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Growth and Nutritional Quality of Cassava under Deficit Irrigation and Potassium Fertigation

Year: 2021
Type: dissertation
Abstract: Cassava (Manihot esculenta Crantz) is a staple food for millions of people in the tropics, providing high energy and nutritional value. Problems associated with cassava in the arid tropics are low yield, high cyanide concentration, and low mineral and vitamin A availability in leaves and roots. These factors hinder the utilization of cassava greatly and are highly influenced by the plant water status and potassium (K) availability in the growth environment. The productivity of cassava in such environments could be improved using irrigation strategies not based on full crop water requirements, such as deficit irrigation combined with K nutrition to ensure sustainable quantity and quality production. Additionally, employing systems that can allow non-destructive estimation of plant performance, such as the use of plant imaging techniques, could provide early information on plant performance, which would facilitate phenotyping, as well as assist in the mitigation of abiotic challenges in cassava production. This study investigated how irrigation water, K fertigation and their interactions affect the growth responses of biofortified cassava during the early growth phase. It was also investigated whether K fertigation could improve the nutritional and reduce the anti-nutritional qualities of biofortified cassava growing under typical conditions of water deficit. The ability to use red-green-blue (RGB) and multispectral sensors to detect the effects of water deficit and low K in cassava, and whether the crop quality changes due to low moisture and low K could be observed from the images, were also examined. Pot experiments were conducted at early developmental stages of cassava under controlled greenhouse conditions at the University of Helsinki. Young biofortified cassava plants were established using cuttings. The plants were subjected to three irrigation treatments (30%, 60%, 100% pot capacity) that were split into five K (0.01 mM, 1 mM, 4 mM, 16 mM, 32 mM) application rates beginning 30 days after planting (DAP) and ended at 90 DAP, when plants were harvested. Irrigation treatments and K application rates significantly affected leaf water potential, leaf osmotic potential, net photosynthesis, stomatal conductance, leaf temperature, leaf chlorophyll, water usage, plant leaf area, plant height, tuber number and whole-plant biomass. The interaction was also statistically significant for these properties. Irrigation treatments and K application rates also affected leaf turgor, but the interaction was not statistically significant. Irrigation at 30% together with 16 mM K lowered the leaf water potential by 69%, leaf osmotic potential by 41%, net photosynthesis by 35%, stomatal conductance by 41%, water usage by 50%, leaf area by 17%, and whole-plant dry mass by 41%, compared with fully irrigated plants. Lowering the K application rate below 16 mM reduced the values further. Most importantly, the growth was decreased least when irrigation was decreased to 60% together with 16 mM K, compared with optimal applications. The combined effect of irrigation treatments and K applications was statistically significant for starch, energy, minerals, total carotenoids, and cyanide, but the interaction was not statistically significant for dietary fibre and crude protein in the leaves and roots. In the leaves and roots, water deficit and lower K applications inhibited starch, carotenoids, crude protein, and fibre synthesis. Water deficit interrupted the uptake of minerals by the cassava roots from the soil and ultimately to the leaves. Improved uptake of calcium, phosphorous, magnesium, zinc, iron, sulphur, and chloride to the leaves was recorded with increased K application regardless of water deficit. K application also mitigated the effect of water deficit at 30% irrigation. Crude protein, carotenoids, and minerals were revealed to be more abundant in the leaves than in the roots, while the inverse was the case for starch content and iron. Cyanide was diminished in the leaves and roots of the cassava with increases in both irrigation and K application rates. Full irrigation (100%) with 16 mM K application produced the highest nutritional quality and the least cyanide concentration. Also, 16 mM K significantly improved the nutritional qualities and diminished the cyanide concentration irrespective of the irrigation treatment. High estimation accuracy (R2 = 0.90) for biomass, chlorophyll, and net photosynthesis were recorded. The estimated leaf area associated strongly (R = 0.98) with the measured leaf area. The estimated biomass also associated strongly with the measured biomass. Starch, energy, total carotenoids, and cyanide were estimated reasonably (R2 > 0.80) and showed strong correlations with the most of spectral indices. The estimation accuracy for all mineral elements was low, and weak relationships existed between the mineral elements and the spectral indices. The regression models identified normalized difference vegetation index, green area index, and simple ratio index as the best estimators of growth and key nutritional traits in cassava. Moreover, irrigation at 30% together with 0.01 mM K reduced all the index values but increased crop senescence index. Regardless of water deficit, increasing K application rate to 16 mM resulted in high values for all the spectral indices but low senescence index. In conclusion, adjusting K fertigation rates in combination with deficit irrigation may improve the growth and dietary quality of young cassava, and reduce cyanide concentration. Findings from this work can be utilized as a foundation to develop agronomic management practices involving K application for cassava growing in water-limited environments. The study also shows that RGB and multispectral sensors can be used to provide indirect measurements of growth and key nutritional traits in cassava, thus representing a tool that breeders may use to facilitate evaluation of cultivars, especially in the developing areas. Information from imaging data may also be used to facilitate corrective measures to avert stress, such as the decision to irrigate or apply fertilizers. Nonetheless, laboratory analysis of plant samples should support sensor estimates, especially under field conditions, when all possible factors affecting plant growth are difficult to forecast. Future studies could place emphasis on field conditions with multiple cassava cultivars and employ different imaging techniques.
Language: English
Subfield: Plant Science
Open Access status: green
OpenAlex ID: W3175367138
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