Applied Research in Science and Technology 5.
: 188Ae203 2025 Contents lists available at openscie.
E-ISSN: 2776-7205
Applied Research in Science and Technology DOI: 10.
33292/areste.
Journal homepage: https://areste.
org/index.
php/oai Micro Irrigation and NPK Fertilization to Improve Nutrient Uptake and Flavonoid of Shallot in Karst Land Fransiska Maria Aprilya Nana1.
Muhamad Khoiru Zaki 1,2*.
Murtiningrum1,2.
Virgolie Diknas Ximenis3.
Ngadisih1,2.
Rizki Maftukhah1,2.
Sahidatun Fahima1 Department of Agricultural and Biosystems Engineering.
Faculty of Agricultural Technology.
Universitas Gadjah Mada.
Yogyakarta.
Indonesia Research Center for Modernization Irrigation.
Faculty Agricultural Technology.
Universitas Gadjah Mada.
Yogyakarta Indonesia Biology Program.
School of Life Sciences.
Arizona State University.
Tempe.
AZ.
United States of America *Correspondence: E-mail: muhamad.
khoiru@ugm.
ARTICLE INFO
ABSTRACT
Article History:
Received 3 July 2025 Revised 28 August 2025 Accepted 9 September 2025 Published 12 October 2025 Background: Water and nutrient limitations in karst soils hinder the optimal growth of shallots, so water and nutrient management is carried out using variations in micro-irrigation and NPK fertilization.
Variations in micro-irrigation and NPK fertilization can support the growth and flavonoid content of shallots.
Aims: This study aims to analyze nutrient uptake and total flavonoid production of shallots in karst soils with variations in micro-irrigation and NPK fertilization.
Methods: The research used a Randomized Block Design (RBD) containing two main factors.
The first factor was the irrigation technique, consisting drip irrigation Keywords:
(I.
and mist irrigation (I.
The second factor was the NPK fertilizer dosage.
Drip Irrigation, consisting three levels: 0 kg/ha (N.
, 500 kg/ha (N.
, and 1000 kg/ha (N.
The Flavonoids, parameters observed included soil moisture, soil NPK availability, plant NPK Mist Irrigation, uptake, total flavonoids, growth, and shallot yield.
NPK,
Results: The results showed that mist irrigation with an NPK dose of 1000 kg/ha Shallot.
yielded higher results compared to drip irrigation in terms of soil moisture.
NPK availability and uptake, growth, and yield.
The highest availability of nitrogen, phosphorus, and potassium in mist irrigation with a dose of 1000 kg/ha was 0.
20 ppm, and 0.
66 me%, respectively.
Phosphorus uptake in mist irrigation was higher than in drip irrigation, at 0.
81% and 0.
89%, respectively.
Growth and yield under mist irrigation with an NPK dose of 1000 kg/ha also yielded the best results compared to drip irrigation with an NPK dose of 1000 kg/ha, namely plant height .
69 and 29.
74 c.
, number of leaves .
65 and 25.
77 leave.
, and bulb diameter .
07 and 27.
02 m.
The highest total flavonoid content was observed in drip irrigation with a 500 kg/ha dose compared to mist irrigation with a 500 kg/ha dose, namely .
83 and 50.
96 mg/k.
Overall, irrigation techniques with varying NPK doses were able to increase nutrient and flavonoid uptake in shallot on karst land.
To cite this article: Nana.
Zaki.
Murtiningrum.
Ximenis.
Ngadisih.
Maftukhah.
Fahima.
Micro irrigation and npk fertilization to improve nutrient uptake and flavonoid of shallot in Karst Land .
Applied Research in Science and Technology, 5.
, 188Ae203.
This article is under a Creative Commons Attribution-ShareAlike 4.
0 International (CC BY-SA 4.
License.
Creative Commons Attribution-ShareAlike 4.
0 International License Copyright A2025 by author/s Introduction Shallot (Allium ascalonicu.
is an important horticultural commodity in Indonesia as a cooking spice, but it can also be processed into food products such as flour, crackers, and pasta.
This commodity contains carbohydrates, vitamins A.
B, and C, as well as minerals such as calcium, phosphorus, and iron (Shahrajabian et al.
, 2.
Additionally, shallot contain secondary metabolites in the form of flavonoids, which act as antioxidants, antimicrobials, and anti-inflammatories (Kothari et al.
, 2.
