South African Classification System Research Articles

Numerical soil horizon classification from South Africa’s legacy database

Allocation of soil profiles to one or another soil class depends on the surveyor’s experience and knowledge. Inconsistent class designations can affect the downstream uses of soil information such as hydrological and ecological applications. Therefore, numerical classifications can be useful in creating property-based soil clusters. Quantitative classification of soil horizons can also be beneficial for guiding physicochemical thresholds used in taxonomic criteria. This study aimed at taking a step in applying numerical classification techniques to the South African soil legacy database to quantitatively cluster horizons. For each master horizon, the database was clustered into new “diagnostic” horizons through Partitioning Around Medoids (PAM) implemented in the Clustering Large Applications algorithm (CLARA). This algorithm has the benefit of using multiple subsets of the data making a more reliable initiation of medoids and it is a non-parametric approach making it more robust to outliers. To determine the optimal number of clusters, the silhouette width for 1 through 11 clusters was calculated. The number of clusters with the largest silhouette width was taken as the optimal number of clusters. The results of this study show that for O, E, and G (gleyed) horizons, the algorithm performs relatively well with the first two principle components capturing almost half of the variation in the data. However, for the A, B, and C horizons, the algorithm struggled to separate clusters sufficiently. The A horizon clusters only broadly corresponded to environmental factors (geography, climate, elevation, and geology) and the large clusters straddled numerous taxonomic thresholds. Moreover, the B horizon clusters correspond relatively well with environmental factors. Limitations identified, include bias in geographic location of modal soil profiles of the database, bias in the South African classification system, how to handle non-globular clusters, and outliers which add leverage to the clusters.

Applying the international classification of diseases to perinatal mortality data, South Africa.

ObjectiveTo examine the feasibility of applying the International Classification of Diseases-perinatal mortality (ICD-PM) coding to an existing data set in the classification of perinatal deaths.MethodsOne author, a researcher with a non-clinical public health background, applied the ICD-PM coding system to South Africa’s national perinatal mortality audit system, the Perinatal Problem Identification Program. The database for this study included all perinatal deaths (n = 26 810), defined as either stillbirths (of birth weight > 1000 g and after 28 weeks of gestation) or early neonatal deaths (age 0–7 days), that occurred between 1 October 2013 and 31 December 2016. A clinical obstetrician verified the coding.FindingsThe South African classification system does not include the timing of death; however, under the ICD-PM system, deaths could be classified as antepartum (n = 15 619; 58.2%), intrapartum (n = 3725; 14.0%) or neonatal (n = 7466; 27.8%). Further, the South African classification system linked a maternal condition to only 40.3% (10 802/26 810) of all perinatal deaths; this proportion increased to 68.9% (18 467/26 810) under the ICD-PM system.ConclusionThe main benefit of using the clinically relevant and user-friendly ICD-PM system was an enhanced understanding of the data, in terms of both timing of death and maternal conditions. We have also demonstrated that it is feasible to convert an existing perinatal mortality classification system to one which is globally comparable and can inform policy-makers internationally.

Indigenous soil classification in four villages of eastern South Africa

Ethnopedology has significantly contributed to understanding local perceptions of soil, and its uses and management, and has complemented technical (scientific) surveys. This study focused on indigenous soil classification of the Zulu and Xhosa ethnic groups of eastern South Africa. The study area comprised four villages, viz Khokhwane (104 ha) and Potshini (577 ha) in KwaZulu-Natal Province and Ntshiqo (629 ha) and Zalaze (80 ha) in Eastern Cape Province. Ethnographic methods were used to elicit general local knowledge of soils and ethnopedologic techniques to gain in-depth understanding of soil and theories associated with local taxonomy. Knowledgeable farmers were chosen (upon recommendation and/or based on interest and detail given during interviews) to produce participatory soil maps. These local maps were later compared with scientific soil mapping at 1:10000 scale using a free survey method. Local classification criteria reflected a detailed understanding of soil behaviour, use potential based on long-term observations, and experience with key soil morphological properties such as texture, consistence and colour. Local soil terminology was mostly different for all four villages as well as across ethnic groups. However, some differences between ethnic groups (e.g. Zulu-isibomvu and Xhosa-obomvu; Zulu-ubumba and Xhosa-udongwe) were mainly linguistic and did not indicate inherent differences in soil properties. Terrain features were important for both indigenous and scientific soil classification. Consequently, soil maps produced by local farmers in areas with distinct geomorphic units were generally closely correlated with scientific maps. Although on a floodplain the correlation was poor, the flexibility of the local classification was demonstrated as farmers manipulated the classification criteria to capture changes with distance away from the river. Farmers classified soils at higher levels than the two-tier system of the South African classification and so these could be incorporated as higher categories in the current South African classification system. Irrespective of the level of correlation between scientific and local maps, farmers' local classifications contained detailed pedological information that can contribute to the development of classifications systems that are both user-friendly and relevant for local needs.

