Remote sensing applications for monitoring the spatial distribution of Bracken fern (Pteridium) in the Cathedral Peak : Drakensberg, South Africa.

Abstract available in PDF file

Estimating and monitoring land surface phenology in rangelands: A review of progress and challenges

Land surface phenology (LSP) has been extensively explored from global archives of satellite observations to track and monitor the seasonality of rangeland ecosystems in response to climate change. Long term monitoring of LSP provides large potential for the evaluation of interactions and feedbacks between climate and vegetation. With a special focus on the rangeland ecosystems, the paper reviews the progress, challenges and emerging opportunities in LSP while identifying possible gaps that could be explored in future. Specifically, the paper traces the evolution of satellite sensors and interrogates their properties as well as the associated indices and algorithms in estimating and monitoring LSP in productive rangelands. Findings from the literature revealed that the spectral characteristics of the early satellite sensors such as Landsat, AVHRR and MODIS played a critical role in the development of spectral vegetation indices that have been widely used in LSP applications. The normalized difference vegetation index (NDVI) pioneered LSP investigations, and most other spectral vegetation indices were primarily developed to address the weaknesses and shortcomings of the NDVI. New indices continue to be developed based on recent sensors such as Sentinel-2 that are characterized by unique spectral signatures and fine spatial resolutions, and their successful usage is catalyzed with the development of cutting-edge algorithms for modeling the LSP profiles. In this regard, the paper has documented several LSP algorithms that are designed to provide data smoothing, gap filling and LSP metrics retrieval methods in a single environment

Predicting zinc-enhanced maize hybrid performance under stress conditions

The low yield potential of most biofortified maize is a barrier to its full adoption and reduces its potential to curb various macro- and micronutrient deficiencies highly prevalent in low-income regions of the world, such as sub-Saharan Africa (SSA). By crossing biofortified inbred lines with different nutritional attributes such as zinc (Zn), provitamin A and protein quality, breeders are attempting to develop agronomically superior and stable multi-nutrient maize of different genetic backgrounds. A key question, however, is the relationship between the biofortified inbred lines per se and hybrid performance under stress and non-stress conditions. In this study, inbred line per se and testcross performance were evaluated for grain yield and secondary traits of Zn-enhanced normal, provitamin A and quality protein maize (QPM) hybrids and estimated heterosis under combined heat and drought (HMDS) and well-watered (WW) conditions. Responses of all secondary traits, except for the number of days to mid-anthesis, significantly differed for HMDS and WW conditions. The contribution of heterosis to grain yield was highly significant under both management levels, although higher mid and high-parent heterosis was observed under WW than HMDS conditions. However, the findings suggest that inbred line performance was the best determinant of hybrid performance under HMDS. Strong correlations were observed between grain yield and secondary traits for both parents and hybrids, and between secondary traits of inbred lines and hybrids under both management levels, indicating that hybrid performance can be predicted based on intrinsic inbred line performance. Phenotypic correlation between grain yield of inbred lines and hybrids was higher under HMDS than WW conditions. This study demonstrated that under HMDS conditions, performance of Zn-enhanced hybrids could be predicted based on the performance of their corresponding inbred lines. However, the parental inbred lines should be systematically selected for desirable secondary traits correlated with HMDS tolerance during inbred line development

Combining ability and testcross performance of multi-nutrient maize under stress and non-stress environments

While significant progress has been made by several international breeding institutions in improving maize nutritional quality, stacking of nutritional traits like zinc (Zn), quality protein, and provitamin A has not received much attention. In this study, 11 newly introduced Zn-enhanced inbred lines were inter-mated with seven testers from normal, provitamin A and quality protein maize (QPM) nutritional backgrounds in order to estimate the general combining ability (GCA) and specific combining ability (SCA) for grain yield (GY) and secondary traits under stress conditions [(combined heat and drought stress (HMDS) and managed low nitrogen (LN)] and non-stress conditions [(summer rainfed; OPT) and well-watered (irrigated winter; WW)] in Zimbabwe. Lines L6 and L7 had positive GCA effects for GY and secondary traits under OPT and LN conditions, and L8 and L9 were good general combiners for GY under HMDS conditions. Superior hybrids with high GY and desirable secondary traits were identified as L10/T7 and L9/T7 (Zn x normal), L2/T4, L4/T4, L3/T5 (Zn x provitamin A), and L8/T6 and L11/T3 (Zn x QPM), suggesting the possibility of developing Zn-enhanced hybrids with high yield potential using different nutritional backgrounds. Both additive and dominance gene effects were important in controlling most of the measured traits. This suggests that selecting for desirable traits during inbred line development followed by hybridization and testing of specific crosses under different management conditions could optimize the breeding strategy for stacked nutritionally-enhanced maize genotypes