Flavonoids play a crucial role in maintaining crop quality by protecting against oxidative stress, extending shelf life, and preserving organoleptic characteristics such as color and flavor (Lopresti et al.
, 2.
Flavonoid synthesis is influenced by environmental conditions, particularly abiotic stresses such as drought and nutrient deficiency (Kumar et al.
, 2023.
Sansan et al.
, 2.
Moderate water deficit has been reported to increase flavonoid accumulation, but severe drought has a negative impact on plant growth and physiology (Ren et al.
, 2.
Marginal lands such as karst lands have major constraints, namely low water reserves and nutrient availability due to the dominance of limestone, high porosity, and low water storage capacity (Lv et , 2.
These conditions hinder nutrient uptake efficiency, plant physiology, and crop yields (Salem et al.
, 2022.
El-Metwally & Saudy, 2.
Water management strategies through micro-irrigation are one approach that can be applied to improve water use efficiency in karst areas.
Micro-irrigation includes drip irrigation and mist irrigation, which can efficiently deliver water directly to the root zone (Deshpande et al.
, 2.
Drip irrigation works by slowly dripping water onto plant roots, minimizing evaporation and percolation, while mist irrigation sprays water particles evenly over the planting area, increasing air humidity and lowering microclimate temperature (Bansal et al.
, 2021.
Li & Su, 2.
The water distribution patterns of each of these techniques affect soil moisture and plant physiological responses, including nutrient uptake and flavonoid biosynthesis (Naveena & Babu.
In addition to water management, the availability of macronutrients such as nitrogen (N), phosphorus (P), and potassium (K) also plays a crucial role in supporting plant growth and the formation of functional compounds.
NPK fertilization is necessary to enhance soil fertility and plant physiological performance.
Nitrogen is involved in protein and chlorophyll synthesis, phosphorus is important for energy production and root development, while potassium supports photosynthesis, osmotic regulation, and the biosynthesis of secondary metabolites (Wang et al.
, 2.
Low water availability in karst soils will inhibit nutrient dissolution and plant metabolism, thereby affecting the growth and secondary metabolic synthesis of shallot (Sansan et al.
, 2.
Optimal absorption of nitrogen, phosphorus, and potassium can support the enzymatic activity required for flavonoid biosynthesis.
Previous studies have shown that plant nutrient content can influence secondary metabolic pathways.
Research by Liu et al.
shows that NPK fertilization not only affects tuber yield, but also the content of bioactive compounds, including flavonoids.
Therefore, proper irrigation and fertilization management can support optimal nutrient availability and uptake for growth, yield, and flavonoid synthesis.
Research on the interaction between micro-irrigation techniques and NPK fertilization rates on horticultural crop physiology has been extensively conducted, but it remains limited to specific crops and has not extensively addressed its impact on flavonoid content in karst soils.
This study aims to analyze growth, yield, nutrient availability, nutrient uptake, and total flavonoid production in shallot on karst land with variations in micro-irrigation .
rip and mis.
and NPK fertilization .
, 500, and 1000 kg/h.
The use of NPK Phonska doses of 500 and 1000 kg/ha was chosen to represent different fertilization levels, where 500 kg/ha is the general recommended dose for shallot cultivation (Atman, 2021.
Kementan, 2017 ), while 1000 kg/ha represents a high dose to evaluate plant response to greater nutrient availability.
Comparing these two doses is important to determine the extent to which increased N.
P, and K supply can affect growth, nutrient uptake, and the formation of secondary metabolites such as flavonoids under different soil moisture conditions.
The results of this study are expected to provide a scientific basis for designing adaptive and sustainable cultivation strategies that can improve the physiological quality and functional value of shallot yields.
These findings can also provide dosage recommendations for NPK fertilization on karst soil in shallot cultivation.
Methods This research will be conducted on agricultural land located in Wareng Village.
Wonosari District.
Gunung Kidul.
Yogyakarta from August 2024 to October 2024.
Geographically, the research location is at coordinates 7A 59A 07A S and 110A 33A 45A E and an elevation of 167 meters above sea level.
1 Materials The materials used in this study were shallot seeds (Allium ascalonicu.
of the Tajuk variety.
Phonska NPK fertilizer, manure, pesticides for pest control.
PVC pipes, drip sticks, emitters, drip irrigation hoses, and mist irrigation hoses.
