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Forage yield and quality of marandugrass fertigated with treated sewage wastewater and mineral fertilizer/Rendimento e qualidade de forragem de capim-marandu fertirrigado com agua residuaria de esgoto tratado e adubo mineral.

Introduction

Applying treated sewage effluent to crops is a common practice that dates back to before the BC period, starting from Germany and England within the sixteenth and seventeenth centuries (Veloso, Duarte, & Silva, 2004). These countries have had a primary goal of preventing pollution in waterways instead of raising agricultural yield.

Nations such as China and Mexico are pioneers in the use of wastewater in agriculture. In Brazil, wastewater usage is performed spontaneously and in an uncontrolled way, mainly due to the lack of wastewater treatment plants in most cities. However, it is expected that controlled applications will increase in the coming years because of economic development as well as environmental and public health pressures.

The major limitation of TSW usage in farming systems is trace elements, often present in irregular effluent. TSW pathogens such as streptococcus, Salmonella sp., Shigella sp., larvae, protozoa (cysts) and viruses (enteroviruses and rotaviruses) cannot withstand soil environment conditions for more than a few hours, except for helminth eggs.

Forage plants have been sorted for cultivation under TSW application because of their long growth cycle associated with high annual water consumption, nutrient absorption and the ability to prevent soil erosion (Fonseca, Herpin, Paula, Victoria, & Melfi, 2007a; Oliveira Filho et al., 2011). Moreover, grasses belonging to the Brachiaria genus meet the tolerance requirements of high soil moisture, salinity, organic matter content and possible toxic effects of TSW.

Grass growth in the tropics is often restrained by soil nitrogen deficiency (Vitor et al., 2009; Serafim & Galbiatti, 2012). Low forage yields are caused by a lack of scientific expertise as reflected in herd characteristics, animal weight fluctuations (i.e., within animal breeding, raising or finishing, low milk or meat yields), and consequently a lower market value. Furthermore, nitrogen is the most limiting factor in biomass production after water (Nogueira et al., 2013).

TSW is rich in macro and micronutrients essential for the growth of most crops, making its use convenient in farming (Bertoncini, 2008; Oliveira Filho et al., 2011; Silva, Matos, Borges, & Previero, 2012; Nogueira et al., 2013; Pinto, Cruz, Frigo, Frigo, & Hermes, 2013). Additionally, it also provides an increase in irrigated areas, even in those under jeopardized water use conditions (river basins under critical conditions).

The management of pastures with wastewater has been providing higher forage nutritional quality (Alencar et al., 2009, Teixeira et al., 2011; Serafim & Galbiatti, 2012; Matos, Silva, Lo Monaco, & Pereira, 2013; Nogueira et al., 2013). In addition to enhanced yield (Drumond, Zanin, Aguiar, Rodrigues, & Fernandes, 2006; Fonseca et al., 2007b; Silva et al., 2012), it is also good for supplying water and nutrient demands in a sustainable way and avoiding direct TSW discharge into water bodies (Bertoncini, 2008).

Leaf protein synthesis is assigned to water availability and soil fertility, mostly nitrogen, which reflects in higher digestible protein (CP) and reduces levels of less digestible fibre (NDF) for forages (Freitas et al., 2007; Geron et al., 2014), producing a forage of better quality for animal consumption.

Studying urban development, water resource management and the use of wastewater for irrigation in India, Van Rooijen, Biggs, Smout, and Drechsel (2010) concluded that wastewater use in agricultural lands is a contribution to food security and public health, in addition to improving the quality of water downstream of cities as well as reducing the demand for underground water in agriculture.

Reduced production costs associated with decreasing the use of mineral fertilizer may justify the economic feasibility of wastewater use in agriculture (Alencar et al., 2010; Nogueira et al., 2013). Additionally, fertigated areas should be connected to sewage treatment plants, thereby minimizing transportation costs.

