© The Authors, 2026, Published by the Universidad del Zulia*Corresponding author:nancyhernandez@fa.luz.edu.ve
Keywords:
Eutrophication
Phytoplankton
Zooplankton
RCI
Bioindicator
Integration of zootechnical and ecological factors to evaluate the physiological well-being of
Penaeus vannamei on farms connected to Lake Maracaibo, Venezuela
Integración de factores zootécnicos y ecológicos para evaluar el bienestar siológico de Penaeus
vannamei en ncas conectadas al lago de Maracaibo, Venezuela
Integração de fatores zootécnicos e ecológicos para avaliar o bem-estar siológico de Penaeus
vannamei em fazendas conectadas ao Lago Maracaibo, Venezuela
Nancy Hernández de Guerrero
1*
Randi Guerrero-Riós
2
Jeny Reyes-Lujan
2
Juan Bárcenas
3
Roberta Mora
4†
Enrique Quintero-Torres
5
Rev. Fac. Agron. (LUZ). 2026, 43(3): e264333
ISSN 2477-9407
DOI: https://doi.org/10.47280/RevFacAgron(LUZ).v43.n3.I
Animal production
Associate editor: Dra. Rosa Razz
University of Zulia, Faculty of Agronomy
Bolivarian Republic of Venezuela
1
Laboratorio de Ecología, Facultad de Agronomía,
Universidad del Zulia (LUZ), Apartado postal 4011.
Maracaibo, Venezuela.
2
Laboratorio de Zoología de Invertebrados, Facultad de
Experimental de Ciencias, Universidad del Zulia (LUZ).
Apartado postal 4011. Maracaibo, Venezuela.
3
Departamento de Ingeniería, Suelos y Agua, Facultad de
Agronomía, Universidad del Zulia (LUZ). Apartado postal
4011. Maracaibo, Venezuela.
4
Laboratorio de Organismos Fotosintéticos, Departamento
de Biología, Facultad de Experimental de Ciencias,
Universidad del Zulia (LUZ). Apartado postal 4011.
Maracaibo, Venezuela.
5
Laboratorio de Ecología Acuática, Centro de Ecología,
Instituto Venezolano de Investigaciones Cientícas,
Apartado Postal 20632, 1020-A Caracas, Venezuela.
Received: 01-02-2026
Accepted: 04-05-2026
Published: 15-06-2026
Abstract
The semi-intensive commercial shrimp farming in Lake Maracaibo,
Venezuela, is aected by eutrophication processes resulting from
excess nutrients, which favor the proliferation of microalgae and the
deterioration of water quality. There is limited information on the
relationship between production variables, uctuations in planktonic
communities, and their impact on the physiological state of the shrimp.
Therefore, the objective of this study was to analyze the relationship
between production and ecological variables with the Relative Condition
Index (RCI) as a physiological indicator of Penaeus vannamei during
a ten-week grow-out cycle. Production and ecological variables were
monitored weekly, including qualitative and quantitative analyses of
phytoplankton and zooplankton. Data were evaluated using Pearson
correlation, variable selection with VIF and FCR, logistic regression
with Firth’s bias reduction, and deviance analysis. Shrimp exhibited a
nal average RCI of 1.36 ± 0.92 and an average FRC of 1.81 ± 0.89.
The phytoplankton community was dominated by Cyanobacteria
(57.8%), followed by Chlorophyta (32.4 %) and Heterokontophyta
(9.1 %), while zooplankton was primarily represented by copepods
(69.9 %). However, the model showed a positive association between
RCI and the abundance of Chlorella sp. and barnacle nauplii, and a
negative relationship with Mesocyclops sp. These results suggest that
the nutritional and functional quality of plankton may be more relevant
than its total abundance, constituting a bioindicator of physiological
well-being and a potential supplementary food source.
This scientic publication in digital format is a continuation of the Printed Review: Legal Deposit pp 196802ZU42, ISSN 0378-7818.
