RESUMO
Weed competition is the major biological stress affecting cassava production in smallholder farms in West and Central Africa, where yields are low compared with those in Asia and Latin America. Options for improved weed management are crucial in increasing productivity. Selected pre- and post-emergence herbicides, integrated with appropriate tillage and plant spacing, were tested in 96 sites in four locations in Nigeria, 24 in 2016 and 72 in 2017. Trials were split plots with six pre-emergence herbicides and no post-emergence treatment as main plots. Subplot treatments were four post-emergence herbicides, weeding with a motorized rotary weeder, short- and long-handled hoes, and no post-emergence weed control, i.e., regardless of pre-emergence treatments. Indaziflam-based treatments, irrespective of post-emergence treatment, and flumioxazin + pyroxasulfone applied pre-emergence followed by one weeding with a long-handled hoe provided >80% control of major broadleaf and grass weeds. Compared with herbicide use, farmer control practices (53%) were not efficient in controlling weeds. The highest root yield was produced where (1) s-metolachlor was combined with atrazine, and one weeding with a long-handled hoe or clethodim with lactofen, and (2) indaziflam + isoxaflutole was combined with glyphosate. An increase in root yield from 3.41 to 14.2 t ha-1 and from 3.0 to 11.99 t ha-1 was obtained where herbicides were used compared with farmers' practice and manual hoe weeding. Our results showed that integrating good agronomic practices with safe and effective use of appropriate herbicides can result in root yield >20 t ha-1. i.e., twice the national average root yield of 8-12 t ha-1, with >50% net profit. The use of appropriate herbicides can reduce the amount of manual labor required and improve livelihoods, specifically for women and children. Smallholder cassava farmers would require continuous training on the safe use and handling of herbicides to improve efficiency and prevent adverse effects on humans and the environment.
RESUMO
Modern breeding methods integrate next-generation sequencing and phenomics to identify plants with the best characteristics and greatest genetic merit for use as parents in subsequent breeding cycles to ultimately create improved cultivars able to sustain high adoption rates by farmers. This data-driven approach hinges on strong foundations in data management, quality control, and analytics. Of crucial importance is a central database able to (1) track breeding materials, (2) store experimental evaluations, (3) record phenotypic measurements using consistent ontologies, (4) store genotypic information, and (5) implement algorithms for analysis, prediction, and selection decisions. Because of the complexity of the breeding process, breeding databases also tend to be complex, difficult, and expensive to implement and maintain. Here, we present a breeding database system, Breedbase (https://breedbase.org/, last accessed 4/18/2022). Originally initiated as Cassavabase (https://cassavabase.org/, last accessed 4/18/2022) with the NextGen Cassava project (https://www.nextgencassava.org/, last accessed 4/18/2022), and later developed into a crop-agnostic system, it is presently used by dozens of different crops and projects. The system is web based and is available as open source software. It is available on GitHub (https://github.com/solgenomics/, last accessed 4/18/2022) and packaged in a Docker image for deployment (https://hub.docker.com/u/breedbase, last accessed 4/18/2022). The Breedbase system enables breeding programs to better manage and leverage their data for decision making within a fully integrated digital ecosystem.