Increased yields and forage quality are expected when using nitrogen fertigation with TSW in Brachiaria brizantha cultivation, coupled with reducing input costs and underground water use in agricultural lands. Investigations under these conditions would provide guidelines for wastewater use in Brazilian agriculture. Based on this research, we aimed to evaluate the response (forage yield and quality) of Brachiaria brizantha cv. Marandu to fertigation with various treated sewage wastewater rates and mineral fertilizer during the years of 2013 and 2014 in Jaboticabal, Sao Paulo State, Brazil.

Material and methods

The experiment was carried out in 2013 and 2014 at the College of Agricultural and Veterinarian Sciences at the Sao Paulo State University (FCAV-UNESP), in Jaboticabal, Sao Paulo State, Brazil (21[degrees]14'41,9" S and 48[degrees]16'25.2" W).

The soil is classified as Eutrophic Red Latosol--Lve (Red Oxisol), with a clayey texture (> 50%), high iron content, gentle landforms and high fertility (Table 1).

In this study, we used treated sewage wastewater from a sewage treatment plant (STP) near the experimental area. Treatments performed in this STP consist of a mixed system (aerobic and anaerobic) composed of an up-flow anaerobic digester and facultative lagoons. This plant collects sewage from Jaboticabal, with an average flow of 202 L [hab.sup.-1]. The city has approximately 71,662 inhabitants, in an area of 707 [km.sup.2] and a population density of 101.4 inhabits [km.sup.-2].

The experiment was performed over a floor area of 345.6 [m.sup.2], consisting of 24 plots (2.4 m wide and 6.0 m long) of 14.4 [m.sup.2]. Homogeneous distribution of water depth and gradual application of TSW were carried out by a triple-line sprinkling system (Lauer, 1983) at 30 m.c.a working pressure (0.042 ksi). Uniformity coefficients of Christiansen (CUC) and distribution (DU) were 88.8% and 83.5%, respectively; thus, it was possible to define six treatments with four replications by applying the following TSW water ratios: E5 = 1.0; E4 = 0.87; E3 = 0.6; E2 = 0.31; E1 = 0.11, and E0 = 0.0 and distribution model of TSW (Y = 0.0015 [X.sup.3] 0.029 [X.sup.2] + 0.057 X + 0.99; [R.sup.2] = 0.98; Figure 1).

TSW monthly samples were collected to analyse nitrogen concentration, and at the end of each season, complete analyses of nutrients were made using TSW samples.

Prior to the experiment, Brachiaria brizantha cv. Marandu seeds were sown into 0.2 m rows and at a rate of 10 kg [ha.sup.-1]. During this operation, fifty kilograms of superphosphate were applied per hectare.

Fertigation control was in accordance with plant nutritional demand, according Dantas et al. (2016), and consisted of 15 kg [ha.sup.-1] nitrogen (N), 3.5 kg [ha.sup.-1] phosphorus (P) and 18 kg [ha.sup.-1] potassium (K) per dry biomass megagram (Mg). However, water demand followed the FAO 56 method in the reference treatment (E3), which was considered the criterion of greatest value within a 28-day interval. In the E0 treatment, a mineral fertilizer (NPK) equivalent to nutrient demand in the reference treatment (E3) was applied. Higher rates in E3 in the same season were utilized to supply crop water requirements. The application of TSW in the experimental area considered the criteria established by the Technical Standard P4.230 (CETESB, 1999).

Dry biomass yield was assessed by harvesting grass. Grass was cut at 0.15 m height, except for the three first harvests when it was at 0.2 m, every 28 days (from Feb. 5, 2013 to Jan. 6, 2014). Eight summer harvests, 10 fallwinter harvests and 8 spring harvests were performed. The adopted management enabled 13 cut cycles and 2 harvests per year, which were done in a single month, one at the beginning and the other at the end.

Cuttings were aided by 0.25 [m.sup.2] templates randomly thrown three times (replications) over each plot and four times per treatment. Replications were homogenized and one sample was withdrawn for weighing. Then, the selected sample was dried in a forced circulation air oven at 65[degrees]C up to constant weight for dry biomass determination (Lacerda, Freitas, & Silva, 2009). Before being collected, plant height was measured using acetate sheets thrown randomly onto the lawn in six replications per plot.