Rev. Fac. Agron. (LUZ). 2026, 43(3): e264330 July-September ISSN 2477-9407.
2-7 |
Resumen
El cultivo semiintensivo comercial de camarón en el Lago de
Maracaibo, Venezuela, se ve afectado por procesos de eutrozación
derivados del exceso de nutrientes, los cuales favorecen la
proliferación de microalgas y el deterioro de la calidad del agua. Existe
escasa información sobre la relación entre las variables productivas,
las uctuaciones de las comunidades planctónicas y su impacto sobre
el estado siológico del camarón. Por ello, el objetivo de este estudio
fue analizar la relación entre variables productivas y ecológicas con
el Índice de Condición Relativa (ICR) como indicador siológico
de Penaeus vannamei durante un ciclo de engorde de diez semanas.
Se monitorearon semanalmente variables productivas y ecológicas,
incluyendo análisis cualitativos y cuantitativos de toplancton y
zooplancton. Los datos fueron evaluados mediante correlación de
Pearson, selección de variables con VIF y AIC, regresión logística
con reducción de sesgo de Firth y análisis de devianza. Los
camarones presentaron un ICR promedio nal de 1,36 ± 0,92 y un
ICA promedio de 1,81 ± 0,89. La comunidad toplanctónica estuvo
dominada por Cyanobacteria (57,8 %), seguida por Chlorophyta
(32,4%) y Heterokontophyta (9,1 %), mientras que el zooplancton
estuvo representado principalmente por copépodos (69,9 %). Sin
embargo, el modelo mostró una asociación positiva entre el ICR y la
abundancia de Chlorella sp. y nauplios de cirrípedos, y una relación
negativa con Mesocyclops sp. Estos resultados sugieren que la calidad
nutricional y funcional del plancton puede tener mayor relevancia
que su abundancia total, constituyendo un bioindicador del bienestar
siológico y una potencial fuente alimenticia complementaria.
Palabras clave: eutrozación, toplancton, zooplancton, ICR,
bioindicador.
Resumo
A carcinicultura comercial semi-intensiva no Lago Maracaibo,
Venezuela, é afetada por processos de eutrozação resultantes do
excesso de nutrientes, que favorecem a proliferação de microalgas
e a deterioração da qualidade da água. Há pouca informação sobre
a relação entre variáveis de produção, utuações nas comunidades
planctônicas e seu impacto no estado siológico do camarão.
Portanto, o objetivo deste estudo foi analisar a relação entre variáveis
de produção e ecológicas com o Índice de Condição Relativa (ICR)
como indicador siológico de Penaeus vannamei durante um ciclo
de cultivo de dez semanas. As variáveis de produção e ecológicas
foram monitoradas semanalmente, incluindo análises qualitativas
e quantitativas de toplâncton e zooplâncton. Os dados foram
avaliados utilizando correlação de Pearson, seleção de variáveis com
VIF e AIC, regressão logística com redução de viés de Firth e análise
de deviance. O camarão apresentou um ICR médio nal de 1,36 ±
0,92 e um ICA médio de 1,81 ± 0,89. A comunidade toplanctônica
foi dominada por cianobactérias (57,8 %), seguidas por clorótas
(32,4 %) e heterocontótas (9,1 %), enquanto o zooplâncton foi
representado principalmente por copépodes (69,9 %). No entanto,
o modelo revelou uma relação positiva entre o índice de condição
relativa (ICR) e a abundância de Chlorella sp. e náuplios de cracas, e
uma relação negativa com Mesocyclops sp. Esses resultados sugerem
que a qualidade nutricional e funcional do plâncton pode ser mais
relevante do que sua abundância total, constituindo um bioindicador
de bem-estar siológico e um potencial fonte alimentar suplementar.
Palavras-chave: eutrozação, toplâncton, zooplâncton, ICR,
bioindicador.
