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The experiment was conducted at Agricultural and Bio-Systems Engineering Department, Faculty of Agriculture Moshtohor, Benha University, Egypt (latitude 30° 21′ N and 31° 13′ E), during the period of May to July, 2019 season under the university guidelines and legislation. Basil seedlings were sown in the plastic cups (7 cm diameter and 7 cm height) filled with peat moss. The cups were irrigated daily using water with nutrient solution (Ca(NO3)2, 236 g L−1, KNO3, 101 g L−1, K2SO4, 115 g L−1, KH2PO4, 136 g L−1, MgSO4 246 g L−1 and chelates for trace elements into preacidified groundwater (from the following ppm concentration are achieved in this formulation: N = 210, P = 31, K = 234, Ca = 200, Mg = 48, S = 64, Fe = 14, Mn = 0.5, Zn = 0.05, Cu = 0.02, B = 0.5, Mo = 0.01)). Two weeks old basil seedlings were planted at 9.0 plant m−2 in the experimental tanks. These seedlings were planted according to the permission of Benha university rules and legislation.Culture systems descriptionFigure 1a,b show the experimental setup. It shows the system which consists of hydroponic system, aeroponic system, soilless substrate, solution system and pumps.Figure 1(a) The experimental setup. (b) Images of system.Full size imageThe hydroponic system (Deep Water Culture (DWC)) consists of three rectangular polyethylene tanks that used for basil plants culture. Dimensions of each tank are 80 cm long, 40 cm wide and 30 cm high. The slope of hydroponic tanks was 2% and stand 1 m high above the ground. The hydroponic tanks were covered with foam boards to support the plants. Each hydroponic tank provided with an air blower (Model NS 780—Flow Rate 850 L h−1—Head 1.5 m—Power 15 W, China) to increase dissolved oxygen concentrations. The solution was circulated by a pump (Model First QB60—Flow Rate 30 L min−1—Head 25 m—Power 0.5 hp, China) from the solution tank to the upper ends of the hydroponic tanks. Small tubes (16 mm) were used to provide tanks with solution in a closed system.Aeroponic system consists of three rectangular polyethylene tanks that used for basil plants culture. Dimensions of each tank are 80 cm long, 40 cm wide and 50 cm high. The aeroponic tanks were established 1 m above the ground. Each aeroponic tank was divided into two parts, the lower part was made from polyethylene and the upper part was made from wood. The aeroponic tanks were covered with foam boards to support the plants. Each aeroponic tank was provided with two fog nozzles (Model M3MNWT5M – Orifice 2 mm – Discharge 8 L h−1, India) located at the bottom of the tank sprayed nutrient solution into the tank in order to keep the roots wet. Small tubes (16 mm) were used to provide aeroponic tank with solution in a closed system.Soilless substrates consist are placed in three rows are 2 m long. Each row consists standard peat moss slabs (1.00 m × 0.20 m × 0.075 m). Basil plants were placed on row peat moss slabs with a drip irrigation system. There were three plants per slab giving a mean density of 9.0 plant m−2. Each plant was fed by a single drip.The circular polyethylene tank of the nutrient solution system 500 L capacity was used for collecting the drained solution by gravity from the ends of the three systems. The nutrient solutions were prepared manually once per ten days17,18 by dissolving appropriate amounts of Ca(NO3)2, 236 g L−1, KNO3, 101 g L−1, K2SO4, 115 g L−1, KH2PO4, 136 g L−1, MgSO4 246 g L−1 and chelates for trace elements into preacidified groundwater (from the following ppm concentration are achieved in this formulation: N = 210, P = 31, K = 234, Ca = 200, Mg = 48, S = 64, Fe = 14, Mn = 0.5, Zn = 0.05, Cu = 0.02, B = 0.5, Mo = 0.01). pH and Electrical Conductivity (EC) were further adjusted to 6.5–7.0 and 1.4–1.8 dS m−1, respectively, after salt addition. The average air ambient temperature was 25.97 ± 4.37 °C and the average water temperature was 24.03 ± 3.92 °C. The average relative humidity was 65.4% and the light intensity was 338.55 ± 40.06 W m−2.MeasurementsThree plants sample were taken during the vegetative and flowering stages (four and seven weeks after transplanting, respectively) for growth measurement and chemical analysis. Plant height, root length and the fresh and dry weight of leaves, stems and roots were determined. After measuring fresh mass, the plants were oven dried at 65 °C until constant weight was reached19. Total content of macro elements was evaluated after being digested20. Nitrogen was determined by Kjeldahl digestion methods21. Potassium, Calcium and magnesium were determined by Photofatometer (Model Jenway PFP7—Range 0—160 mmol L−1, USA) and phosphorus (P) was determined colorimetrically method22. The content of oil was determined in different organs: leaves, stems and inflorescences according to23.Water samples were taken, at inlet and outlet of the culture units for measuring nitrogen (N), phosphorus (P), potassium (K), calcium (Ca) and magnesium (Mg) were measured every week at 10 am during the experimental period.Total production costThe cost calculation based on the following parameters was also performed:Fixed costs (Fc)Depreciation costs (Dc)$$D_{c} = frac{{P_{d} – S_{r} }}{{L_{d} }}$$
(1)