Nitrogen yield was calculated by the ratio between dry biomass production and the amount of nitrogen applied.

A forage qualitative study analysing crude protein (CP) and neutral detergent fibre (NDF) was conducted in a quarterly basis per respective season using a methodology proposed by Silva and Queiroz (2006).

Forage yield data were analysed per season according to Johnson, Chaudhuri, and Kanemasu (1983), using the GLM procedure of SAS software, and the averages were compared by Tukey's test at 1% and 5% probability. Response functions were adjusted between dry biomass yield and qualitative characteristics according to the amount of nitrogen applied via TSW.

Results and discussion

TSW analyses confirmed high annual average concentrations of essential nutrients for Brachiaria growth, such as total nitrogen (52.9 [+ or -] 7.0 mg [L.sup.-1]). Concentrations of potassium (20.3 [+ or -] 7.2 mg [L.sup.-1]) and phosphorus (1.1 [+ or -] 0.4 mg [L.sup.-1]) were, respectively, ideal and low for forage fertigation purposes (Table 2). Although TSW salinity was low (< 0.46 dS [m.sup.-1]) by electrical conductivity evaluation, low sodium concentrations were observed (58.8 [+ or -] 8.7 mg [L.sup.-1]) but in a low adsorption ratio (SAR = 3.3 [+ or -] 0.6), which is above the critical level. In addition, there was also a high total coliform count and the presence of Escherichia coli in the effluent.

Other nutrients were applied in the following amounts in E5: P = 27, K = 314, Ca = 258, Mg = 92, Na = 894, SO = 369, Fe = 6, Mn = 1, and Zn = 11, in 2013, and P = 21, K = 463, Ca = 358, Mg = 108, Na = 1,428, SO = 421, Fe = 17, Mn = 2, and Zn = 3, in 2014, in kg [ha.sup.-1]. The remaining treatments were given quantities proportional to application ratios as defined for each treatment.

Mineral fertilizers (E0) were applied in summer, fall" winter and spring at the rates of 189, 85, and 182 kg [ha.sup.-1] N in 2013, and 200, 157, and 292 kg [ha.sup.-1] N in 2014. Superior nitrogen levels in E3 were applied in the same seasons to fulfil the crop water requirements.

Irrigation water depths for summer, fall-winter and spring were, respectively, 678, 500, and 675 mm in 2013, and 750, 661, and 842 mm in 2014. The total depth of irrigation and precipitation is shown in Table 3.

Mineral P and K fertilizers at the respective rates of 96 and 554 kg [ha.sup.-1] (2013) and 136 and 696 kg [ha.sup.-1] (2014) supplemented all treatments. Fertilizations were scheduled as needed for each cutting cycle of the crop (28 days).

Thus, an amount of 931 and 1,132 kg [ha.sup.-1] nitrogen was applied to the E5 treatment (Table 4). Moreover, a greater nitrogen increment in the second year stemmed from the higher dry biomass yield.

Rising temperatures, reduced rainfall, and consequently, greater water demand in 2014 led to higher forage yields. During 2013 and 2014, the average temperatures were 22.2, and 23.3[degrees]C, respectively, with maximum values of 34.1, and 36.5[degrees]C and minimum values reaching 8.2, and 11.9[degrees]C; however, annual average rainfall was 1,393 mm, and 721 mm with an evapotranspiration of 1,398 mm, and 1,616 mm.

Wastewater application increased the organic matter content, calcium, base saturation and cation exchange capacity (Table 5). Additionally, reductions of phosphorus, potassium and magnesium contents were observed, where plants absorbed some of the minerals and the remainder leached into the soil. Soil B concentration remained at an average content over time. During the evaluation period, the soil retained a low Al content, a medium to high content of Zn and Fe, and high amounts of Cu, Mn, and S-S[O.sub.4].