Remote sensing hail damage on maize crops in smallholder farms using data acquired by remotely piloted aircraft system

Smallholder farmers reside in marginal environments typified by dryland maize-based farming systems. Despite the significant contribution of smallholder farmers to food production, they are vulnerable to extreme weather events such as hailstorms, floods and drought. Extreme weather events are expected to increase in frequency and intensity under climate change, threatening the sustainability of smallholder farming systems. Access to climate services and information, as well as digital advisories such as Robust spatially explicit monitoring techniques from remotely piloted aircraft systems (RPAS), could be instrumental in understanding the impact and extent of crop damage. It could assist in providing adequate response mechanisms suitable for bolstering crop productivity in a spatially explicit manner. This study, therefore, sought to evaluate the utility of drone-derived multispectral data in estimating crop productivity elements (Equivalent water thickness (EWT), Chlorophyll content, and leaf area index (LAI)) in maize smallholder croplands based on the random forest regression algorithm. A hailstorm occurred in the study area during the reproductive stages 2 to 3 and 3 to 4. EWT, Chlorophyll content, and LAI were measured before and after the storm. Results of this study showed that EWT, Chlorophyll content, and LAI could be optimally estimated based on the red edge and its spectral derivatives. Specifically, EWT was estimated to a rRMEs 2.7% and 59%, RMSEs of 5.31 gm−2 and 27.35 gm-2, R2 of 0.88 and 0.77, while chlorophyll exhibited rRMSE of 28% and 25%, RMSEs of 87.4 µmol m−2 and 76.2 µmol m−2 and R2 of 0.89 and 0.80 and LAI yielded a rRMSE of 10.9% and 15.2%, RMSEs of 0.6 m2/m2 and 0.19 m2/m2 before and after the hail damage, respectively. Overall, the study underscores the potential of RPAS-based remote sensing as a valuable resource for assessing crop damage and responding to the impact of hailstorms on crop productivity in smallholder croplands. This offers a means to enhance agricultural resilience and adaptability under climate change

Genetic trends in the Zimbabwe’s national maize breeding program over two decades

Monitoring genetic gains within breeding programs is a critical component for continuous improvement. While several national breeding programs in Africa have assessed genetic gain using era studies, this study is the first to use two decades of historical data to estimate genetic trends within a national breeding program. The objective of this study was to assess genetic trends within the final two stages of Zimbabwe’s Department of Research & Specialist Services maize breeding pipeline between 2002 and 2021. Data from 107 intermediate and 162 advanced variety trials, comprising of 716 and 398 entries, respectively, was analyzed. Trials were conducted under optimal, managed drought stress, low nitrogen stress, low pH, random stress, and disease pressure (maize streak virus (MSV), grey leaf spot (GLS), and turcicum leaf blight under artificial inoculation. There were positive and significant genetic gains for grain yield across management conditions (28–35 kg ha-1 yr-1), under high-yield potential environments (17–61 kg ha-1 yr-1), and under low-yield potential environments (0–16 kg ha-1 yr-1). No significant changes were observed in plant and ear height over the study period. Stalk and root lodging, as well as susceptibility to MSV and GLS, significantly decreased over the study period. New breeding technologies need to be incorporated into the program to further increase the rate of genetic gain in the maize breeding programs and to effectively meet future needs

Estimating and monitoring the phenological cycle of bracken fern (Pteridium aquilinum) using remote sensing.