where Dc is the depreciation cost, EGP (Egyptian pound) year−1. ($ = 15.63 EGP). Pd is the system price, EGP. Sr is the salvage rate (0.1Pd) EGP. Ld is the system life, year.Interest costs (In):$$I_{n} = frac{{P_{d} + S_{r} }}{2} times {text{i}}_{{text{n}}}$$
(2)

where In is the interest, EGP year−1. in is the interest as compounded annually, decimal (12%). Shelter, taxes and insurance costs (Si).Shelter, taxes and insurance costs were assumed to be 3% of the purchase price of the automatic feeder (Pm).Then:$${text{Fixed,cost }} = {text{ D}}_{{text{c}}} + {text{ I}}_{{text{n}}} + 0.03{text{ P}}_{{text{m}}} /{text{ hour, of, use ,per ,year}}$$
(3)
Variable (operating) costs (Vc)Repair and maintenance costs (Rm):$${text{R}}_{{text{m}}} = 100% ;{text{deprecation,cost/hour,of,use,per,year}}$$
(4)
Energy costs (E):$${text{E }} = {text{ EC }} times {text{ EP}}$$
(5)

where E is the energy costs, EGP h−1. EC is the electrical energy consumption, kWh. EP is the energy price, 0.57 EGP kW−1.Labor costs (La):$${text{L}}_{{text{a}}} = {text{ Salary, of, one, worker }} times {text{ No}}{text{. ,of, workers}}$$
(6)

where La is the Labor costs, EGP h−1. Salary of one worker = 10 EGP h−1. No. of workers = 1.Then:$${text{Variable,costs }} = {text{ Rm }} + {text{ E }} + {text{ La}}$$
(7)
Total costs (Tc)$${text{Total ,costs }} = {text{ Fixed ,costs }} + {text{ Variable ,costs}}$$
(8)

Table 1 shows the input parameters of calculate total production costs of basil plants grown in different soilless systems.Table 1 The input parameters of calculate total production costs of basil plants grown in different soilless systems.Full size tableNutrients consumption rateThe Nutrients consumption rate were calculated as the differences between the nutrients at inlet and outlet of culture units by the following formula24:$$C_{{Nc}} = frac{{Nc_{{in}} – Nc_{{out}} }}{{{text{Number, of ,plants}}}} times Q times {text{24}}$$
(9)

where CNc is the nutrients consumption rate, mg day−1 plant −1. Ncin is the nutrients at inlet of the hydroponic unit, mg L−1. Ncout is the nutrients at outlet of the hydroponic unit, mg L−1. Q is the discharge, L h−1.Model development of nutrient consumptionModel assumptions:

N, P, K, Ca and Mg are the nutrients used in study.

The plants are uniformity distributed in the solution, so they work as a uniform sink for water and minerals with space at any time.

The root systems are uniformly dispersed in the solution with uniform root length density at any time.

The whole root system uptake characteristics are uniform.

Water losses by evaporation are negligible.

The simplest nutrient consumption models relate the nutrient consumption to the concentration gradient using some sort of proportionality factor such as root permeability or conductivity25,26. The nutrient consumption was determined by using the following equation:$$NC = a_{{NC}} cdot Delta {text{C }}$$
(10)

where NC is the nutrient consumption, mg plant−1 day−1. ∆C is the concentration gradient, mg plant−1 day−1. aNC is the proportionality factor, dimensionless.A similar model of nutrient consumption takes into consideration the differing effects caused by variations in root growth stage. Assuming that growth follows a first order differential equation and assuming that the root growth is exponential27, then Eq. (11) can be derived. This equation is presented in similar form to Eq. (10) and use the following equation:$$NC = left( {frac{{left( {C_{{plant}} – {text{C}}_{{{text{plant0}}}} } right)}}{{A_{r} – A_{{r0}} }}} right) cdot left( {frac{{{text{ln}}left( {frac{{{text{A}}_{{text{r}}} }}{{{text{A}}_{{{text{r0}}}} }}} right)}}{{{text{t}} – {text{t}}_{0} }}} right){text{.A}}_{{text{r}}}$$
(11)

