Dynamics of N-P-K demand and uptake in cassava

Abstract

Fertilizers are required to improve productivity of cassava and meet the increasing demand for cassava as food, feed, or raw material for processing industries. Our objective was to develop nutrition indices for N, P, and K to provide quantitative insight in the dynamics of nutrient demand and uptake of cassava. On-farm experiments were conducted at six locations in Nigeria from 2016 to 2018, across the major cassava growing agro-ecologies of West Africa. Nitrogen, P, and K were applied at different rates. Uptake of nutrients was measured in leaves, stems, and storage roots at 4, 8, and 12 or 14 months after planting (MAP) and used to construct NPK dilution curves and nutrition indices. About 67, 61, and 52% of total N, P, and K were taken up at 4 MAP, with a maximum uptake rate of 0.21, 0.03, and 0.12 g/m2/d for N, P, and K, respectively. Nutrient concentrations in stems and storage roots declined gradually, in contrast to concentrations in the leaves that fluctuated within narrow ranges. Dilution curves and nutrition indices for N, P, and K were established for the first time in cassava. Dilution curves of N, P, and K in the crop for the highest NPK application treatment were described as Nc = 82DM−0.61, Pc = 7.4DM−0.54, and Kc = 43DM−0.54, when total biomass was between 5 and 57 t/ha dry matter (DM). The nutrition indices were linearly related to relative crop biomass. Insight into the nutrient uptake and dilution patterns during the growth cycle can help to understand the temporal nutrient demands of cassava and identify sustainable management practices. Initial ample supply of N and P and moderate K, with extra K top-dress during the second growth phase, will benefit cassava growth and yield. Furthermore, such information provides a basis to develop a dynamic model to simulate nutrient-limited growth of cassava.

A New Curve of Critical Leaf Potassium Concentration Based on the Maximum Root Dry Matter for Diagnosing Potassium Nutritional Status of Sweet Potato

“…Gómez et al ( 2018 ) proved the existence of a “dilution phenomenon” for K in potato and constructed critical shoot dilution curves for K in potato (Suprema: K c = 6.58 W −0.135 ). Adiele et al ( 2021 ) constructed the critical plant and shoot K dilution curves in cassava (the whole plant: K c = 4.2DM −0.69 ; shoot: K c = 4.3DM −0.54 ) and proved that the dilution of K concentration in leaves was less than that in roots, which is consistent with our study. Generally, the K dilution of sweet potato is less than that of potato and cassava.…”

“…KNI leaf has better advantages to combine with remote sensing than KNI root for monitoring the yield of sweet potato quickly. Adiele et al ( 2021 ) showed that there was a linear relationship between relative biomass yield and KNI in cassava, and KNI explained 65–66% of the variation for the relative biomass for all treatments. Gómez et al ( 2018 ) developed a quadratic polynomial model between N nutrition index (NNI) and potato yield, and NNI explained 73% of the variability in relative yield.…”

“…All these studies indicated the likely presence of a critical K concentration curve for crops. Recent studies by Adiele et al (2021) reported, for the first time, the critical K dilution curves for cassava.…”

LINTUL-Cassava-NPK: A simulation model for nutrient-limited cassava growth

“…Understanding the dynamics of nutrient requirements and the impact of uptake limitations of cassava during the growth cycle enables prediction of cassava yields under nutrient limited conditions and may provide insight into best management practices to improve nutrient use efficiency. The nutrient contents of organs of the cassava plant vary during the growth cycle, but concentrations in the leaves fluctuate within narrow ranges ( Cock and Connor, 2021 ; Adiele et al, 2021a ). Typically, plants dilute nutrients over time as carbon accumulates ( Lemaire, 2012 ).…”

“…Knowledge of nutrient (N, P and K) demand and uptake patterns under deficient conditions in cassava ( Adiele et al, 2021a ) can be used to develop a crop simulation model. After testing, such a model may be used for many purposes, including to generate crop responses for series of years to characterize cassava growth and nutrient uptake, provide location-specific fertilizer recommendations, and to extrapolate from the studied area to other areas where less detailed information is available.…”