Introduction
The semi-intensive shrimp farms established in Lake of Maracaibo
are supplied with water from the lake, which is characterised by
eutrophic conditions (Redeld, 1958); therefore, the eutrophic
condition of the farming systems is implicit, and this fact poses a
challenge for maintaining the organisms in the aquaculture systems
(Martínez et al., 2021). Eutrophication generates massive algal
blooms that are intensied by the inecient use of fertilisers in the
systems, leading to changes in plankton, a decrease in dissolved
oxygen, acidication of the environment, accumulation of nitrates and
ammonium, and a general deterioration in the quality of the rearing
environment, compromising the growth and health of the shrimp
(Qiao et al., 2020). Thus, lake eutrophication, combined with poor
aquaculture management practices, aects the growth of organisms,
leads to mass mortality and prolongs production cycles (Martínez et
al., 2021).
In this context, the inclusion of zootechnical variables such as
body condition scores is useful for assessing the physiological well-
being of shrimp. The feed conversion ratio (FCR) is a key metric for
determining the eciency of nutrient biotransformation into somatic
growth, whilst the relative condition index (RCI) is an indicator of
physiological status (Berry et al., 2019). The adoption of the relative
condition index (RCI) in intensive aquaculture management systems
provides relevant information for optimising production cycles,
nutritional planning and the operational organisation of farmed
organisms (Bonilla-Flórez et al., 2017). Furthermore, the structure
and stability of the planktonic community have been associated
with better rearing conditions and an adequate physiological state,
indirectly inuencing indicators of body performance and production
eciency. In this context, the joint monitoring of the RCI, the
feed conversion ratio (FCR) and planktonic dynamics allows for a
comprehensive assessment of the organisms’ welfare and growth,
facilitating the design of adaptive management strategies and the
mitigation of potential environmental impacts (Lyu et al., 2021).
Planktonic communities in ponds are essential both as a natural
food source and because they can induce changes in the aquatic
environment; this makes them suitable for use as indicator organisms
in water quality assessment (Samosir et al., 2021). Their response
to variations in dissolved oxygen or nutrient load provides key
metrics for trophic diagnosis and the operational sustainability of
the production system (Gómez et al., 2020). A direct and positive
correlation has been documented between the abundance of
microalgae such as Chlorella vulgaris and the production performance
of P. vannamei. Various studies demonstrate that high concentrations
of this chlorophyte optimise yield, survival and physiological
condition, as well as signicantly improving the feed conversion
ratio (Eissa et al., 2023; Hudson, 2024). Furthermore, regarding the
contribution of zooplankton, Artemia nauplii remain fundamental in
larviculture; their high energy density and essential fatty acid prole
establish them as the optimal nutritional source for the early stages
of P. vannamei (Van Stappen et al., 2024). Despite the importance of
plankton as a bioindicator, knowledge of planktonic communities in
the aquaculture facilities of Lake of Maracaibo is limited compared
to other regions such as Brazil and Ecuador (Casé et al., 2008; Neto
et al., 2009; Patricio et al., 2023; Delgado et al., 2024).
This scientic publication in digital format is a continuation of the Printed Review: Legal Deposit pp 196802ZU42, ISSN 0378-7818.
Hernández et al. Rev. Fac. Agron. (LUZ). 2026, 43(3): e264330
3-7 |
At present, there is a knowledge gap regarding the relationship
between production variables and uctuations in planktonic
communities, and their potential impact on the physiological
condition of shrimp. This has limited the ability to implement
management strategies based on production and ecological indicators
that would optimise production and mitigate negative impacts.
From the perspective of the overall functioning of intensive farming
systems, the aim of this study is to analyse the relationship between
productive and ecological planktonic variables and the physiological
condition of P. vannamei during the grow-out cycle.
Materials and methods
Study area
The study was conducted at a shrimp farm located in the
municipality of Rosario de Perijá, on the western shore of Lake of
Maracaibo. The area has a tropical climate with a bimodal rainfall
pattern, with peaks between May and October and troughs between
January and April, and an average annual rainfall of 1057 mm. The
water temperature ranges between 26 and 28 °C, which favours the
aquaculture production of P. vannamei in the region (Lozada and
Graterol, 2003) (Figure 1).