Seasonal effects marked forage production, with high values present from October to April and low ones between May and September (Tables 6). High yields were reported in summer (44.7%) and spring (35.7%) of 2013, due to climatic factors that increased plant metabolic activities and, thus, promoted forage growth. In contrast, the low yield in autumn-winter (19.6%) was due to sub-optimal conditions for crop growth.

In 2014, high values of average yields were obtained in spring (38.4%), followed by summer (35.9%) and fall-winter (25.7%) (Table 6). Cumulative results per season showed that in 2013, the highest average of forage performance occurred in summer (17.7 Mg [ha.sup.-1]), followed by spring (14.1 Mg [ha.sup.-1]) and fall-winter (7.8 Mg [ha.sup.-1]) (Table 7).

Rainfall reduction (672 mm) and an increase in temperature (1.1[degrees]C) and solar radiation (312.5 MJ [m.sup.-2] [year.sup.-1]), mainly from March to November of 2014, resulted in improved dry biomass yield, with a sharper production gradient in 2013. Furthermore, in 2014, there was an increase in biomass production from 25.7 Mg [ha.sup.-1] (E1) to 56.9 Mg [ha.sup.-1] (E5), corresponding to an increase of 121%. These results agree with Fonseca et al. (2007b) and Matos et al. (2013).

A variance analysis of summer forage yield revealed that the factors cultivation year, TSW rate and TSW x year interaction were significant (Table 8). The coefficient of variation was 9.6%, which shows high experimental accuracy.

The average comparisons showed a higher forage yield in 2014 compared to 2013. Statistical breakdown of the TSW x year interaction showed similar yield averages in the summer of 2013.

Initial fertilization standardized forage production at the beginning of the experiment. In the summer of 2014, the highest average yields were observed for E5, E4, and E0; however, E3, E2, and E1 had the lowest averages, but the E4 and E3 averages did not differ significantly.

During the fall-winter season, we observed significant results for the year and TSW rates; however, there was no interaction between them (Table 9). The coefficient of variation was 13.5%. Moreover, biomass yield in 2014 surpassed the findings for 2013.

When comparing TSW rates, we noticed higher yields for E5, E4, and E0, with no significant differences between E3 and E0. In addition, relatively low rates of nitrogen (E1) reduced biomass yield by up to 84.2% compared with the maximum rates (E5). During this season, biomass yield did not reach the minimal level for cattle grazing, which is 1,200 kg [ha.sup.-1] (Silva et al., 2012), within the 28-day intervals. This yield drop is associated with low temperatures, humidity and light, which are limiting factors for grass development, unlike what is observed in summer and spring. The growth of C4 grasses is highly demanding of temperature and luminosity (Matos et al., 2013). Maranhao et al. (2010) proved this fact in a study of nitrogen levels on Brachiaria, observing a 78.9% reduction in dry biomass from summer to winter. Similar results were obtained by Alencar et al. (2009) and Oliveira Filho et al. (2011).

As for spring data, we observed significant effects of year, TSW rates and their interaction, with a variation coefficient of 10.3% (Table 10). In 2014, biomass yield was higher than in 2013 (41%). Furthermore, in 2014, peaks of higher and lower biomass yield for E5 (24 Mg [ha.sup.-1]) and E1 (7 Mg [ha.sup.-1]) were recorded, respectively. It is worth mentioning that in warmer periods with high solar radiation, as in 2014, increased yields occurred.

The average rates of dry biomass growth in 2013 were 158, 56, and 126 kg h[a.sup.-1] da[y.sup.-1] in the summer, fall-winter and spring, respectively. The highest rates were observed in E0 (171 kg [ha.sup.-1] [day.sup.-1]) and E5 (170 kg [ha.sup.-1] [day.sup.-1]) during the summer, and the lowest rate was observed for E1 (38 kg [ha.sup.-1] [day.sup.-1]) in the winter. Similar results were obtained by Dupas et al. (2010), Matos et al. (2013) and Dantas et al. (2016).