The tools used in this study were an AWS (Automatic Weather Syste.
MS10 soil moisture sensor (INFWIN.
Chin.
, shovel, ruler for measuring plant height, pump, manometer, flow meter, digital scale, writing instruments, and camera.
2 Experimental Design This study used a split plot design with a randomized block design (RAK) in an area of 256 m 2 .
This study involved two independent variables, namely two types of irrigation and three doses of Phonska NPK fertilizer.
The irrigation type variable consists of drip irrigation (I.
and mist irrigation (I.
The NPK Phonska fertilizer dose variable includes 0 kg/ha (N.
500 kg/ha (N.
and 1000 kg/ha (N.
Each treatment will be applied to separate plots with three replications, resulting in 18 experimental units on the research plot.
Samples will be randomly collected from each plot to measure dependent variables such as onion growth, yield, soil chemical analysis samples, and plant samples.
The experimental layout is divided into two blocks for mist irrigation and drip irrigation.
Each block has 9 experimental plots measuring 1.
5 m x 3 m.
The two experimental blocks are separated by a distance of 10 m to minimize bias during cultivation and data collection.
3 Soil Moisture Content Data was collected using a special data cable and stored in .
csv format.
Soil moisture measurements were taken during the shallot growing season using an MS10 sensor installed 5 cm below the center of each experimental plot.
Data can be accessed online and offline via the data log.
The sensor automatically records data every 30 minutes to align with actual moisture content (% volumetri.
Calibration was performed on the soil sensor using the same soil from the research field.
Data collection involved weighing the soil from saturated to oven-dry conditions.
The results were then converted into moisture content data based on % volumetric.
The calibration results obtained were plotted in graph form, yielding the equation y = 0.
0093x 3 y 10a.
The regression equation derived from calibration was subsequently used to represent soil moisture values obtained from sensor data.
4 Plant Physiology and Biomass Plant physiology measurements were performed by measuring plant height and number of leaves, while plant biomass was measured by weighing the wet weight of tubers, dry weight of plants, number and diameter of tubers in each experimental plot.
Plant samples were oven-dried at 60AC for 3 days until constant weight was achieved.
The oven-dried samples are then weighed using a digital scale with a precision of 0.
01 grams to obtain the dry weight.
The diameter of the tubers is measured at the widest part of the tuber using a caliper on tubers representing each experimental block.
5 Nutrient Availability and Nutrient Uptake Soil nutrient testing and nutrient uptake were conducted for each treatment with three replicates.
Soil sampling was performed continuously and randomly.
The testing was conducted at the Chemistry and Soil Fertility Laboratory of UNS Surakarta.
Samples were collected after harvesting.
Nitrogen was analyzed using the Kjeldahl method, which consists of three main stages: destruction, distillation, and A total of 0.
5 grams of soil was converted with concentrated sulfuric acid and a catalyst, then heated until the solution was clear.
The digestion product was distilled with the addition of NaOH solution, and the ammonia formed was captured in boric acid solution.
Next, titration was performed 01 N HCl.
The end point of titration was marked by a stable pink color change for A 30 seconds, and the nitrogen content could be calculated from the titration volume.
Plant tissue phosphorus was analyzed using wet destruction, while soil phosphorus was analyzed using dry destruction and the Olsen method, which involves extraction with 0.
5 M NaHCO3 solution .
H 8.
A total of 2.
5 grams of soil was extracted with 50 mL of the solution and shaken for 30 minutes, then filtered.
The extraction filtrate was reacted with molybdate-ascorbate reagent, producing a blue color.
The intensity of the blue color was then measured using a spectrophotometer at a wavelength of 880 nm.
Potassium was analyzed using the extraction method with 1N acetic acid solution at pH 7.
Five grams of soil were extracted with 50 mL of the solution, shaken for 30 minutes, and filtered.
The extraction filtrate was then analyzed using an atomic absorption spectrophotometer (AAS).
6 Total Flavonoid Content Measurement of total flavonoid content using the UV-Vis spectrophotometer method.
Shallot bulb samples were extracted with 70% ethanol solvent through a soxhlet extraction process for several The extract obtained was then filtered and taken for analysis.
The extract solution was mixed with a 10% aluminum chloride (AlClCE) solution, a 1 M sodium acetate solution, and the mixture was incubated for 30Ae60 minutes at room temperature.
