Determination of the effect of GA3 applications on plant development, nutrient content change and analysis of root architectural features using ML artificial neural network modelling in Tulipa saxatilis

Ömer Sari

doi:10.2478/fhort-2024-0024

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Determination of the effect of GA3 applications on plant development, nutrient content change and analysis of root architectural features using ML artificial neural network modelling in Tulipa saxatilis

Folia Horticulturae

Volume 36 (2024): Issue 3 (December 2024)

By: Ömer Sari

Open Access

|Oct 2024

Figures & Tables

Measurement of tulips’ roots with 3D scanning WhinRhizo program (a: control, b: 100 ppm, c: 200 ppm and d: 400 ppm).

The MLP structure with 7 inputs, 4 outputs, and 10 hidden neurons.

Change rate of plant upper part characteristics compared to control values after GA₃ applications. GA₃: gibberellic acid.

Table 1.

Correlations between vegetative, root architectural properties and bulb nutritional content.

	Flower stem length (cm)	Number of flover	Flower stem diameter (mm)	Perianth length (cm)	Number of leaves	Leaflength (cm)	Leaf width (cm)	Mother bulb diameter (mm)	Number of bulblet	Bulblet diameter (mm)	Bulblet weight (g)	N (%)	P (%)	K (%)	Ca (%)	Mg (%)	Fe (mg · kg⁻¹)	Cu (mg · kg⁻¹)	Zn (mg · kg⁻¹)	Mn (mg · kg⁻¹)	Root length (cm)	Root surface area (cm²)	Root diameter (mm)	Root volume (cm³)	Number of tips	Number of forks	Number of crossings
Plant height (cm)	0.996**	–0.994**	–0.919	0.603	–0.952*	0.992**	0.978*	0.450	0.740	–0.242	0.236	0.262	–0.991**	–0.725	0.192	0.401	0.324	–0.186	0.165	–0.664 0.277	–0.295	–0.180	0.452	0.123	–0.489	0.058	–0.614
Flower stem length (cm)		–0.998**	–0.931	0.543	–0.955*	0.979*	0.982*	0.372	0.678	–0.210	0.234	0.305	–0.975*	–0.684	0.267	0.356	0.408	–0.160	0.198	–0.729 0.283	–0.277	–0.215	0.383	0.039	–0.493	0.033	–0.671
Number of hovers			0.908	–0.512	0.971*	–0.973*	–0.969*	–0.351	–0.667	0.264	–0.292	–0.355	0.972*	0.715	–0.238	–0.402	–0.412	0.216	–0.144	0.734 -0.225	0.220	0.161	–0.351	–0.060	0.440	–0.090	0.644
Flower stem diameter				–0.617	0.784	–0.917	–0.981*	–0.372	–0.612	–0.158	0.127	–0.034	0.895	0.400	–0.504	–0.008	–0.442	–0.211	–0.540	0.712 -0.606	0.569	0.553	–0.456	0.180	0.768	0.333	0.837
Perianth length (cm)					–0.380	0.695	0.629	0.948	0.927	0.090	–0.32	–0.560	–0.689	–0.431	–0.159	0.151	–0.427	0.185	0.322	0.107 0.594	–0.756	–0.310	0.982*	0.468	–0.684	–0.272	–0.182
Number of leaves						–0.917	–0.881	–0.274	–0.614	0.473	–0.512	–0.533	0.928	0.820	–0.096	–0.578	–0.399	0.435	0.085	0.715 0.014	–0.011	–0.066	–0.228	–0.157	0.213	–0.319	0.503
Leaf length (cm)							0.974*	0.553	0.811	–0.214	0.171	0.155	–0.998**	–0.726	0.139	0.394	0.220	–0.149	0.188	–0.578 0.331	–0.374	–0.199	0.558	0.192	–0.537	0.021	–0.573
Leaf width (cm)								0.425	0.693	–0.034	0.045	0.140	–0.962*	–0.569	0.357	0.202	0.386	0.022	0.368	–0.697 0.459	–0.451	–0.382	0.471	–0.029	–0.650	–0.149	–0.742
Mother bulb weight (g)									0.927	–0.117	–0.182	–0.546	–0.562	–0.513	–0.463	0.339	–0.666	–0.024	0.045	0.351 0.354	–0.573	–0.029	0.978*	0.715	–0.431	–0.042	0.135
Mother bulb diameter (mm)										–0.278	0.047	–0.242	–0.823	–0.738	–0.340	0.501	–0.390	–0.186	0.007	0.009 0.288	–0.468	–0.001	0.893	0.646	–0.440	0.087	–0.087
Number of bulblet											–0.943	–0.653	0.266	0.814	0.701	–0.971*	0.186	0.995**	0.917	–0.014 0.829	–0.718	–0.910	0.083	–0.680	–0.694	–0.979*	–0.478
Bulblet diameter (mm)												0.866	–0.216	–0.705	–0.457	0.861	0.128	–0.964*	–0.854	–0.233 -0.866	0.840	0.839	–0.362	0.398	0.730	0.951*	0.294
Bulblet weight (g)													–0.179	–0.439	0.037	0.526	0.598	–0.702	–0.539	–0.608 -0.688	0.793	0.514	–0.654	–0.109	0.564	0.685	–0.108
N (%)														0.763	–0.090	–0.444	–0.196	0.201	–0.134	0.559 -0.284	0.335	0.145	–0.555	–0.235	0.494	–0.073	0.532
p (%)															0.491	–0.918	0.128	0.764	0.534	0.216 0.353	–0.221	–0.526	–0.374	–0.678	–0.147	–0.679	–0.071
K(%)																–0.720	0.823	0.673	0.806	–0.707 0.603	–0.380	–0.821	–0.289	–0.937	–0.591	–0.703	–0.891
Ca (%)																	–0.269	–0.944	–0.825	0.018 -0.675	0.530	0.821	0.150	0.776	0.516	0.904	0.412
Mg (%)																		0.138	0.344	–0.921 0.100	0.136	–0.370	–0.588	–0.806	–0.165	–0.174	–0.786
Fe (mg · kg⁻¹)																			0.933	0.002 0.874	–0.781	–0.925	0.177	–0.623	–0.748	–0.992**	–0.484
Cu(mg·kg⁻¹)																				–0.305 0.950	–0.840	–1.000**	0.250	–0.657	–0.901	–0.969*	–0.749
Zn (mg · kg⁻¹)																				–0.157	–0.021	0.332	0.295	0.570	0.299	0.078	0.854
Mn (mg·kg⁻¹)																					–0.966*	–0.944	0.539	–0.390	–0.973*	–0.925	–0.645
Root length (cm)																						0.828	–0.730	0.143	0.948	0.836	0.479
Root surface area (cm²)																							–0.233	0.672	0.899	0.963*	0.767
Root diameter (mm)																								0.560	–0.599	–0.246	–0.011
Root volume (cm³)																									0.322	0.610	0.689
Number of tips																										0.825	0.730
Number of forks																											0.567
Number of crossings