Figure 1. Geographical location of the aquaculture farm on Lake
of Maracaibo, Venezuela.
Sampling design
Seven sampling points were established: two control points, one
outside the farming system known as the ‘Lake station’ and one inside
the system located at the sluice gate, known as the ‘Canal station’; and a
block comprising ve ponds lled and stocked simultaneously, ensuring
uniform conditions for the study. The sampling period ran from 13
April to 14 June 2024 and covered exclusively the fattening phase of
P. vannamei. Sampling was carried out weekly, with collections taking
place in the morning (Cremen et al., 2007; Lyu et al., 2021) (Figure 2).
Figure 2. Spatial distribution of sampling points in the culture ponds
(A01–A05), the channel and the lake used during the study.
Planktonic community in P. vannamei culture
Phytoplankton samples were taken in triplicate in the morning,
between 8:00 and 10:00 am, to ensure consistency in light conditions
and biological activity. Phytoplankton was collected at a depth of
between 30 and 50 cm using a rod tted at its distal end with a 350
mL plastic collector. The sample was xed in situ by adding 1 mL of
1 % concentrated Lugol’s solution (Cremen et al., 2007). Samples for
the identication and quantication of zooplankton were collected by
ltering 5 L of water using a plastic collector of the same volume,
employing a plankton net with a mesh size of 150
μm. The samples
were xed in situ with 4 % formaldehyde (Casé et al., 2008). The
samples were labelled and stored in the dark until subsequent analysis
in the laboratory.
For phytoplankton quantication, a 0.1 mm deep Neubauer
haemocytometer was used (Martínez et al., 2021), and for zooplankton
quantication, a 1 mL Sedgewick-Rafter counting chamber was used;
in both cases, quantication was performed in triplicate (Picapedra
et al., 2020). Observations and counts were carried out using a high-
resolution Carl Zeiss
®
binocular microscope.
The taxonomic identication of zooplankton was carried out using
the taxonomic keys of Bradford-Grieve (2002) and Ávila-Parga et
al. (2022), validated against the World Register of Marine Species
(WoRMS, 2023) database. Meanwhile, for the taxonomic identication
of phytoplankton, recognised taxonomic keys were used, including
those proposed by Yacubson (1972, 1974a, 1974b, 1974c), validated
against the updated database by Guiry and Guiry (2024).
Estimation of production variables
Production variables were measured weekly during the fattening
phase in ve ponds within a semi-intensive system. The following
metrics were calculated: harvest density (individuals.m⁻²), weight
gain (g), survival (%), yield per hectare (kg.ha⁻¹) and the Feed
Conversion Ratio (FCR) (Domingos and Vinatea, 2008). To calculate
the Relative Condition Index (RCI) of P. vannamei shrimp, the model
by Peig and Green (2010). The scalar mass of each individual was
estimated using the formula (Mi = Pi (LT0 / LTi)
b
), where Pi is the
individual weight, LT0 is the average length calculated as the sum
of the lengths divided by the total number of individuals, and LTi
is the length of the individual; where an RCI value greater than 1
indicates good growth and lower values indicate insucient growth.
For greater accuracy, the population standard deviation of the RCI
was also calculated to assess variability in population growth.
In addition, the total abundance of phytoplankton and zooplankton
was correlated with production variables through weekly comparative
analyses, assessing their potential inuence on growth, survival, ICA
and relative condition index during the culture. Dierences between
tanks for the FCR were assessed using one-way ANOVA (or Kruskal-
Wallis, as appropriate), using a signicance level of α = 0.05.
