Canonical correlation between clogging agents and performance of drippers operating with aquaculture effluents

Paiva, Laio A. L. de; Batista, Rafael O.; Silva, Rodrigo R. da; Moniz, Tiago D. da C.; Augusto, Francisco I. S.; Cunha, Weverton A. da; Rodrigues Filho, Ricardo A.; Melo, Stefeson B. de; Costa, Lucas R. da; Medeiros, José F. de; Portela, Jeane C.; Araújo, Antonio G. R.

doi:10.1590/1807-1929/agriambi.v28n5e274127

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Revista Brasileira de Engenharia Agrícola e Ambiental

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Original Article • Rev. bras. eng. agríc. ambient. 28 (5) • May 2024 • https://doi.org/10.1590/1807-1929/agriambi.v28n5e274127 copy

Canonical correlation between clogging agents and performance of drippers operating with aquaculture effluents¹ 1 Research developed at Universidade Federal Rural do Semi-Árido, Departamento de Ciências Agronômicas e Florestais, Mossoró, RN, Brazil

Correlação canônica entre agentes de entupimento e desempenho de gotejadores operando com efluente da aquicultura

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

The canonical correlation is used to correlate groups of distinct variables. The objective of this study was to use canonical correlation analysis to evaluate the interaction between water quality attributes clogging-causing and the hydraulic performance of non-pressure compensating drippers operating with dilutions of aquaculture effluent in well water. The experiment was in a completely randomized design in a split-split-plot scheme with three replicates, with five dilutions in the plots (Dilution 1: 100% aquaculture effluent; Dilution 2: 75% aquaculture effluent + 25% well water; Dilution 3: 50% aquaculture effluent + 50% well water; Dilution 4: 25% aquaculture effluent + 75% well water; and Dilution 5: 100% well water), three emitters in the sub-plots (ST (1.6 L h^-1), SL (1.6 L h^-1) and NJ (1.7 L h^-1)), and three operating times in the sub-subplots (0, 80 and 160 hours, in which 0 hours operating time means the start of evaluations). The statistical analyses performed were correlation matrix and canonical analysis. The canonical correlation analysis indicated that when the concentrations of attributes increase, the hydraulic performance of the drippers decreases. The interaction of this group of attributes indicates that the clogging of drippers operating with the five dilutions of aquaculture effluent in well water occurs by the combined action of physical, chemical, and biological agents. The ST dripper was the least sensitive to the group of quality attributes of the dilutions, whereas the most sensitive was the SL dripper.

Key words:
agricultural reuse; multivariate statistics; emitters

HIGHLIGHTS:

Clogging agents have inverse canonical correlation to hydraulic performance coefficients of non-self-compensating emitters.

Canonical analysis indicates that clogging of drippers is caused by combination of physical, chemi-cal, and biological agents.

The dripper most susceptible to clogging was the ST (1.6 L h^-1), and the least sus-ceptible was the SL (1.6 L h^-1).

Dripper	Specifications
ST	Nominal flow rate: 1.60 L h^-1; flow rate coefficient: 0.53; exponent of the flow rate that characterizes the flow regime: 0.48; filtration area: 34 mm²; labyrinth length: 23 mm; coefficient of variation of manufacture ±7; recommended pressure range: 60 to 300 kPa; spacing between emitters: 0.30 m.
SL	Nominal flow rate: 1.60 L h^-1; flow rate coefficient: 0.57; exponent of the flow rate that characterizes the flow regime: 0.45; filtration area: 17 mm²; labyrinth length: 13 mm; coefficient of variation of manufacture ±7; recommended pressure range: 90 to 100 kPa; spacing between emitters: 0.30 m.
NJ	Nominal flow rate: 1.70 L h^-1; flow rate coefficient: 0.56; exponent of the flow rate that characterizes the flow regime: 0.46; filtration area: 6.0 mm²; labyrinth length: 44 mm; coefficient of variation of manufacture ±5; recommended pressure range: 70 to 300 kPa; spacing between emitters: 0.20 m.

