 were related to natural forests and 24 were related to commercial forests. Empirical models were most commonly used for estimating forest LAI, followed by physical models.
APPLIED SCIENCES-BASEL
(2023)
Article
Multidisciplinary Sciences
Eskinder Gidey, Solomon Gitet, Paidamwoyo Mhangara, Oagile Dikinya, Solomon Hishe, Atkilt Girma, Gidey Gebremeskel, Romano Lottering, Amanuel Zenebe, Emiru Birhane
Summary: This study aimed to analyze the patterns of urban and peri-urban expansion and its impact on arable land. The findings revealed that urban and peri-urban lands increased while arable land decreased. This research provides important information for urban planners and decision makers.
SN APPLIED SCIENCES
(2023)
Article
Multidisciplinary Sciences
Kimara Moodley, Michele L. Toucher, Romano T. Lottering
Summary: Due to human activities, the earth's surface is constantly changing through Land-use/cover change (LULCC), which is a major driver of global, regional and local environmental change. This study aimed to understand the historical and current spatial-temporal variability of LULCC and its connection to future land-use change in Southern Africa. Using a spatially distributed, empirical land-use modelling approach, the study simulated future land-use change in the uThukela and uMngeni catchments in South Africa.
SCIENTIFIC AFRICAN
(2023)
Article
Multidisciplinary Sciences
Kabir Peerbhay, Samuel Adelabu, Romano Lottering, Leeth Singh
Summary: This study investigated the potential of using a multispectral sensor to remotely detect and map carbon content in a mountainous rural rangeland in South Africa. The results showed that the SPOT 5 satellite, combined with ensemble models, can effectively map carbon across the rangeland. The study also identified the most effective spectral bands for carbon mapping.
SCIENTIFIC AFRICAN
(2022)
Review
Fisheries
Rodney Tatenda Muringai, Paramu Mafongoya, Romano Trent Lottering
Summary: Sub-Saharan Africa's freshwater fisheries play a crucial role in the lives and food security of millions of people in the region. However, these fisheries are threatened by overfishing, illegal fishing, pollution, and climate change. This study examines the impact of climate change on freshwater fisheries in the region, as well as the adaptation strategies employed by fishing communities and management efforts to address the issue. Climate change has led to increased water temperatures, altered hydrological processes, and higher levels of pollutants, negatively affecting fish physiology and the well-being of fishing-dependent communities. To cope with fluctuating fish resources, fishing communities have diversified their livelihoods, changed fishing gear, increased fishing efforts, and targeted new species. Management measures have also been implemented at local and regional levels to enhance the sustainability of fish resources. The study recommends the involvement of resource users in policy formulation to promote climate change adaptation and the resilience of freshwater fisheries for sustainable development.
Article
Environmental Sciences
Kiara Brewer, Romano Lottering, Kabir Peerbhay
Summary: The presence of invasive alien plants has a significant impact on ecosystems, affecting productivity and biodiversity. This study demonstrates the utility of remote sensing techniques and machine learning algorithms in detecting and mapping invasive alien wattle.
REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT
(2022)