RCI Modelling vs. Productive Factors
Collinearity Assessment: using Pearson’s correlation, the Survival
variable was removed as it showed a strong correlation (r ≈ 0.9)
with harvest density and ICA. The step VIF function (pedometrics
package, Samuel-Rosa, 2022) was then used to select a subset of
predictor variables that maintained a Generalised Variance Ination
Factor (GVIF) below the collinearity threshold. Values of GVIF ≥
4 and GVIF ≥ 10 were considered indicative of correlation issues or
serious correlation issues, respectively.
Handling of Complete Separation: Due to a problem of complete
separation in the inuence of the FRC variable on the RCI, the FRC
variable was recategorised into two levels (Low and High) using
quantile-based intervals (the “cut2” function, Harrell, 2025).
This scientic publication in digital format is a continuation of the Printed Review: Legal Deposit pp 196802ZU42, ISSN 0378-7818.
Rev. Fac. Agron. (LUZ). 2026, 43(3): e264330 July-September ISSN 2477-9407.
4-7 |
Model Fitting: The nal model was tted using Firth’s Bias-
Reduced Logistic Regression (Firth, 1993). This is a penalised
maximum likelihood method that was employed to mitigate bias in
the logistic regression estimators, a recommended practice in the
presence of issues such as separation or scattered data.
RCI Modelling vs. Species Abundance
The relationship between the abundance of phytoplankton and
zooplankton species and the RCI was analysed using binary logistic
regression, which enabled the identication of species predictive of
the physiological status of the shrimp. Variable (species) selection
was carried out in three stages:
Starting from a saturated model, the step VIF function
(pedometrics package) was used to obtain an initial set of predictor
species with low collinearity (specically, GVIF < 4).
With the preselected species, the step AIC function (MASS
package, Venables and Ripley, 2002) was employed. This function
performs a stepwise (backward) variable selection based on the
Akaike Information Criterion (AIC), seeking the most parsimonious
model that optimises the trade-o between goodness of t and
complexity.
Finally, a deviance analysis was carried out using the chi-square
test to assess the signicance of the nal predictors. Only those
species that signicantly reduced the residual deviance were included
in the nal model.
The estimated coecients of the nal model were converted
into odds ratios (OR) with their respective condence intervals. The
discriminatory power of the logistic regression model was assessed
using Tjur’s R² (or discrimination coecient), a measure of the
model’s ability to distinguish between the two classes of the response
variable (Tjur, 2009). All statistical analyses were performed using
the statistical programming language R (R Core Team, 2024).
Results and discussion
Correlation between production variables and the RCI
The shrimp exhibited an average Relative Condition Index
(RCI) of 1.36 ± 0.92 during the study period, a value suggesting a
favourable physiological condition according to the ranges reported
for organisms in the fattening phase under semi-intensive systems,
where values close to or above 1 are typically associated with
individuals exhibiting adequate somatic performance and relative
growth (Prajapati and Ujjania, 2021). The RCI showed variability
between tanks (Figure 3).
Tank 2 had the highest average value (RCI = 1.81 ± 1.16),
followed by tanks 1 and 4 (1.54 ± 0.94 and 1.51 ± 1.01, respectively).
Pool 5 recorded an intermediate RCI (1.14 ± 0.63), whilst pool 3
had the lowest mean value (0.81 ± 0.45). Although no statistically
signicant dierences were detected between means (p > 0.05),
the observed variation suggests a dierential trend in the relative
condition of the organisms across experimental units. As the RCI
reects the relationship between weight and size, values below 1 may
indicate lower accumulation of relative body biomass or dierences
in individual growth under specic rearing conditions.
When evaluating production values spatially, it can be seen that
the lowest RCI was recorded in the third pond and, consequently,
the lowest yield.ha
-1
; however, contrary to expectations, the shrimp
in this pond showed the highest weight gain (Figure 4). The fourth
pond achieved the highest yield, followed by the fth pond. These
indices appeared to contradict the ndings regarding the RCI of
the ponds; however, this discrepancy can be explained by survival
patterns. Furthermore, the third pond recorded the highest survival
rate, which led to the lowest FRC, as was the case with the fth
pond. Conversely, the low yield was associated with the reduced RCI
observed previously.