Subsequently, the absorbance of the mixture was measured using a UV-Vis spectrophotometer at a maximum wavelength of 415 nm.
The absorbance values were then compared with the standard curve of quercetin as the reference compound, enabling the total flavonoid concentration in the sample to be calculated and expressed in units of mg/kg.
The total flavonoid content testing was conducted at the Integrated Research and Testing Laboratory.
Gadjah Mada University.
Yogyakarta.
7 Growth Rate Modeling The mathematical model used to describe the growth rate of plants, including plant height and number of leaves in this study, is the quadratic exponential equation (France & Thornley, 2.
The quadratic exponential equation prediction model is shown in equation:
yayc 2 Wt = WCA A exp [CA .
- 2 )] Wt represents the plant height or number of leaves at time t.
W0 indicates the initial plant height taken from the average measurement results in the early growth phase.
CA is the initial specific growth rate from the curve fitting that describes the plant's ability to grow rapidly in the early vegetative phase, and D is the growth rate decline coefficient estimated from the model to show the rate of growth deceleration over time.
8 Statistical Analysis Data analysis was performed using several tests, namely ANOVA.
Duncan's test, and T-test.
ANOVA was performed on moisture content.
NPK availability.
NPK uptake, plant growth, and crop Subsequently, a post-hoc test was performed using Duncan's test.
The T-test was applied to both observational data and predictive data for model validation.
Total flavonoid content was presented through descriptive analysis since it was only tested on a single sample representing each treatment without replicates.
Results and Discussions 1 Soil Moisture Content The soil moisture content values for each irrigation technique and fertilizer dose treatment are shown in Table 1.
Irrigation techniques had a very significant effect on soil moisture content, while NPK fertilizer doses and the interaction between the two treatments had no significant effect.
Fog irrigation consistently produced higher soil moisture content than drip irrigation.
Table 1.
Results of ANOVA test on average moisture content Irrigation Techniques NPK Dosage Moisture Content (%) 0 kg/ha 24,08 A 6,48b Drip Irrigation 500 kg/ha 18,67 A 1,66b 1000 kg/ha 19,81 A 2,55b 0 kg/ha 35,56 A 2,25a Mist Irrigation 500 kg/ha 34,22 A 0,52a 1000 kg/ha 34,20 A 0,46a a, b, c, d, e = letter notation is not similar, meaning that there is no real effect on the level Duncan test has a value of 5%.
The significant difference in soil moisture content between drip irrigation and mist irrigation is related to the water distribution mechanisms of each irrigation technique.
The difference in soil moisture content between drip irrigation and mist irrigation is mainly due to differences in water distribution patterns.
Drip irrigation delivers water slowly and directly to the root zone, thereby reducing losses due to evaporation, but its distribution is limited and uneven on clay-textured soils (Bansal et al.
, 2.
In contrast, mist irrigation sprays water in the form of micro-particles that are more easily absorbed by the soil surface and create more homogeneous moisture.
This condition expands the moist zone around the roots, increases water absorption capacity, and has implications for improved nutrient availability and plant growth (Li et al.
, 2023.
Liu et al.
, 2.
2 Nutrient Availability and Nutrient Uptake Dynamics The NPK availability values for each irrigation technique and fertilizer dose treatment are shown in Table 2, indicating that irrigation techniques and NPK fertilizer doses affect phosphorus and potassium availability, while nitrogen availability does not differ significantly.
In general, mist irrigation produces higher P and K availability compared to drip irrigation.
This is related to more even soil moisture distribution, which accelerates the dissolution and diffusion of nutrients in the soil solution (Li et al.
, 2.
Increasing the NPK fertilizer rate also enhances P and K availability, with the highest values recorded in mist irrigation at a rate of 1000 kg/ha (P = 89.
20 ppm.
K = 0.
66 me%), indicating that this combination is most effective in providing essential nutrients for plants.
Table 2.
Results of ANOVA test on average NPK availability NPK Dosage Nitrogen (%) Phosphorus .
Potassium .
e %) 0 kg/ha 22A 0.
92A 4.
29A 0.
Drip Irrigation 500 kg/ha 20A 0.
48A 2.
37A 0.
1000 kg/ha 22A 0.
52A 1.
43A 0.
0 kg/ha 23A 0.
07A 8.
40A 0.
Mist Irrigation 500 kg/ha 22A 0.
60A 12.
60A 0.
1000 kg/ha 36A 0.