1** p < 0.01

1* p < 0.05

Change rate of bulb properties compared to control values after GA₃ applications. GA₃: gibberellic acid.

Change rate of vase life compared to control values after GA₃ applications. GA₃: gibberellic acid.

Change rate of bulb nutrient content compared to control values after GA₃ applications. GA₃: gibberellic acid.

The rate of change of root architectural features compared to the control values of the analysis results after GA₃ applications. GA₃: gibberellic acid.

DT obtained by J.48 Method. DT, decision tree.

Table 2.

Prediction performance of ML models representing the relationship between GA₃ variables and the change of root architectural features of T. saxatilis.

Classifiers	Accuracy (%)	Kappa	TP	FP	Precision	Recall	F-score
MultilayerPerceptron	85.9	0.81	0.86	0.04	0.88	0.86	0.86
Baggin	74.2	0.65	0.74	0.08	0.75	0.74	0.74
J48	85.7	0.80	0.86	0.05	0.87	0.86	0.86
PART	80.0	0.73	0.80	0.06	0.82	0.80	0.80
LR	94.3	0.92	0.94	0.01	0.94	0.94	0.94
MCC	88.6	0.85	0.87	0.04	0.90	0.89	0.88

1 LR, logistic regression; MCC, multiclassclassifier; ML, machine learning.

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DOI: https://doi.org/10.2478/fhort-2024-0024 | Journal eISSN: 2083-5965 | Journal ISSN: 0867-1761

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Language: English

Page range: 381 - 398

Submitted on: May 7, 2024

Accepted on: Aug 26, 2024

Published on: Oct 9, 2024

Published by: Polish Society for Horticultural Sciences (PSHS)

In partnership with: Paradigm Publishing Services

Publication frequency: 2 issues per year

Keywords:

flower stem length,

GA₃,

growing,

Related subjects:

© 2024 Ömer Sari, published by Polish Society for Horticultural Sciences (PSHS)
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Volume 36 (2024): Issue 3 (December 2024)

Determination of the effect of GA3 applications on plant development, nutrient content change and analysis of root architectural features using ML artificial neural network modelling in Tulipa saxatilis

Figures & Tables

Figure 1.

Figure 2.

Figure 3.

Table 1.

Figure 4.

Figure 5.

Figure 6.

Figure 7.

Figure 8.

Table 2.

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