Figure 3. Comparison of the Relative Condition Index (RCI) of
white shrimp across the ponds evaluated.
Figure 4. Comparison of the production indices recorded in the
evaluated grow-out ponds.
Dierences were observed in the behaviour of the production
variables between weeks of cultivation (Figure 5).
Figure 5. Temporal variation in production variables during the
weeks of cultivation.
Weight gain showed relatively consistent values throughout
the evaluation period, whilst survival rates varied between weeks,
reaching their highest percentages during weeks 2 and 5. The relative
This scientic publication in digital format is a continuation of the Printed Review: Legal Deposit pp 196802ZU42, ISSN 0378-7818.
Hernández et al. Rev. Fac. Agron. (LUZ). 2026, 43(3): e264330
5-7 |
Yield.ha
-1
remained stable throughout the study, except for
decreases observed in the seventh and tenth weeks, which coincided
with variations in stocking density and survival rates. These changes
were attributed to the carrying capacity of the ponds and the
progressive deterioration of water quality, disrupting the ecological
balance of the system. An increase in stocking density can induce
chronic stress in the shrimp due to overcrowding and environmental
deterioration, limiting the eciency and yield of the culture (Aguilar
et al., 2012).
The logistic regression model revealed a moderate negative
association (OR = 0.99) between harvest density and the probability
of obtaining a favourable RCI, whilst high FRC showed a signicant
positive association, increasing the probability of obtaining a good
RCI by 7.6 times (OR = 7.57). Overall, the model t was adequate (R²
= 0.5). Therefore, increased density was associated with RCI values
close to poor condition, and 70% of cases with good physiological
condition were associated with a high FRC (Figure 6).
Figure 6. A) Logistic regression curve for predicting RCI
categories based on harvest density. B) Relationship
between RCI and low and high FRC categories.
The model variables showed that higher FRC values were
associated with an increase in the RCI; this relationship can be
explained by the fact that feed eciency directly inuences biomass
accumulation and the relative body condition of the organisms, given
that greater utilisation of feed favours an increase in weight relative to
expected size (Le Cren, 1951). A high FRC indicates lower feed loss
and greater feed utilisation by the shrimp, as well as greater stability
in water quality, which results in an optimisation of the shrimp’s
physiological condition (Irani et al., 2022). However, in 7.7 % of
cases, an inverse relationship was observed: despite a high FRC, the
RCI was low. This discrepancy could be attributed to genetic factors
or other variables not taken into account.
These variables also have implications for harvest density, as shrimp
with a higher RCI have a larger body size and weight, and therefore a
higher biomass. The relationship between a population’s biomass and
the area it occupies is well studied in crustaceans; limited space causes
stress in the population, leading it to adapt and reduce its biomass
(Rodríguez-Olague et al., 2021). This explains the downward-sloping
sigmoid curve between the RCI and density, suggesting that there was
either excessive density or unfavourable environmental conditions.
Relationship between planktonic communities and the Relative
Condition Index (RCI)
To analyse the relationship between the abundance of phytoplankton
and zooplankton species and the Relative Condition Index (RCI),
a binary logistic regression was applied, given that the RCI has two
possible values: Poor (= 0) and Good (= 1), following a binomial
distribution. This approach enabled the identication of which species
inuenced the physiological condition of the shrimp, providing a clear
interpretation of the underlying ecological patterns.
The variable selection process for the phytoplankton community
included only the species Chlorella, as it showed a positive and
signicant relationship with high RCI values (OR = 1.08), indicating
that an increase in its abundance raises the probability of recording
individuals with higher relative condition by 8 %, albeit with weak
to moderate discriminatory power (R² Tjur = 0.251) (Figure 7).
Figure 7. Logistic regression curve of the RCI as a function of
Chlorella sp. abundance; the grey band represents the
95 % condence interval.