Coefficient	Equation	Variables	Reference	N° of equation
Flow rate	$Q = \frac{V o l}{1000 t_{e m}} \cdot 60$	Q: Emitter flow rate, L.h^-1; Vol: Volume of effluent collected, mL; and tem: Time of effluent collection, min.		(1)
Relative flow rate	$Q R = \frac{q_{a}}{q_{i}}$	QR: Relative flow rate, L h^-1; qa: Actual flow rate, L h^-1; and qi: Initial flow rate, L h^-1.	Capra & Scicolone (1998Capra, A.; Scicolone, B. Water quality and distribution uniformity in drip/trickle irrigation systems. Journal of Agricultural Engineering Research, v.70, p.355-365, 1998. https://doi.org/10.1006/jaer.1998.0287 https://doi.org/10.1006/jaer.1998.0287... )	(2)
Reduction in relative flow rate	$R Q R = 100 (\frac{q_{i} - q_{a}}{q_{i}})$	RQR: Reduction in relative flow rate, %; qi: Initial flow rate, L h^-1; and qa: Actual flow rate, L h^-1.	Capra & Scicolone (1998Capra, A.; Scicolone, B. Water quality and distribution uniformity in drip/trickle irrigation systems. Journal of Agricultural Engineering Research, v.70, p.355-365, 1998. https://doi.org/10.1006/jaer.1998.0287 https://doi.org/10.1006/jaer.1998.0287... )	(3)
Distribution uniformity coefficient	$D U C = 100 \frac{q_{25 %}}{\bar{q}}$	DUC: Distribution uniformity coefficient, % q25%: Average of the 25% lowest flow rate values of the emitters, L h^-1, and q: Average flow rate of the emitters, L h^-1.	Keller & Karmeli (1975Keller, J.; Karmeli, D. Trickle irrigation design. Glendora: Rain Bird Sprinkler Manufacturing, 1975. 133p.)	(4)
Coefficient variation of flow rate	$C V Q = 100 \frac{\sqrt{\sum_{i = 0}^{n} \frac{{(q_{i} - \bar{q})}^{2}}{n_{e} - 1}}}{\bar{q}}$	CVQ: Coefficient of variation of flow rate, %; qi: Flow rate of each emitter, L h^-1; q: Average flow rate of the emitters, L h^-1, and ne: Number of emitters evaluated.	Bralts et al. (1987Bralts, V.F.; Edward, D. M.; Wu, I. P. Drip irrigation design and evaluation based on statistical uniformity concept. In: Hillel, D. (Ed). Advances in irrigation. Orlando: Academic Press, v.4, p.67-117, 1987. https://doi.org/10.1016/B978-0-12-024304-4.50005-5 https://doi.org/10.1016/B978-0-12-024304... )	(5)
Statistical uniformity coefficient	$U s = 100 (1 - C V Q)$	Us: Statistical uniformity coefficient of effluent application, %; and CVQ: Coefficient of variation of flow rate, %.	Bralts et al. (1987Bralts, V.F.; Edward, D. M.; Wu, I. P. Drip irrigation design and evaluation based on statistical uniformity concept. In: Hillel, D. (Ed). Advances in irrigation. Orlando: Academic Press, v.4, p.67-117, 1987. https://doi.org/10.1016/B978-0-12-024304-4.50005-5 https://doi.org/10.1016/B978-0-12-024304... )	(6)

