In vitro micropropagation of Musa sapientum L. (Cavendish Dwarf)

A complete protocol for micropropagation of Musa sapientum using shoot meristems was developed. Multiple shoots were induced in vitro from shoot meristems. Murashige and Skoog’s medium supplemented with BAP and NAA (3.0 + 0.2 mg/l, respectively) was found to be most suitablecombination. Further multiplication of shoots required habituation of cultures up to 3 passages of 21 days each on the same medium after establishment of culture and initiation of shoot buds. Thereafter 3-fold multiplication rate was achieved during every subculture. For rooting the shoots were excised and transferred to same medium. Rooted plantlets were then transferred to primary and secondary hardening and grown in the green house. These hardened plants have been successfully established insoil

In vitro micropropagation of orchid, Oncidium sp. (Dancing Dolls)

A successful procedure was established for in vitro mass multiplication of orchid (Oncidium sp.). In vitro regeneration multiplication and rooting of plantlets were achieved from the immature seeds on Murashige and Skoog's medium supplemented with BAP (2.0 mg/l). Rooted plantlets were then transferred to perforated plastic pots and grown in the green house

Inorganic Fertilizer Use and Its Association With Rice Yield Gaps in Sub-Saharan Africa

Where and which countries should receive higher priority for improving inorganic fertilizer use in rice fields in sub-Saharan Africa (SSA)? This study addressed this question by assessing the spatial variation in fertilizer use and its association with rice yield and yield gap in 24 SSA countries through a systematic literature review of peer-reviewed papers, theses, and grey literature published between 1995 and 2021. The results showed a large variation in N, P, and K fertilizer application rates and rice yield and an opportunity for narrowing the yield gap by increasing N and P rates, especially in irrigated rice systems. We identified clusters of sites/countries based on nutrient input and yield and suggested research and development strategies for improving yields and optimizing nutrient use efficiencies. Further research is essential to identify the factors causing low fertilizer use and the poor association between its use and yield in rainfed systems

Status quo and challenges of rice production in sub-Saharan Africa

Rice production in sub-Saharan Africa (SSA) has increaed ten-fold since 1961, whereas its consumption has exceeded the production and the regional self-sufficiency rate is only 48% in 2020. Increase in rice production has come mainly from increased harvested area. Yield increase has been limited and the current average yield in SSA is around 2 t ha−1. This paper aims to provide the status quo of (i) current rice production and its challenges, (ii) selected achievements in rice agronomy research mainly by the Africa Rice Center and its partners, and (iii) perspectives for future research on rice agronomy in SSA. The major problems confronting rice production include low yield in rainfed environments, accounting for 70% of the total rice harvested area. Rainfed rice yields are strongly affected by climate extremes such as water stresses, soil-related constraints, and sub-optimum natural resource management and crop management practices by smallholder farmers including poor water management, and suboptimal use of fertilizers, herbicides, and machineries. For alleviating these constraints, a wide range of technologies have been developed and introduced over the last three decades. These include water conservation technologies in rainfed and irrigated lowland rice, site-specific nutrient management practices, decision support tools such as crop growth simulation models, and labor-saving technologies. We conclude that further research efforts are needed to develop locally adapted agronomic solutions for sustainable intensification, especially in rainfed rice to enhance the resilience to climate change and increase land and labor productivity and sustainability of rice cultivation in SSA

Estimating nutrient concentrations and uptake in rice grain in sub-Saharan Africa using linear mixed-effects regression

Context or problem Quantification of nutrient concentrations in rice grain is essential for evaluating nutrient uptake, use efficiency, and balance to develop fertilizer recommendation guidelines. Accurate estimation of nutrient concentrations without relying on plant laboratory analysis is needed in sub-Saharan Africa (SSA), where farmers do not generally have access to laboratories. Objective or research question The objectives are to 1) examine if the concentrations of macro- (N, P, K, Ca, Mg, S) and micronutrients (Fe, Mn, B, Cu) in rice grain can be estimated using agro-ecological zones (AEZ), production systems, soil properties, and mineral fertilizer application (N, P, and K) rates as predictor variables, and 2) to identify if nutrient uptakes estimated by best-fitted models with above variables provide improved prediction of actual nutrient uptakes (predicted nutrient concentrations x grain yield) compared to average-based uptakes (average nutrient concentrations in SSA x grain yield). Methods Cross-sectional data from 998 farmers’ fields across 20 countries across 4 AEZs (arid/semi-arid, humid, sub-humid, and highlands) in SSA and 3 different production systems: irrigated lowland, rainfed lowland, and rainfed upland were used to test hypotheses of nutrient concentration being estimable with a set of predictor variables among above-cited factors using linear mixed-effects regression models. Results All 10 nutrients were reasonably predicted [Nakagawa’s R2 ranging from 0.27 (Ca) to 0.79 (B), and modeling efficiency ranging from 0.178 (Ca) to 0.584 (B)]. However, only the estimation of K and B concentrations was satisfactory with a modeling efficiency superior to 0.5. The country variable contributed more to the variation of concentrations of these nutrients than AEZ and production systems in our best predictive models. There were greater positive relationships (up to 0.18 of difference in correlation coefficient R) between actual nutrient uptakes and model estimation-based uptakes than those between actual nutrient uptakes and average-based uptakes. Nevertheless, only the estimation of B uptake had significant improvement among all nutrients investigated. Conclusions Our findings suggest that with the exception of B associated with high model EF and an improved uptake over the average-based uptake, estimates of the macronutrient and micronutrient uptakes in rice grain can be obtained simply by using average concentrations of each nutrient at the regional scale for SSA. Implications Further investigation of other factors such as the timing of fertilizer applications, rice variety, occurrence of drought periods, and atmospheric CO2 concentration is warranted for improved prediction accuracy of nutrient concentrations