For zooplankton, Balanus nauplii were positively associated
with high RCI values (OR = 1.32), whilst Mesocyclops sp. showed a
signicant negative association (OR = 0.23), implying that an increase
in its abundance increases the probability of recording individuals
with low RCI values by up to 4.35 times. This zooplankton model
exhibited moderate discriminatory power (R² Tjur = 0.402), higher
than that observed in the phytoplankton model (Figure 8 A and B).
Figure 8. Logistic regression curves for the RCI as a function of the
abundance of Balanus nauplii (A) and Mesocyclops sp. (B).
reduction in survival observed at certain stages of the culture could
be associated with increases in eective density and intraspecic
competition, factors reported as limiting factors for production
performance in semi-intensive systems (Zhang et al., 2024).
Furthermore, an inverse relationship was observed between survival
and FCR, suggesting a possible alteration in feed eciency associated
with stocking density stress and competition for resources (Shirly-
Lim et al., 2024). Furthermore, the RCI and FRC showed variability
between weeks, which could reect changes in physiological
condition and feed utilisation by the organisms during the fattening
period.he seventh and tenth weeks, which coincided with variations
in stocking density and survival rates.
This scientic publication in digital format is a continuation of the Printed Review: Legal Deposit pp 196802ZU42, ISSN 0378-7818.
Rev. Fac. Agron. (LUZ). 2026, 43(3): e264330 July-September ISSN 2477-9407.
6-7 |
The positive relationship between the RCI of the shrimp and the
presence of Chlorella is consistent with the ndings of Eissa et al.
(2023), who demonstrated that the inclusion of C. vulgaris in the diet
improved the growth and health status of the shrimp, showing that
higher concentrations of this microalga resulted in better performance
and physiological condition of the farmed organism.
Meanwhile, Hudson (2024) evaluated zootechnical performance
and gene expression in P. vannamei fed diets supplemented with
Chlorella, demonstrating an improvement in survival and feed
conversion ratio, as well as an increase in nal productivity.
As regards the contribution of zooplankton groups, crustacean
nauplii such as those of Artemia, used in the larviculture of P.
vannamei, possess high nutritional value, making them an essential
component within aquaculture systems as they promote the survival
and growth of farmed species (Van Stappen et al., 2024). In this
regard, Balanus nauplii, in addition to being relatively larger than
Artemia nauplii, exhibit a nutritional prole comparable to that of
copepods, characterised by high levels of EPA, taurine and essential
minerals, suggesting potential nutritional value for juveniles in the
grow-out phase (Pedro et al., 2025).
On the other hand, the presence of cyclopoids of the genus
Mesocyclops was linked to an unfavourable RCI. This coincides
with their association with poor water quality; these organisms tend
to proliferate under eutrophic conditions, when the environment is
not optimal for shrimp farming (Jindal and Sharma, 2011). Research
conducted by Vidhya et al. (2014) showed that the quality of the
copepod diet inuences their viability as live feed; therefore, it can
be inferred that a decient diet in an eutrophic pond dominated by
cyanobacteria negatively aects the viability of copepods, impairing
their functional characteristics as high-quality live feed.
Conclusion
The results showed that planktonic and productivity variables
are related to the physiological status of Penaeus vannamei in semi-
intensive systems. The RCI and FRC exhibited weekly uctuations,
which may reect changes in physiological condition and feed
utilisation eciency during the grow-out period. From a production
perspective, the increase in harvest density limited the eciency and
yield of the culture. Furthermore, the planktonic community inuenced
the physiological status of the shrimp, with Chlorella sp. and Balanus
nauplii standing out for their positive association with high RCI
values, whilst Mesocyclops sp. showed a negative relationship. These
ndings suggest that the functional composition of plankton may
be more relevant than its total abundance, constituting an important
component as a natural food source and as an ecological indicator of
physiological performance in semi-intensive farming systems.
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