A recalibrated and tested LINTUL-Cassava simulation model provides insight into the high yield potential of cassava under rainfed conditions

J.G Adiele,A.G.T Schut,R.P.M Van Den Beuken,K.S Ezui,P Pypers,A.O Ano,C.N Egesi,K.E Giller

doi:10.1016/j.eja.2021.126242

Abstract

Accurate assessments of the yield potential of cassava are needed to analyse yield gaps, define yield targets and set benchmarks for actual yields in Nigeria. This study evaluated the crop model LINTUL-Cassava under assumed potential growth and water-limited conditions in Nigeria. On-farm experiments were conducted at six locations across the three major cassava growing agro-ecologies of Western Africa (Tropical Rainforest – Ogoja and Ikom in Cross River state, Rainforest Transition Savanna – Ekpoma in Edo state and Guinea Savanna – Otukpo in Benue state) during two subsequent seasons (2016 – 2018). Treatments included fertilizer rates calculated to support the assumed potential yields of 90 t fresh storage root yield ha−1 y−1 (equivalent to 32 t DM ha−1, produced in a growing season of 12 months). Light interception (LI) and leaf area index (LAI) were measured each month. The weights of leaves, stems and storage roots were measured at 4 and 8 months after planting and at harvest, and radiation use efficiency (RUE) calculated. The Edo experiment from 2016 was without drought stress and was used to parameterise LINTUL-Cassava and calibrate assimilate partitioning as function of temperature sums. The average fraction of light intercepted during the season was 80 %, with a light extinction coefficient of 0.67 and a RUE of 2.8 g DM MJ−1 intercepted photosynthetically active radiation (IPAR). After calibration, the LINTUL-Cassava model described the crop growth and observed patterns of LAI well in the experiments in Cross River and Edo (2017). Simulated and observed storage root yield at 4 MAP (vegetative period), 8 MAP (mid-season) and at harvest were strongly correlated (R2 of 0.92), with a RMSE of 4.93 t DM ha−1. We ascertained that RUE of cassava was much higher than previously observed in Africa, with an average storage root yield of 39 ± 7 t DM ha−1. Consequently, potential yields are greater and yield gaps larger than expected or previously reported. We conclude that the LINTUL-Cassava model can provide an adequate estimate of storage root yield across major cassava growing agroecological zones in Nigeria under rainfed conditions.

Highlights

Cassava (Manihot esculenta Crantz) is an important food crop and animal feed in tropical and sub-tropical Africa, Asia, and Latin America
We conclude that the LINTUL-Cassava model can provide an adequate estimate of storage root yield across major cassava growing agroecological zones in Nigeria under rainfed conditions
The area cropped with cassava has expanded considerably over the past decades (Howeler et al, 2013), with over 26 million hectares of land cultivated in 2017, of which approximately 78 % was in Africa (FAO STAT, 2017)

Summary

Introduction

Cassava (Manihot esculenta Crantz) is an important food crop and animal feed in tropical and sub-tropical Africa, Asia, and Latin America. There is wider recognition of cassava as a crop of choice for climate change adaptation strategies, in sub-Saharan Africa (SSA) (FAO, 2018) Tropical root crops such as cassava or tuber crops like yams may provide new options to feed the growing population with lower nutrient requirements than cereals (Howeler, 2017). Observed storage root yields from experiments in the region ranged between 6 and 35 t dry matter (DM) ha− 1 (Adiele et al, 2020) and were larger than simulated potential yields (Matthews and Hunt, 1994; Gabriel et al, 2014; Ezui et al, 2018) This suggests that some crop parameters used currently in cassava growth simulation models require modification. Good estimates of po tential yields provide important benchmarks for realistic yield targets and understanding of yield gaps with local relevance (Van Ittersum et al, 2013)

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