20A 1.
66A 0.
a, b, c, d, e = letter notation is not similar, meaning that there is no real effect on the level Duncan test has a value of 5%.
Irrigation Techniques Conversely, soil nitrogen content .
36%) did not show a consistent pattern between The nature of nitrogen, which is easily lost through leaching, denitrification, and volatilization, means that irrigation and fertilizer effectiveness have little effect on its availability (Shafreen et al.
, 2021.
Papadimitriou et al.
, 2.
Overall, the results of this study confirm that mist irrigation, especially with high fertilizer doses, is more optimal in maintaining phosphorus and potassium availability compared to drip irrigation, thereby potentially increasing nutrient uptake and onion yields in karst soils.
Significant differences in phosphorus and potassium content between mist irrigation and drip irrigation are due to the characteristics of mist irrigation, which distributes water evenly on the soil surface and maintains more stable moisture levels that can support the activity of phosphate-solubilizing microbes and reduce the level of P fixation by Al3 and Fe3 , leading to the release of phosphorus from bound forms into available forms (Li et al.
, 2.
Phosphorus is difficult to mobilize in dry soil, so it is more optimally available in soil with optimal water conditions because water dissolves phosphate compounds bound to soil particles, making them easily accessible to plants.
Potassium is more mobile than phosphorus but still requires water to support transportation, diffusion, and movement in the soil (Liu et al.
, 2.
Stable soil moisture in mist irrigation can reduce K binding by clay particles, thereby increasing its availability in the soil solution, whereas in drip irrigation with low doses shows low potassium content, indicating inefficient fertilizer distribution due to the narrower scope of nutrient movement and water pathways (Bansal et al.
, 2021.
Mouhamad et al.
The NPK uptake values for each irrigation technique and fertilizer dosage treatment are shown in Table 3.
Table 3.
Results of ANOVA test on average NPK uptake Potassium (%) Irrigation techniques NPK Dosage Nitrogen (%) Phosphorus (%) 0 kg/ha 03A 0.
97A 0.
82A 0.
Drip Irrigation 500 kg/ha 47A 0.
85A 0.
46A 0.
1000 kg/ha 95A 0.
85A 0.
02A 0.
0 kg/ha 68A 0.
88A 0.
88A 0.
Mist Irrigation 500 kg/ha 00A 0.
76A 0.
37A 0.
1000 kg/ha 44A 0.
79A 0.
45A 0.
a, b, c, d, e = letter notation is not similar, meaning that there is no real effect on the level Duncan test has a value of 5%.
Nutrient uptake is influenced by the availability of nutrients in the soil, mobility, the chemical properties of each element, and the irrigation techniques used.
The results indicate that K uptake increases with increased fertilizer application rates, particularly in mist irrigation systems, which maintain more uniform soil moisture levels, thereby supporting nutrient dissolution and diffusion (Li & Su, 2017.
Bhattacharyya et al.
, 2.
Conversely.
N uptake remains relatively stable across treatments due to its high leaching and volatilization rates, meaning its availability in the soil does not always align with the applied fertilizer (Pal et al.
, 2020.
Xiang et al.
, 2.
Phosphorus uptake did not show significant differences because it has low mobility and limited movement around the roots.
Potassium has higher mobility and is distributed more evenly with the help of irrigation.
Potassium ions (K ) can maintain relatively stable mobility, resulting in a more uniform distribution of K ions with mist irrigation compared to drip irrigation.
Increased P and K uptake plays a crucial role in shallot bulb growth due to their roles in root formation, cell division, and bulb development (Wang et al.
, 2.
3 Shallot Growth Table 4 show that irrigation techniques have a significant effect on shallot growth, both in terms of plant height and number of leaves.
Conversely.
NPK dosage only affects plant height, but does not affect the number of leaves.
The interaction between the two factors does not show a significant effect on the observed growth parameters.
In general, mist irrigation resulted in higher average plant height and number of leaves compared to drip irrigation.
Table 4.
Results of ANOVA test on the average growth of shallots Irrigation techniques NPK Dosage Plant Height .
Number of Leaves .