In 2014, the lowest average rates of biomass growth occurred in treatments with lower inputs of TSW (E1 and E2), corresponding to 136, 78, and 146 kg [ha.sup.-1] [day.sup.-1] in the summer, fall-winter and spring, respectively. On the other hand, the largest rates were observed for E5 and E4 with 214 and 197 kg [ha.sup.-1] [day.sup.-1], respectively, during the spring; and the lowest rate was observed in E1 (55 kg [ha.sup.-1] [day.sup.-1]) in the winter. These results agree with those of Andrade et al. (2012).

The dry biomass yield increased according to the nitrogen applied to the soil via TSW in all assessed seasons for the years of 2013 and 2014. Despite the high levels of nitrogen applied via TSW, in 2013 (931 kg [ha.sup.-1]; Y = 0.016 [X.sup.2] + 2.53 X + 31,071; [R.sup.2] = 0.99) and 2014 (1,132 kg [ha.sup.-1]; Y = 0.014 [X.sup.2] + 12.53 + 24,628; [R.sup.2] = 0.99), forage yield peaks were not reached. Equivalent rates of organic and mineral nitrogen resulted in yields greater than or equal to E0 compared to E3. Similar results were obtained by Drumond et al. (2006), Silva et al. (2012), Nogueira et al. (2013) and Dantas et al. (2016).

Nitrogen yield for treatments receiving TSW were 173.8, 77.9 and 102.5 kg of biomass per kg of N in the summer (Y = 0.0098 [X.sup.2] - 4.64 X + 585.5; [R.sup.2] = 0.95), fall-winter (Y = 0.0053 [X.sup.2] - 2.09 X + 231.49; [R.sup.2] = 0.93) and spring (Y = 0.0038 [X.sup.2] - 2.05 X + 312.81; [R.sup.2] = 0,95) and 117 (Y = 0.0046 [X.sup.2] - 2.46 X + 361.7; [R.sup.2] = 0.96), 79 (Y = 0.0014 [X.sup.2] - 0.87 X + 182.65; [R.sup.2] = 0.93) and 81.3 kg of biomass per kg of N (Y = 0.0027 [X.sup.2] 1.51 X + 236.7; [R.sup.2] = 0.95), in 2014, respectively. Regardless of the higher yield in 2014, the lowest nitrogen efficiency is related to the increase in TSW rates. Serafim and Galbiatti (2010) argued that lower rates had better nitrogen performance, thus confirming the results of our research. For Fonseca et al. (2007b), low water tension in soil derived from regular irrigation favours nitrogen performance and, as a consequence, enhances forage yield.

An improved leaf quality, in terms of CP (> 12%) and NDF (< 60%), was provided when forage had low yield. Therefore, in the fall-winter, low yields associated with a smaller leaf area and larger leaf-stem ratio resulted in higher CP content and lower NDF in both years (Tables 11 and 12). Furthermore, we observed a gradual increase in herbage quality in 2014, which occurred due to the increased TSW rates applied. Similar results were obtained by Dantas et al. (2016).

Foliar analysis showed that the reference treatment (E3) had an ideal CP content, albeit below average, for every season except fall-winter. This high content, shown in 2013, could be attributed to higher leaf production against stems since leaves carry the most nutrients, as shown in some previous reports. These results agree with those of Matos et al. (2013), Silva and Queiroz (2006), Castro et al. (2007), Serafim and Galbiatti (2012), Geron et al. (2014) and Dupas et al. (2010).

Forage fertigation with TSW has the potential to supply nitrogen and potassium to crops; however, this also causes phosphorus limitation and an average potential for soil salinization because of large concentrations of sodium and coliforms within this effluent. However, it has promoted high levels of good quality forage production, favourable for cattle feeding, weight gain per animal, reducing the use of underground water and mineral fertilizers, in addition to social and environmental benefits.

Using wastewater in agriculture enables irrigated areas to be extended and reduces the amount of sewage disposed of in receiving water bodies. It denotes an alternative to control pollution of water sources, lowering underground water and fertilizer demands, in addition to a sustainable agricultural management tool.