Effect of genotype and age on some carcass and meat quality traits of beef carcasses subjected to the South African classification system

Genotype and age effects on pH24, L*, a*, b*, tenderness (WBSF), cooking (CL %), and thawing loss (TL %) of beef carcasses subjected to the South African classification system were determined. Carcass traits (bruising, subcutaneous fat (SF), and conformation) were also measured. Meat quality measurements were taken on the longissimus thoracis et lumborum (n=175) of A, AB, B, and C carcasses from Angus, Bonsmara, Fleckvieh, Non-descript, and Simmental genotypes. No bruises were evident in all carcasses. All carcasses scored medium conformation (class 3) while in SF classification, class 2 had the greatest frequency (66.3%). Genotypic effects (P<0.05) were observed for a*, hue angle (HA), pH24, TL%, CL%, and WBSF between steers with six, seven, and eight incisors. Notable differences (P<0.05) were observed for tenderness where Angus and Simmental had least tender meat while Non-descript and Fleckvieh had the tenderest meat within the C-age class. Meat quality varied within animals of the same age-class across genotypes.

Taxonomic distance between South African diagnostic horizons and the World Reference Base diagnostics

A myriad of soil classifications exist internationally. These usually cater for unique national variations and conditions. These different classification systems, however, hinder international communication. This paper attempted to relate the South African Soil Taxonomic (SAT) soil classification system with the World Reference Base for Soil Resources (WRB) through taxonomic distance classification. A probability matrix of the presence of selected identifiers of the diagnostic elements (properties, horizons, materials) of the South African classification system and the WRB was constructed to determine the taxonomic relationships between them. Euclidean distance calculation on these data enabled numeric expression of the taxonomic similarities and dissimilarities between the South African and WRB diagnostics. Results proved encouraging and some recommendations can be made. For example, a >20% OC family for the organic O, as well as stagnic and gleyic families for the G horizon is proposed. It is further proposed that the WRB consider recognition of red apedal B, yellow-brown apedal B, and lithocutanic B horizons. Since the compared units are the basic building blocks of the two systems, the results presented here can be useful in the relation of soil classification in the South African Soil Taxonomy to the WRB.

Quality related principles of the South African beef classification system in relation to grading and classification systems of the world

This paper addresses the principles related to different grading and classification systems of the world with specific focus on beef quality related outcomes. The paper uses the definitions that classification is a set of descriptive terms describing features of the carcass that are useful as guidelines to those involved in the production, trading and consumption of carcasses, whereas grading is the placing of different values on carcasses for pricing purposes, depending on the market and requirements of traders and consumers. The literature shows that the criteria used in grading systems rank carcasses fairly accurately according to expected eating experience of the loin muscles but not of higher connective tissue cuts of the hind and fore quarter. Criteria used in classification systems give limited descriptions of the quality related characteristics of the carcass. Only the Meat Standards Australia (MSA) cuts based grading system of Australia seeks to define or predict consumer satisfaction with a cooked meal for each cut of the carcass. Its success is based on a palatability assured critical control point (PACCP) approach to satisfy the consumer. However, MSA requires high technical skills, a well organised infrastructure and proper traceability, high level of integrity from different role players and could be very costly, involving high additional personnel cost. The South African classification system should probably focus on distinguishing between young feedlot and somewhat more mature pasture animals with different criteria within each sub category to describe the variation in product quality. Correct pre-slaughter and slaughter management (stress, weight, chilling rate, electrical stimulation, post mortem aging) could improve consistency within age group.

The complexities of conducting ethnographic race research

This paper explores the challenges and dilemmas of conducting ethnographic race research in the context of the South African situation, forming part of my ethnographic race research PhD project, conducted in two historically white, single-sex schools in South Africa. First, it critically examines the theoretical dilemmas on crucial issues of objectivity and subjectivity in conducting ethnographic race research. It then explores the role of gatekeepers in determining who does research in predominantly white educational institutions; and shares the challenging accounts on what it was like to break the invisible barriers of difference in order to build social relationships for the purpose of research in very antagonistic environments. Finally, the paper provides some brief critical reflections. Pseudonyms are used for all the respondents, together with the official South African classification system, which refers to Africans as people of African descent and to whites as people of European descent.

Sources of variation in quality of South African beef: Case studies in relation to the red meat classification system

The South African classification system describes beef carcasses in regard to visual fat cover, conformation and age by dentition. Animal age provides a fairly accurate description of expected eating quality in regard to tenderness in an industry where other sources of variation in tenderness are limited. Since deregulation in the beef industry in the 90s many changes have occurred in all parts of the value chain. This paper presents a number of case studies that focussed on the sources of variation in meat quality, but in particular on sources of changes in meat tenderness over the past two decades. These sources include feeding regime, the use of beta agonists, post mortem ageing and electrical stimulation. In some studies these factors are integrated with age or interactions among two or more of these factors are investigated.Keywords: Age, beef, classification, dentition, grading