0 kg/ha 24,74 A 2,30b 18,69 A 2,72c Drip Irrigation 500 kg/ha 26,27 A 1,40b 19,86 A 2,66bc 1000 kg/ha 29,74 A 0,69a 25,77 A 3,88ab 0 kg/ha 29,37 A 1,68a 25,57 A 4,42ab Mist Irrigation 500 kg/ha 31,28 A 0,57a 25,80 A 2,58ab 1000 kg/ha 30,69 A 1,80a 27,65 A 3,77a a, b, c, d, e = letter notation is not similar, meaning that there is no real effect on the level Duncan test has a value of 5%.
The best treatment was observed in mist irrigation with an NPK dose of 1000 kg/ha, which produced the highest plant height .
69 c.
and the greatest number of leaves .
65 leave.
Conversely, the lowest growth was observed in drip irrigation without fertilization .
74 cm.
The more stable humidity conditions in mist irrigation promote the development of meristematic tissue, thereby enhancing plant height growth and leaf formation (G.
Li et al.
, 2.
Increasing NPK doses also tended to increase plant height, indicating that the availability of macronutrients (N.
K) supports cell division and elongation (Amare, 2020.
Bekele, 2.
These findings align with Wang et al.
, who found that regulating soil moisture through irrigation plays a crucial role in supporting the vegetative growth of shallots.
4 Shallot Growth Rate Modeling plant height growth with a quadratic-exponential function produces the equation W.
= WCAA exp [CA .
Ae 0.
5Dt.
The parameters obtained through non-linear regression reflect the initial growth conditions (WCA), relative growth rate (CA), and inflection point (D) that determine when the growth rate reaches its peak.
Table 6.
Quadratic Exponential Growth Model Function Irrigation techniques NPK Dosage Model function W.
= 3.
902 * exp .
Drip Irrigation 0 kg/ha 5*0.
024*t^.
) W.
= 3.
805 * exp .
500 kg/ha 5*0.
024*t^.
) 1000 kg/ha Mist Irrigation 0 kg/ha 500 kg/ha 1000 kg/ha W.
= 3.
5*0.
024*t^.
) W.
= 3.
5*0.
024*t^.
) W.
= 3.
5*0.
023*t^.
) W.
= 4.
5*0.
023*t^.
) .
The prediction function in Table 6 was used to calculate daily plant height, and the prediction results were compared with field observation data to determine the accuracy of the model.
The irrigation type variable consists of drip irrigation (I.
and mist irrigation (I.
The NPK Phonska fertilizer dose variable includes 0 kg/ha (N.
500 kg/ha (N.
and 1000 kg/ha (N.
The prediction results and observations of plant height growth are presented in Figure 1.
Plant Height .
Plant Height .
DAP
Observation DAP Observation Prediction .
I1N1
Prediction .
I1N2
Plant Height .
Plant Height .
DAP
Observation Prediction .
I1N3
DAP
Observation .
I2N1
Prediction Plant Height .
Plant Height .
Observation DAP Prediction .
I2N2
DAP 40
Observation Prediction .
I2N3 Figure 1.
Graph of predicted and observed plant height growth The highest growth was obtained in treatment I2N3, namely mist irrigation with 1000 kg/ha of NPK.
Biologically, the growth pattern follows a quadratic exponential curve with three main phases, namely the slow initial phase .
, the rapid growth phase .
, and the flat phase towards the end of the vegetative period .
(Liu et al.
, 2.
A higher CA value indicates accelerated growth, while the D parameter relates to the plant's age when maximum growth is achieved.
These findings are consistent with Sibly & Brown .
, who stated that plant growth follows a sigmoidal pattern due to physiological and resource limitations.
Thus, this model can be used as a basis for evaluating the effectiveness of treatments in accelerating the vegetative growth of shallots.
Table 7.
Results of t-tests for predicted and observed plant height values Irrigation techniques NPK Dosage Drip Irrigation 0 kg/ha 500 kg/ha 1000 kg/ha Mist Irrigation 0 kg/ha 500 kg/ha 1000 kg/ha p-value 0,961 0,953 0,944 0,955 0,955 0,960 A comparison graph between observed and predicted values shows the similarity of growth patterns (Figure .
, and a t-test reveals no significant difference .
>0.
between the two (Table .
This confirms that the model is sufficiently representative to describe the growth dynamics of shallot plants.
The highest leaf growth rate was observed in treatment I2N3, which involved mist irrigation with 1000 kg/ha of NPK, and was comparable to the plant height growth rate.
This further reinforces that this combination of treatments is capable of supporting plant growth through optimal leaf formation.