Dilutions and time of operation	Water quality attributes
Dilutions and time of operation	pH	EC	Ca²⁺	Mg²⁺	CO₃^2-	HCO₃^-	TC	TTC	TSS	TDS	Mn⁺	Fe⁺	S⁺	Na⁺	LSI	Tur	T
D1 – 0 hours	7.93	5.88	20.40	33.80	0.14	1.78	180.00	16.00	44.00	6850.00	0.05	0.45	0.11	42.70	-0.20	9.9	30
D2 – 0 hours	8.04	5.01	13.50	25.80	0.20	1.76	70.00	12.00	26.00	5608.00	0.00	0.06	0.04	35.03	0.01	3.9	34
D3 – 0 hours	8.06	3.60	11.90	17.80	0.25	1.94	120.00	20.00	4.00	3738.00	0.02	0.34	0.10	25.66	0.01	4.8	34
D4 – 0 hours	7.92	2.26	5.30	13.10	0.12	1.51	110.00	15.00	14.00	2138.00	0.02	0.11	0.04	15.26	-0.46	5.5	33
D5 – 0 hours	7.05	0.52	0.60	0.28	0.05	1.66	20.00	0.00	2.00	452.00	0.00	0.00	0.01	7.98	-2.12	0.23	35
D1 – 80 hours	7.62	8.45	16.90	41.80	0.00	1.89	420.00	60.00	6.00	6644.40	0.02	0.06	0.08	70.42	-1.46	4.2	28
D2 – 80 hours	7.61	5.37	12.60	17.90	0.00	1.71	70.00	20.00	4.00	4300.00	0.02	0.09	0.08	45.44	-0.14	2.6	29
D3 – 80 hours	7.67	4.18	8.70	11.50	0.05	1.66	60.00	30.00	4.00	3246.00	0.00	0.01	0.11	35.55	0.13	1.5	28
D4 – 80 hours	7.64	3.34	6.90	11.40	0.07	1.53	150.00	60.00	4.00	2470.00	0.00	0.08	0.08	29.62	-0.24	1.36	27
D5 – 80 hours	7.55	0.59	0.67	0.13	0.23	1.42	40.00	10.00	2.00	392.00	0.00	0.04	0.04	6.52	-1.31	0.19	30
D1 – 160 hours	7.65	10.33	18.00	54.70	0.00	2.40	460.00	90.00	68.00	7778.00	0.00	0.35	0.23	83.43	-2.27	10.7	29
D2 – 160 hours	8.20	5.49	10.00	23.10	0.09	1.72	70.00	20.00	6.00	3878.00	0.01	0.05	0.10	42.84	0.59	3.8	26
D3 – 160 hours	8.28	4.26	6.80	21.20	0.15	1.51	60.00	10.00	6.00	2864.00	0.00	0.15	0.19	33.99	0.47	2.5	26
D4 – 160 hours	8.47	3.70	6.00	15.70	0.20	1.45	50.00	10.00	4.00	2414.00	0.00	0.03	0.16	31.50	0.62	3	26
D5 – 160 hours	8.50	0.67	0.52	0.31	0.33	1.40	70.00	20.00	2.00	308.00	0.00	0.03	0.17	8.60	-0.28	0.5	27

Dilutions and time of operation	Hydraulic performance coefficients
Dilutions and time of operation	QR ST	QR SL	QR NJ	DUC ST	DUC SL	DUC NJ	Q ST	Q SL	Q NJ
D1 – 0 hours	1.00	1.00	1.00	95.63	93.63	94.42	1.5	1.19	1.32
D2 – 0 hours	1.00	1.00	1.00	92.20	95.85	96.40	1.48	1.22	1.34
D3 – 0 hours	1.00	1.00	1.00	99.07	97.90	97.87	1.48	1.25	1.37
D4 – 0 hours	1.00	1.00	1.00	97.13	96.54	96.98	1.47	1.23	1.35
D5 – 0 hours	1.00	1.00	1.00	95.93	97.39	97.76	1.47	1.24	1.34
D1 – 80 hours	0.96	0.73	0.90	91.11	92.58	91.49	1.43	1.09	1.35
D2 – 80 hours	0.86	0.82	0.88	77.97	95.26	91.95	1.28	1.21	1.31
D3 – 80 hours	1.00	0.81	0.89	95.46	90.11	84.59	1.48	1.2	1.31
D4 – 80 hours	1.04	0.88	0.94	95.27	91.42	91.46	1.52	1.29	1.38
D5 – 80 hours	0.95	0.80	0.89	92.78	92.74	92.78	1.4	1.18	1.31
D1 – 160 hours	0.90	0.63	0.81	84.80	58.70	85.71	1.34	0.95	1.21
D2 – 160 hours	0.77	1.02	1.12	74.92	90.72	89.73	1.14	1.21	1.34
D3 – 160 hours	0.99	0.73	0.83	94.47	82.16	75.02	1.46	1.08	1.23
D4 – 160 hours	1.00	0.79	0.91	95.44	93.24	94.90	1.46	1.16	1.33
D5 – 160 hours	0.95	0.79	0.90	94.64	96.14	92.40	1.4	1.17	1.32
	Hydraulic performance coefficients
	RQR ST	RQR SL	RQR NJ	CVQ ST	CVQ SL	CVQ NJ	Us ST	Us SL	Us NJ
D1 – 0 hours	0.00	0.00	0.00	6.26	7.54	6.52	93.74	92.46	93.48
D2 – 0 hours	0.00	0.00	0.00	8.86	5.66	6.72	91.14	94.34	93.28
D3 – 0 hours	0.00	0.00	0.00	2.86	3.44	4.3	97.14	96.56	95.7
D4 – 0 hours	0.00	0.00	0.00	5.71	6.13	5.88	94.29	93.87	94.12
D5 – 0 hours	0.00	0.00	0.00	6.64	6.28	6.92	93.36	93.72	93.08
D1 – 80 hours	4.10	8.54	-2.38	8.08	6.95	8.71	91.92	93.05	91.29
D2 – 80 hours	13.87	0.10	2.85	37.7	9.94	12.97	62.3	90.06	87.03
D3 – 80 hours	0.00	4.06	4.56	5.88	16.49	19.35	94.12	83.51	80.65
D4 – 80 hours	-3.74	-5.15	-2.00	5.66	10.26	9.99	94.34	89.74	90.01
D5 – 80 hours	4.78	4.96	2.39	6.63	6.53	9.39	93.37	93.47	90.61
D1 – 160 hours	10.37	20.61	8.17	21.51	40.24	18.55	78.49	59.76	81.45
D2 – 160 hours	23.1	0.24	0.59	59.27	13.19	14.97	40.73	86.81	85.03
D3 – 160 hours	0.99	13.75	10.21	9.22	25.33	30.97	90.78	74.67	69.03
D4 – 160 hours	0.48	5.76	1.57	8.44	9.64	8.59	91.56	90.36	91.41
D5 – 160 hours	4.98	6.23	1.58	7.96	7.09	9.34	92.04	92.91	90.66

