Time Series Dataset of Phenology, Biomass, and Chemical Composition of Cassava (Manihot esculenta Crantz) as Affected by Time of Planting and Variety Interactions in Field Trials at Koronivia, Fiji

Poasa Nauluvula, Bruce L. Webber, Roslyn M. Gleadow, William Aalbersberg, John N.G. Hargreaves, Bianca T. Das, Diogenes L. Antille, Steven J. Crimp

Research output: Contribution to journalData articlepeer-review

Abstract

Cassava is the sixth most important food crop and is cultivated in more than 100 countries. The crop tolerates low soil fertility and drought, enabling it to play a role in climate adaptation strategies. Cassava generally requires careful preparation to remove toxic hydrogen cyanide (HCN) before its consumption, but HCN concentrations can vary considerably between varieties. Climate change and low inputs, particularly carbon and nutrients, affect agriculture in Pacific Island countries where cassava is commonly grown alongside traditional crops (e.g., taro). Despite increasing popularity in this region, there is limited experimental data about cassava crop management for different local varieties, their relative toxicity and nutritional value for human consumption, and their interaction with changing climate conditions. To help address this knowledge gap, three field experiments were conducted at the Koronivia Research Station of the Fiji Ministry of Agriculture. Two varieties of cassava with contrasting HCN content were planted at three different times coinciding with the start of the wet (September-October) or dry (April) seasons. A time series of measurements was conducted during the full 18-month or differing 6-month durations of each crop, based on destructive harvests and phenological observations. The former included determination of total biomass, HCN potential, carbon isotopes (δ13C), and elemental composition. Yield and nutritional value were significantly affected by variety and time of planting, and there were interactions between the two factors. Findings from this work will improve cassava management locally and will provide a valuable dataset for agronomic and biophysical model testing. Dataset: The dataset was submitted and will be published as a supplement to this article in the journal Data. The dataset is available electronically as Supplementary Material.

Original languageEnglish
Article number120
Number of pages12
JournalData
Volume10
Issue number8
DOIs
Publication statusPublished - Aug 2025

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