where Cplanto is the concentration of the nutrients in the plant at time t0, mg plant−1. Ar is the root surface area at time t, cm2 plant−1. Ar0 is the root surface area at time t0, cm2 plant−1.Root surface area was calculated from root length and mean root radius using the following equation:$$A_{r} = {text{2}}pi {text{r}}_{{text{0}}} {text{L}}_{{text{r}}}$$
(12)
The root length increment using the following equation28:$$Delta L_{r} = Delta DW_{{root}} {text{v }}$$
(13)

where ∆Lr is the root length increment, cm day−1. ∆DWroot is the daily amount of root dry mass increment, g day−1. v is the ratio of root length and mass of roots, cm g−1.The daily amount of dry weight of roots is calculated from the following equation29:$$Delta DW_{{root}} = left{ {begin{array}{*{20}l} {{text{5LAI}}} hfill & {{text{for,LAI}} le {{0}}{{.5}}} hfill \ {{{2}}{{.5}} + {{23}}{{.9}}left( {{text{LAI-0}}{{.5}}} right)} hfill & {{text{for,LAI}} > {{0}}{{.5}}} hfill \ end{array} } right.$$
(14)

where LAI is the leaf area index.Leaf area index was changed in the same proportions as root length density to maintain a constant ratio between roots and shoots. The leaf area index is calculated from the following equation30:$$LAI = frac{{LAI_{{max }} }}{{1 + K_{2} e^{{left( { – k_{1} t} right)}} }}$$
(15)

where LAImax is the maximum leaf area index. K2 and k1 are the coefficients of the growth functions.All computational procedures of the model were carried out using Excel spreadsheet. The computer program was devoted to mass balance for predicting the nutrients consumption. The differences between the predicted and measured values were evaluated using RMSE indicator (root means square error) which is calculated using the following equation:$$RMSE = sqrt {frac{{sum {left( {Predicted-Measured} right)^{2} } }}{n}}$$
(16)
The parameters used in the model that were obtained from the literature are listed in Table 2. Figure 2 shows flow chart of the model.Table 2 The parameters used in the model.Full size tableFigure 2Flow chart of nutrients consumption rate.Full size imageStatistical analysisThree replicates of each treatment were allocated in a Randomize Complete Block Design (RCBD) in the system. Data were analyzed one-way ANOVA (analysis of variance) using statistical package for social sciences (spss v21). Means were separated using New Duncan Multiple Range Test (DMRT). Data presented are mean ± standard division (SD) of four replicates. More