Stable availability of water and dissolved nutrients can support plant tissue formation (Kudoyarova et al.
(Kareem et al.
, 2.
Modeling of shallot plant height growth produced specific growth prediction functions for each treatment combination in Table 8.
Table 8.
Average growth rate of leaf number Irrigation techniques NPK Dosage Drip Irrigation 0 kg/ha 500 kg/ha Leaf Rate 1000 kg/ha 0 kg/ha 500 kg/ha 1000 kg/ha Mist Irrigation Modeling leaf number growth using a quadratic exponential function (Table .
produced specific predictive equations for each treatment combination.
Table 9.
Exponential Quadratic Leaf Number Growth Model Function Irrigation techniques Drip Irrigation Mist Irrigation NPK Dosage 0 kg/ha 500 kg/ha 1000 kg/ha 0 kg/ha 500 kg/ha 1000 kg/ha Model Function W.
= 2.
672 * exp .
121 * .
- 0.
5*0.
026*t^.
) W.
= 2.
882 * exp .
119 * .
- 0.
5*0.
025*t^.
) W.
= 2.
734 * exp .
130 * .
- 0.
5*0.
024*t^.
) W.
= 2.
772 * exp .
119 * .
- 0.
5*0.
022*t^.
) W.
= 2.
648 * exp .
124 * .
- 0.
5*0.
023*t^.
) W.
= 2.
824 * exp .
125 * .
- 0.
5*0.
023*t^.
) Number of Leaves Number of Leaves The irrigation type variable consists of drip irrigation (I.
and mist irrigation (I.
The NPK Phonska fertilizer dose variable includes 0 kg/ha (N.
500 kg/ha (N.
and 1000 kg/ha (N.
The application of this model shows a high degree of agreement between predicted and observed values, as shown in Figure 2.
DAP
Observation Prediction 20 DAP Observation Prediction .
I1N2
Number of Leaves Number of Leaves .
I1N1
DAP
Observation Prediction Observation DAP Prediction .
I2N1
Number of Leaves Number of Leaves .
I1N3
DAP 40
Observation Prediction .
I2N2
DAP
Observation Prediction .
I2N3 Figure 2.
Graph of predicted and observed leaf growth The results of the t-test (Table .
indicate that all treatments have p-values > 0.
05, meaning there are no significant differences between observed data and predicted results.
Therefore, the model can be accepted as a representation of actual leaf number growth.
Table 10.
Results of t-tests for predicted and observed number of leaf Irrigation techniques NPK Dosage Drip Irrigation 0 kg/ha 500 kg/ha 1000 kg/ha Mist Irrigation 0 kg/ha 500 kg/ha 1000 kg/ha p-value 0,985 0,973 0,992 0,979 0,995 0,995 The consistent increase in the number of leaves reflects better plant biomass accumulation, as leaf area is directly related to light energy absorption capacity.
According to Sibly & Brown .
, the rate of leaf formation follows a logistic pattern determined by the interaction of genetic and environmental The results of this study indicate that a micro-irrigation system supported by appropriately dosed NPK fertilization not only influences vegetative growth but also enhances plant photosynthetic capacity through increased leaf number (Zhao et al.
, 2.
The highest leaf growth rate was observed in treatment I2N3, which consisted of mist irrigation with 1000 kg/ha of NPK, resulting in a plant height growth rate that was comparable to that of the control treatment.
This further reinforces the fact that this combination of treatments is capable of supporting plant growth through optimal leaf 5 Shallot Yield Table 11 show that irrigation techniques have a very significant effect on the wet weight of tubers, total dry weight, and diameter of shallot tubers.
Mist irrigation consistently yields higher values compared to drip irrigation, especially when combined with an NPK dose of 1000 kg/ha, which produces the highest fresh weight of bulbs .
, total dry weight .
, and largest bulb diameter .
07 m.
Table 11.
Results of ANOVA tests on crop yields Irrigation Wet Weight of Tubers Total Dry Weight bulb diameter NPK Dosage .
0 kg/ha 49,34 A 26,90 d 9,36 A 2,15c 24,81 A 1,70c Drip Irrigation 500 kg/ha 40 A 7,10 cd 10,47 A 2,11c 25,18 A 1,20c 1000 kg/ha 61 A 14,30 bc 11,48 A 2,28bc 27,02 A 1,12bc 0 kg/ha 74 A 6,87 bc 15,45 A 2,61ab 28,13 A 1,16ab Mist Irrigation 500 kg/ha 39 A 17,00 ab 16,65 A 3,21a 29,04 A 2,39ab 1000 kg/ha 47 A 18,8 a 18,42 A 2,77a 30,07 A 1,06a a, b, c, d, e = letter notation is not similar, meaning that there is no real effect on the level Duncan test has a value of 5%.