Doctoral Degree. University of KwaZulu-Natal, Pietermaritzburg.Abstract available in PDF

Genotype x environment interaction and yield stability of normal and biofortified maize inbred lines in stress and non-stress environments

AbstractBreeding for nutrient-dense maize cultivars is reliant on introductions of exotic inbred lines enhanced with high levels of the targeted nutrients. Sometimes, the exotic nutrient donor germplasm may not adapt well in new growing environments, thereby reducing seed production when used in hybrid combinations. Therefore, evaluating introduced trait donors for adaptation, through genotype × environment interaction (GEI) analysis is crucial in breeding for quality traits. The objectives of this study were to (i) evaluate grain yield performance of introduced zinc-enhanced, provitamin A, normal and quality protein maize lines across stress and non-stress environments in Zimbabwe, (ii) assess the presence of GEI and (iii) identify high yielding and stable lines that could be used for developing Zn-enhanced hybrids with improved seed producibility. Additive main effects and multiplicative interaction (AMMI) and genotype plus genotype × environment interaction (GGE) biplot analyses were used for stability analysis. GEI effects were highly significant (P ≤ 0.01) for grain yield. Grain yields for the inbred lines ranged from 1.28 to 3.5 t ha−1. The Zn donor G11 (ITZN313) had the highest grain yield of 3.5 t ha−1 across environments, whereas the normal check G24 (CZL1111) had the lowest grain yield. G2 (CLWQHZN14), G4 (CLWQHZN19), G8 (OBATANPA6), G11 (ITZN313) and G18 (CML546) were stable and high yielding and can be used for developing Zn-enhanced hybrids. Five mega-environments were identified, clearly separating stress and non-stress environments. E11 (Chisumbanje WW) was the most discriminating and representative test environment and could be used to identify superior genotypes

Detection and mapping of bracken fern weeds using multispectral remotely sensed data: a review of progress and challenges

Bracken fern is one of the major invasive plants distributed all over the world currently threatening socio-economic and ecological systems due to its ability to swiftly colonize landscapes. The study aimed at reviewing the progress and challenges in detecting and mapping of bracken fern weeds using different remote sensing techniques. Evidence from literature have revealed that traditional methods such as field surveys and modelling have been insufficient in detecting and mapping the spatial distribution of bracken fern at a regional scale. The applications of medium spatial resolution sensors have been constrained by their limited spatial, spectral and radiometric capabilities in detecting and mapping bracken fern. On the other hand, the availability of most of these data-sets free of charge, large swath width and their high temporal resolution have significantly improved remote sensing of bracken fern. The use of commercial satellite data with high resolution have also proven useful in providing fine spectral and spatial resolution capabilities that are primarily essential to offer precise and reliable data on the spatial distribution of invasive species. However, the application of these data-sets is largely restricted to smaller areas, due to high costs and huge data volumes. Studies on bracken fern classification have extensively adopted traditional classification methods such as supervised maximum likelihood classifier. In studies where traditional methods performed poorly, the combination of soft classifiers such as super resolution analysis and traditional methods of classification have shown an improvement in bracken fern classification. Finally, since high spatial resolution sensors are expensive to acquire and have small swath width, the current study recommends that future research can also consider investigating the utility of the freely available recently launched sensors with a global footprint that has the potential to provide invaluable information for repeated measurement of invasive species over time and space

Multinutrient Biofortification of Maize (Zea mays L.) in Africa: Current Status, Opportunities and Limitations

Macro and micronutrient deficiencies pose serious health challenges globally, with the largest impact in developing regions such as subSaharan Africa (SSA), Latin America and South Asia. Maize is a good source of calories but contains low concentrations of essential nutrients. Major limiting nutrients in maize-based diets are essential amino acids such as lysine and tryptophan, and micronutrients such as vitamin A, zinc (Zn) and iron (Fe). Responding to these challenges, separate maize biofortification programs have been designed worldwide, resulting in several cultivars with high levels of provitamin A, lysine, tryptophan, Zn and Fe being commercialized. This strategy of developing single-nutrient biofortified cultivars does not address the nutrient deficiency challenges in SSA in an integrated manner. Hence, development of maize with multinutritional attributes can be a sustainable and cost-effective strategy for addressing the problem of nutrient deficiencies in SSA. This review provides a synopsis of the health challenges associated with Zn, provitamin A and tryptophan deficiencies and link these to vulnerable societies; a synthesis of past and present intervention measures for addressing nutrient deficiencies in SSA; and a discussion on the possibility of developing maize with multinutritional quality attributes, but also with adaptation to stress conditions in SSA