	pH	EC	Ca²⁺	Mg²⁺	CO₃²	HCO₃	TC	TTC	TSS	TDS	Mn⁺	Fe⁺	S⁺	Na⁺	LSI	Tur	T	QR ST	QR SL	QR NJ	DUC ST	DUC SL	DUC NJ	Q ST	Q SL	Q NJ	RQR ST	RQR SL	RQR NJ	CVQ ST	CVQ SL	CVQ NJ	Us ST	Us SL	Us NJ
pH	1.00
EC	-0.03	1.00
Ca²⁺	-0.02	0.89*	1.00
Mg²⁺	0.02	0.97*	0.89*	1.00
CO₃²	0.64*	-0.59*	-0.43	-0.48	1.00
HCO₃	-0.28	0.81*	0.76*	0.82*	-0.48	1.00
TC	-0.20	0.81*	0.67*	0.84*	-0.48	0.77*	1.00
TTC	-0.22	0.71*	0.50	0.66*	-0.52*	0.66*	0.87*	1.00
TSS	-0.06	0.66*	0.67*	0.76*	-0.24	0.73*	0.63*	0.52*	1.00
TDS	-0.03	0.94*	0.98*	0.95*	-0.47	0.80*	0.74*	0.57*	0.73*	1.00
Mn⁺	-0.01	0.30	0.62*	0.37	-0.13	0.21	0.25	-0.05	0.34	0.50	1.00
Fe⁺	0.06	0.47	0.67*	0.59*	0.00	0.60*	0.46	0.28	0.71*	0.61*	0.66*	1.00
S⁺	0.51*	0.46	0.25	0.45	0.06	0.31	0.38	0.43	0.42	0.31	-0.07	0.38	1.00
Na⁺	-0.07	0.99*	0.84*	0.94*	-0.63*	0.79*	0.83*	0.75*	0.62*	0.90*	0.24	0.40	0.48	1.00
LSI	0.73*	-0.15	-0.03	-0.21	0.38	-0.46	-0.54*	-0.43	-0.37	-0.11	0.06	-0.10	0.13	-0.20	1.00
Tur	0.08	0.73*	0.81*	0.84*	-0.25	0.73*	0.66*	0.45	0.88*	0.82*	0.61*	0.84*	0.39	0.67*	-0.16	1.00
T	-0.44	-0.24	0.00	-0.13	0.08	0.21	-0.11	-0.29	0.12	-0.02	0.15	0.17	-0.62*	-0.30	-0.38	0.10	1.00
QR ST	-0.09	-0.33	-0.16	-0.24	0.25	-0.26	-0.10	-0.11	-0.08	-0.19	0.02	0.07	-0.19	-0.35	-0.03	-0.12	0.33	1.0
QR SL	-0.03	-0.38	-0.05	-0.31	0.20	-0.18	-0.48	-0.55*	-0.17	-0.15	0.30	0.05	-0.67*	-0.46	0.27	-0.02	0.58*	0.1	1.00
QR NJ	0.07	-0.22	0.00	-0.18	0.14	-0.10	-0.33	-0.41	-0.17	-0.07	0.23	-0.03	-0.56*	-0.29	0.27	0.02	0.36	-0.2	0.92*	1.00
DUC ST	0.04	-0.46	-0.29	-0.34	0.45	-0.31	-0.16	-0.22	-0.15	-0.33	0.01	0.09	-0.14	-0.48	-0.02	-0.14	0.34	0.9	0.12	-0.10	1.00
DUC SL	0.06	-0.65*	-0.36	-0.65*	0.38	-0.64*	-0.63*	-0.70*	-0.71*	-0.48	0.18	-0.38	-0.72*	-0.67*	0.37	-0.53*	0.31	0.2	0.65*	0.55*	0.30	1.00
DUC NJ	-0.16	-0.33	-0.08	-0.26	0.25	-0.06	-0.15	-0.27	-0.10	-0.14	0.25	-0.02	-0.64*	-0.36	-0.16	-0.01	0.64*	0.2	0.63*	0.57*	0.21	0.61*	1.00
Q ST	0.42	0.05	-0.30	0.01	0.09	-0.19	-0.02	0.12	-0.09	-0.21	-0.48	-0.24	0.57*	0.10	0.16	-0.17	-0.72*	-0.4	-0.54*	-0.34	-0.37	-0.44	-0.51	1.00
