Cassava whitefly, Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae), in sub-Saharan African farming landscapes: a review of the factors determining abundance

Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) is a pest species complex that causes widespread damage to cassava, a staple food crop for millions of smallholder households in Sub-Saharan Africa. Species in the complex cause direct feeding damage to cassava and are the vectors of multiple plant viruses. Whilst significant work has gone into developing virus-resistant cassava cultivars, there has been little research effort aimed at understanding the ecology of these insect vectors. In this review we critically assess the knowledge base relating to factors that may lead to high population densities of Sub-Saharan African (SSA) Bemisia tabaci species in cassava production landscapes of East Africa. We focus first on empirical studies that have examined biotic or abiotic factors that may lead to high populations. We then identify knowledge gaps that need to be filled to deliver long-term sustainable solutions to manage both the vectors and the viruses that they transmit. We found that whilst many hypotheses have been put forward to explain the increases in abundance witnessed since the early 1990s, there are little available published data and these tend to have been collected in a piecemeal manner. The most critical knowledge gaps identified were: (i) understanding how cassava cultivars and alternative host plants impact B. tabaci population dynamics and its natural enemies; (ii) the impact of natural enemies in terms of reducing the frequency of outbreaks and (iii) the use and management of insecticides to delay or avoid the development of resistance. In addition, there are several fundamental methodologies that need to be developed and deployed in East Africa to address some of the more challenging knowledge gaps

Quantum-Key Distribution With Vector Modes

High-dimensional encoding using higher degrees of freedom has become topical in quantum communication protocols. When taking advantage of entanglement correlations, the state space can be made even larger. Here, we exploit the entanglement between two dimensional space and polarization qubits, to realize a four-dimensional quantum key distribution protocol. This is achieved by using entangled states as a basis, analogous to the Bell basis, rather than typically encoding information on individual qubits. The encoding and decoding in the required complementary bases is achieved by manipulating the Pancharatnam-Berry phase with a single optical element: a q-plate. Our scheme shows a transmission fidelity of 0.98 and secret key rate of 0.9 bits per photon. While the use of only static elements is preferable, we show that the low secret key rate is a consequence of the filter based detection of the modes, rather than our choice of encoding modes

Nature and dynamics of climate variability in the uganda cattle corridor

The study was conducted in the districts of Nakaseke and Nakasongola stratified into four farming systems of crop dominancy, pastoralists, mixed crop and livestock and fishing. The study was guided by two research questions: (1) how do community residents perceive climate change/variability? (2) What is the trend and nature of climate variability and how does it compare with people’s perceptions? Ninety eight percent (98%) of the respondents reported that the routine patterns of weather and climate had changed in the last 5 to 10 years and it has become less predictable with sunshine hours being extended and rainfall amounts being reduced. This compared well with the analyzed secondary data. Over 78% respondents perceived climate change and variability to be caused by tree cutting other than the known scientific reasons like increase in industrial fumes or increased fossil fuel use. Climate data showed that over the period 1961 to 2010 the number of dry spells within a rainfall season had increased with the most significant increase observed in the first rainfall season of March to May as compared to the season of September to November. The first dry season of June/July to August is short while the second dry season of December to February is long during the study period. The two rainfall seasons of March to May and September to November seem to be merging into one major season from May to November. Temperature data shows a significant increasing trend in mean annual temperatures with the most increase observed in the mean annual minimum temperatures than the maximum temperatures.Key words: Climate variability, community perceptions, Uganda cattle corridor, dry spells

Introduction of household biogas digesters in rural farming households of the Maluti-a-Phofung municipality, South Africa

The study aimed to introduce biogas as an alternative source of energy for rural cattle farmers in the Maluti-a-Phofung municipality in the Free State Province, South Africa. To augment the rural farming community’s adoption of the biodigester technology the following initiatives were undertaken: (i) a situational analysis (or diagnostic survey); (ii) training on biogas production in an integrated crop-livestock-bioenergy system; (iii) installation of the biodigesters; and (iv) monitoring and evaluation of the biogas production. Results on the diagnostic survey showed that the main source of energy for cooking was wood in all the farms and availability of water was not a constraint. Prefabricated biodigesters of 6m3 -12m3 were installed in all the households and, after continual feeding of the units with cattle dung, the production of biogas increased gradually. Monitoring of biogas production showed that, in two-thirds of the households, 80% of their cooking needs were met in summer, while in winter biogas production was minimal due to extremely cold weather. Challenges faced included non-adherence to a feeding regime – resulting in a blockage of the biodigester – and lack of feeding. Generally, farmers in the study area showed a high appreciation of the biodigester technology

Photonic quantum information processing: a review

Photonic quantum technologies represent a promising platform for several applications, ranging from long-distance communications to the simulation of complex phenomena. Indeed, the advantages offered by single photons do make them the candidate of choice for carrying quantum information in a broad variety of areas with a versatile approach. Furthermore, recent technological advances are now enabling first concrete applications of photonic quantum information processing. The goal of this manuscript is to provide the reader with a comprehensive review of the state of the art in this active field, with a due balance between theoretical, experimental and technological results. When more convenient, we will present significant achievements in tables or in schematic figures, in order to convey a global perspective of the several horizons that fall under the name of photonic quantum information.Comment: 36 pages, 6 figures, 634 references. Updated version with minor changes and extended bibliograph

A method for real-time classification of insect vectors of mosaic and brown streak disease in cassava plants for future implementation within a low-cost, handheld, in-field multispectral imaging sensor

Background The paper introduces a multispectral imaging system and data-processing approach for the identification and discrimination of morphologically indistinguishable cryptic species of the destructive crop pest, the whitefly Bemisia tabaci. This investigation and the corresponding system design, was undertaken in two phases under controlled laboratory conditions. The first exploited a prototype benchtop variant of the proposed sensor system to analyse four cryptic species of whitefly reared under similar conditions. The second phase, of the methodology development, employed a commercial high-precision laboratory hyperspectral imager to recover reference data from five cryptic species of whitefly, immobilized through flash freezing, and taken from across four feeding environments. Results The initial results, for the single feeding environment, showed that a correct species classification could be achieved in 85–95% of cases, utilising linear Partial Least Squares approaches. The robustness of the classification approach was then extended both in terms of the automated spatial extraction of the most pertinent insect body parts, to assist with the spectral classification model, as well as the incorporation of a non-linear Support Vector Classifier to maintain the overall classification accuracy at 88–98%, irrespective of the feeding and crop environment. Conclusion This study demonstrates that through an integration of both the spatial data, associated with the multispectral images being used to separate different regions of the insect, and subsequent spectral analysis of those sub-regions, that B. tabaci viral vectors can be differentiated from other cryptic species, that appear morphologically indistinguishable to a human observer, with an accuracy of up to 98%. The implications for the engineering design for an in-field, handheld, sensor system is discussed with respect to the learning gained from this initial stage of the methodology development

Effects of cassava mosaic virus disease on the growth and yield of cassava - some highlights from Makerere experiments

(African Crop Science Journal 1999 7(4): 511-522