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A single long day induces the photoperiodic molecular responseFigure 1c shows results from the experiment 1, as evidenced from the qPCR measurement of mRNA expression of genes of known biological functions in the blood and hypothalamus. Clearly, the exposure to extended light period induced a molecular response by hour 18 of the first long day, as shown by change in mRNA levels of candidate genes in both central (hypothalamus) peripheral (blood) tissues of photosensitive buntings. Blood mRNA levels of peroxiredoxin 4 (prdx4) were significantly lower at hour 18 mimicking a long 18 h photoperiod than those at hour 10 mimicking a short 10 h photoperiod (p = 0.002, t = 5.18, n = 4/time point). Paradoxically, this indicated a reduced cellular response against oxidative stress in the otherwise photo stimulated birds on the first long day. We speculate that prdx4 expression pattern would be inversed (i.e. increased prdx4 mRNA levels) after several long days when birds show photoperiodically stimulated hyperphagia (increased food intake) and lipogenesis (fat accumulation). Intriguingly, however, blood mRNA levels of gpx1 (p = 0.399, t = 0.91, n = 4/time point) and sod1 (p = 0.845, t = 0.20, n = 4/time point) genes were not different between hours 10 and 18 (Student’s t-test, Fig. 1c(a–c)). Taken together differences in the expression pattern of these enzymes, we speculate differential activation of the enzymatic pathways that are probably involved in the oxidative cellular response when migratory birds are exposed to an acute change in their photoperiodic environment.On the other hand, blood il1β mRNA levels were significantly higher at hour 18 than the hour 10 (p = 0.041, t = 2.58, n = 4/time point; Student’s t-test, Fig. 1c(d)). It is consistent with the known role of il1β-encoded interleukin 1β, as a crucial mediator of the inflammation and a marker of the innate immune system22,23. Increased il1β mRNA expression on the first long day is consistent with the idea of parallel photoperiodic induction of multiple biological processes, including those associated with the innate immune response, body fattening and gonadal maturation in migratory songbirds28; however, the possibility that an upregulated interleukin was an indicative a stress response cannot be excluded at this time.Changes in hypothalamic gene expressions further confirm a rapid molecular response to the extended light period when it surpasses the threshold photoperiod, i.e. acts as the stimulatory long day. Reciprocal switching of genes involved in the thyroid hormone responsive pathway at hour 18 particularly evidences this. Hypothalamic mRNA levels of tshβ (p = 0.033, t = 2.75, n = 4/time point) and dio2 (p = 0.0004, t = 7.14, n = 4/time point) genes were higher, and that of dio3 gene expression was lower at hour 18 than the hour 10 (p = 0.036, t = 2.68, n = 4/time point). This is also in agreement with the rapid photoperiodic response found on the first long day in plasma LH secretion, and in hypothalamic expressions of Fos-immunoreactivity and thyroid hormone responsive genes in blackheaded buntings14,33 and other photoperiodic birds15,17,19,32,34,35,36,37,38. However, gnrh mRNA levels were not found significantly different between hours 10 and 18 of the first long day (p = 0.324, t = 1.07, n = 4/time point; Student’s t-test, Fig. 1c(e–h) indicating that hour 18 was probably too early a time for an upregulated gnrh expression on the first long day37,38,39.RNA-Seq reveals differences in time course of the photoperiodic responseTable S2 summarizes the primary statistics used for RNA-Seq results. Using only transcripts with non-zero abundance, we compared the time course of transcriptome-wide response in the hypothalamus both as the function of time (within photosensitive or photorefractory state) and LHS (photosensitive vs. photorefractory state; n = 2/time point/state except at hour 22 in photorefractory state which had n = 1 sample size). Further, to show a functional linkage of differentially expressed genes (DEGs), we performed STRING analysis that predicts the protein–protein interaction (see methods for details).Results on hypothalamic gene expressions suggest that buntings react to the acute photoperiodic change in photorefractory state almost as they do in the photosensitive state. However, the comparison of the overall RNASeq data from both states revealed LHS-dependent pattern in the time course of transcriptional response, with differences in the number and functions of DEGs and associated physiological pathways.Within state differences in time course of transcriptional responseWe examined the time course of response on the first long day, by comparing gene expressions at the hours 14, 18 and 22 of the extended light period that mimicked 14 h, 18 h and 22 h long photoperiods, respectively, with those at hour 10 that mimicked a 10 h short photoperiod.Photosensitive stateAt hour 14, we found 10 differentially expressed genes (DEGs) with 4 upregulated and 6 downregulated genes (Figs. 2a, 3a, Table S3). Of the 10 DEGs, atp6v1e1, atp6v1b2, uqcrc1 and pgam1 genes enriched the oxidative phosphorylation, metabolic pathways, phagosome and mTOR signalling pathways (Table 1). The oxidative phosphorylation and metabolic pathways were upregulated at hour 10, while the phagosome and mTOR signalling pathways were enriched by two genes that were opposite in the expression trend: atp6v1e1 was upregulated while atp6v1b2 was downregulated at hour 14. The STRING analysis showed a significant interaction of atp6v1e1 and atp6v1b2 encoded proteins (ATP6V1E1 and ATP6V1B2). These proteins are the components of vacuolar ATPase enzyme that mediates the acidification of eukaryotic intracellular organelles necessary for protein sorting and zymogen activation. Further, at hour 14, ttr gene that codes for transthyretin (a preferential T3 binder) and pomc gene that codes for the proopiomelanocortin receptor had significantly lower expressions. Whereas, low ttr gene expression, as in photostimulated redheaded buntings40, might indicate a reduced trafficking of thyroid hormones via ttr-encoded transthyretins in the photosensitive state, the low pomc gene expression might suggest the removal of inhibitory effects of the opioids (e.g. β-endorphin, a pomc-encoded proopiomelanocortin product) on hypothalamic GnRH and, in turn, pituitary LH secretion41,42.Figure 2Top panel: Volcano plots showing results of differential gene expression analysis (− log10 padj. vs. log2 fold change values) in the hypothalamus within the photosensitive (a–c) and photorefractory states (e–g). The comparison protocol is shown on the left. In each state, the comparisons were done with respect to the hour 10 value (akin to short day control). Venn diagram shows common and unique DEGs in photosensitive (d) and photorefractory states (h). Bottom panel: Volcano plots showing results of differential gene expression analysis (− log10 padj. vs. log2 fold change values) between the photosensitive and photorefractory states. The pairwise comparisons were made at all the four time points (hours 10 (i), 14 (j), 18 (k) and 22 (l)). Venn diagram shows common and unique DEGs between states at hours 10, 14, 18 and 22 (m). Genes in a volcano plot with log2 fold change  > 2 are marked by green colour, and those with log2 fold change  > 2 and p value (padj.)  More