Q SL	-0.09	-0.64*	-0.36	-0.68*	0.24	-0.54*	-0.68*	-0.54*	-0.59*	-0.49	0.06	-0.29	-0.73*	-0.67*	0.39	-0.48	0.35	0.2	0.78*	0.65*	0.23	0.84*	0.57*	-0.45	1.00
Q NJ	-0.06	-0.40	-0.17	-0.41	0.18	-0.34	-0.28	-0.26	-0.53*	-0.27	0.13	-0.28	-0.71*	-0.41	0.22	-0.33	0.30	0.2	0.67*	0.67*	0.25	0.82*	0.74*	-0.46	0.83*	1.00
RQR ST	0.09	0.34	0.17	0.25	-0.26	0.27	0.11	0.13	0.09	0.20	-0.02	-0.07	0.20	0.36	0.02	0.13	-0.34	-1.0	-0.08	0.17	-0.94*	-0.26	-0.17	0.42	-0.26	-0.24	1.0
RQR SL	0.13	0.49	0.18	0.52*	-0.12	0.43	0.55*	0.45	0.46	0.31	-0.21	0.21	0.76*	0.52*	-0.35	0.34	-0.34	-0.2	-0.81*	-0.71*	-0.12	-0.81*	-0.63*	0.50	-0.97*	-0.86*	0.2	1.00
RQR NJ	0.15	0.22	0.00	0.21	-0.08	0.18	0.04	0.11	0.30	0.08	-0.27	0.18	0.69*	0.24	0.01	0.14	-0.32	-0.2	-0.60*	-0.65*	-0.16	-0.70*	-0.81*	0.48	-0.66*	-0.93*	0.2	0.76*	1.00
CVQ ST	0.09	0.33	0.19	0.22	-0.35	0.20	-0.01	0.07	0.04	0.21	-0.01	-0.10	0.12	0.34	0.19	0.10	-0.34	-0.9	0.07	0.30	-0.95*	-0.19	-0.17	0.39	-0.08	-0.14	0.9*	-0.01	0.11	1.0
CVQ SL	-0.01	0.59*	0.29	0.56*	-0.41	0.53*	0.48	0.59*	0.60*	0.40	-0.23	0.30	0.76*	0.61*	-0.23	0.43	-0.39	-0.3	-0.64*	-0.56*	-0.32	-0.97*	-0.74*	0.48	-0.79*	-0.87*	0.3	0.80*	0.82*	0.2	1.0
CVQ NJ	0.14	0.28	0.02	0.20	-0.27	0.06	0.04	0.18	0.08	0.09	-0.31	-0.03	0.60*	0.32	0.17	-0.03	-0.57*	-0.2	-0.56*	-0.52*	-0.28	-0.60*	-0.98*	0.54*	-0.54*	-0.77*	0.2	0.61*	0.86*	0.3	0.8*	1.0
Us ST	-0.09	-0.33	-0.19	-0.22	0.35	-0.20	0.01	-0.07	-0.04	-0.21	0.01	0.10	-0.12	-0.34	-0.19	-0.10	0.34	0.9	-0.07	-0.30	0.95*	0.19	0.17	-0.39	0.08	0.14	-0.9*	0.01	-0.11	-1.0*	-0.2	-0.3	1.0
Us SL	0.01	-0.59*	-0.29	-0.56*	0.41	-0.53*	-0.48	-0.59*	-0.60*	-0.40	0.23	-0.30	-0.76*	-0.61*	0.23	-0.43	0.39	0.3	0.648	0.56*	0.32	0.97*	0.74*	-0.48	0.79*	0.87*	-0.3	-0.80*	-0.82*	-0.2	-1.0*	-0.8*	0.2	1.0
Us NJ	-0.14	-0.28	-0.02	-0.20	0.27	-0.06	-0.04	-0.18	-0.08	-0.09	0.31	0.03	-0.60*	-0.32	-0.17	0.03	0.57*	0.2	0.56*	0.52*	0.28	0.60*	0.98*	-0.54*	0.54*	0.77*	-0.2	-0.61*	-0.86*	-0.3	-0.8*	-1.0*	0.3	0.8*	1.0