This increase in yield is associated with more stable soil moisture under mist irrigation, which supports nutrient uptake, photosynthesis, and the translocation of assimilates to the bulbs (TerynChaves et al.
, 2023.
Li et al.
, 2.
Increasing NPK doses tended to increase tuber fresh weight and tuber diameter but had no significant effect on total dry weight.
This indicates that plant response is more pronounced in fresh biomass accumulation and tuber size enlargement compared to dry matter According to Singh et al.
, the role of NPK fertilizer is primarily in providing N.
P, and K nutrients to support vegetative growth and tuber formation.
The absence of interaction between irrigation and NPK dose indicates an additive response, but mist irrigation treatment with NPK at 1000 kg/ha proved most effective in increasing onion yield through enhanced bulb cell expansion and accumulation of reserve carbohydrates (Ombydi et al.
, 2.
6 Total Flavonoid Content of Shallot The total flavonoid content in shallot bulbs showed differences in each treatment combination of irrigation system and NPK fertilizer dosage.
In general, drip irrigation produced higher flavonoid levels than mist irrigation.
Under drip irrigation, an NPK fertilizer dose of 500 kg/ha yielded the highest flavonoid content .
83 mg/k.
, higher than both the untreated control .
96 mg/k.
and the 1000 kg/ha dose .
89 mg/k.
This indicates that moderate doses can balance nitrogen and phosphorus supply to support phenolic compound biosynthesis without promoting excessive vegetative growth (Salama et al.
, 2.
Total Flavonoids .
g/k.
Drip Irrigation NPK 0 kg/Ha Mist Irrigation NPK 500 kg/Ha NPK 1000 kg/Ha Figure 3.
Total flavonoid content of shallot In contrast, in mist irrigation, the flavonoid content was lower, ranging from 50.
96 to 59.
6 mg/kg.
The high micro-humidity conditions in this system are thought to reduce the mild oxidative stress that is actually needed to induce the accumulation of secondary metabolites (Baskar et al.
, 2.
Environmental factors such as water availability, nutrient status, and oxidative stress play a crucial role in regulating flavonoid biosynthesis (Patil et al.
, 2.
Macronutrients such as NPK play a role in optimizing plant metabolism, including flavonoid biosynthesis.
Nitrogen supports the synthesis of aromatic amino acids as precursors to flavonoids, phosphorus is involved in energy metabolism that supports biosynthetic pathways, while potassium can increase the activity of enzymes involved in phenylpropanoid pathways (Srivastava et al.
, 2.
Therefore, the combination of drip irrigation and moderate NPK fertilization .
kg/h.
is more recommended, as it not only enhances tuber growth but also enriches the bioactive flavonoid content, which is functionally valuable for both consumers and the food industry (Nugraha et al.
, 2.
Conclusions This study shows that micro-irrigation techniques and NPK doses have a significant effect on the growth, yield, nutrient uptake, and flavonoid content of shallots.
Fog irrigation with a dose of 1000 kg/ha resulted in the highest growth, nutrient uptake, and bulb yield, while drip irrigation with a dose of 500 kg/ha produced the highest flavonoid content .
83 mg/k.
Therefore, the choice of cultivation technique should be tailored to production objectives: drip irrigation with 500 kg/ha NPK is more suitable for enhancing bioactive quality, while mist irrigation with 1000 kg/ha NPK is recommended for maximizing yield.
Further research under various environmental conditions is needed to strengthen the sustainable application of these findings.
Acknowledgment The authors gratefully acknowledge the Program for Academic Excellence Improvement 2024.
Universitas Gadjah Mada, for financial support of this research.
Appreciation is also extended to the Soil Chemistry and Testing Laboratory.
Universitas Sebelas Maret, and the Integrated Research and Testing Laboratory.
Universitas Gadjah Mada, for providing facilities and assistance in analysis.
Authors Note The authors declare that there is no conflict of interest regarding to the publication of this article.
Authors confirmed that the paper was free of plagiarism.
References