Groups	Canonical analysis 1		Canonical analysis 2		Canonical analysis 3
	Variables	Canonical pair	Variables	Canonical pair	Variables	Canonical pair
	Variables	1	Variables	1	Variables	1
Water quality attributes	EC	-0.67	EC	0.65	EC	0.67
	Ca²⁺	-0.42	Ca²⁺	0.34	Ca²⁺	0.38
	Mg²⁺	-0.68	Mg²⁺	0.64	Mg²⁺	0.67
	TC	-0.64	TC	0.60	TC	0.61
	TSS	-0.80	TSS	0.69	TSS	0.73
	Fe⁺	-0.45	Fe⁺	0.34	Fe⁺	0.37
	S⁺	-0.62	S⁺	0.74	S⁺	0.72
Hydraulic performance coefficients	QR - ST	0.32	Q - ST	0.51	RQR - ST	0.38
	QR - SL	0.51	Q - SL	-0.83	RQR - SL	0.77
	QR - NJ	0.41	Q - NJ	-0.79	RQR - NJ	0.66
	DUC - ST	0.38	US - ST	-0.30	CVQ - ST	0.31
	DUC - SL	0.97	US - SL	-0.95	CVQ - SL	0.95
	DUC - NJ	0.43	US - NJ	-0.56	CVQ - NJ	0.54
R		0.995		0.999		0.998
(p ≤ 0.05)		0.02		0.00002		0.0003

Unidade Acadêmica de Engenharia Agrícola Unidade Acadêmica de Engenharia Agrícola, UFCG, Av. Aprígio Veloso 882, Bodocongó, Bloco CM, 1º andar, CEP 58429-140, Tel. +55 83 2101 1056 - Campina Grande - PB - Brazil
E-mail: revistagriambi@gmail.com

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[1] * Corresponding author - E-mail: laioariel@yahoo.com.br

Brasil

Brasil

Canonical correlation between clogging agents and performance of drippers operating with aquaculture effluents1 1 Research developed at Universidade Federal Rural do Semi-Árido, Departamento de Ciências Agronômicas e Florestais, Mossoró, RN, Brazil

Correlação canônica entre agentes de entupimento e desempenho de gotejadores operando com efluente da aquicultura

ABSTRACT

HIGHLIGHTS:

Canonical correlation between clogging agents and performance of drippers operating with aquaculture effluents¹ 1 Research developed at Universidade Federal Rural do Semi-Árido, Departamento de Ciências Agronômicas e Florestais, Mossoró, RN, Brazil