Conclusion

Brachiaria brizantha had positive responses to TSW application, increasing annual dry biomass production from 31.3 to 47.4 Mg [ha.sup.-1] in 2013 and from 25.7 to 56.9 Mg [ha.sup.-1] in 2014, between E1 and E5, respectively.

There was a marked seasonality in forage performance; the highest yields occurred in the summer (35.9 to 44.7%) and spring (35.7 to 38.4%), and the lowest yields (19.6 to 25.7%) with improved forage quality were observed in the fall-winter.

The constant use of TSW combined with growing levels resulted in forage production with an enhanced nutritional quality concerning crude protein and neutral detergent fibre.

Doi: 10.4025/actasciagron.v39i4.32828

Acknowledgements

This work was supported by the Foundation of the Sao Paulo State (FAPESP) [grant numbers 2012/12.923-3 e 2013/00362-0].

The authors thank the Self-governing Water and Sewage Service of the city of Jaboticabal (SAAEJ) for wastewater supplies and Prof. Gener Tadeu Pereira from Sao Paulo State University in Jaboticabal (FCAV-UNESP) for helping with statistical analysis.

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Received on July 21, 2016.

Accepted on December 2, 2016.

Gilmar Oliveira Santos (1) *, Rogerio Teixeira de Faria (2), Gilberto Aparecido Rodrigues (3), Geffson de Figueredo Dantas (2), Alexandre Barcellos Dalri (2) and Luiz Fabiano Palaretti (2)

(1) Universidade de Rio Verde, Fazenda Fontes do Saber, Cx. Postal 104, 75901-970, Rio Verde, Goias, Brazil. (2) Universidade de Sao Paulo, Jaboticabal, Sao Paulo, Brazil. (3) Taquaritinga Technology College, Taquaritinga, Sao Paulo, Brazil. * Author for correspondence. E-mail: gilmar@unirv.edu.br

Caption: Figure 1. Experimental diagram showing the lines of gradual distribution of TSW in water (left) and the distribution ratio of rainfall on the distance of irrigation lines (right).
Table 1. Soil chemical characteristics of samples collected from the
experimental area within a depth of 0 to 1.0 m, in November of 2012,
Jaboticabal, Sao Paulo State, Brazil.

pH         OM         K   Ca   Mg   H+Al   BS   CEC   Al

      g [dm.sup.-3]            mmol [dm.sup.-3]

5.5        20         4   25   12   27     40   68    0

pH    P    B     Cu    Fe   Mn   Zn   S    V

                       mg [dm.sup.-3]      %

5.5   53   0.3   3.4   12   18   2    24   57

Table 2. Chemical, physical and microbiological characteristics of
treated sewage wastewater (TSW) from a sewage treatment plant (STP)
in Jaboticabal, Sao Paulo State, Brazil, in the summer,
fall-winter and spring seasons of 2013 and 2014.

Factors        Unit of measure     Summer   Fall-Winter   Spring

pH                   --             6.7         7.2        7.1
EC              dS [m.sup.-1]       0.44       0.49        0.42
TOC             mg [L.sup.-1]       56.1       48.0        45.0
N[O.sub.3]      mg [L.sup.-1]       2.1         5.8        4.5
N[O.sub.2]      mg [L.sup.-1]       1.0        0.04        0.04
N[H.sub.3]      mg [L.sup.-1]       31.4       35.7        31.6
Total N         mg [L.sup.-1]       44.3       57.8        51.7
Total Fe        mg [L.sup.-1]       0.28       0.62        0.60
K               mg [L.sup.-1]       25.3       19.1        17.2
P               mg [L.sup.-1]       1.3         1.0        1.0
Ca              mg [L.sup.-1]       9.3        15.9        21.2
Mg              mg [L.sup.-1]       7.5         4.9        7.0
Zn              mg [L.sup.-1]       0.1         0.5        0.2
Na              mg [L.sup.-1]       60.3       54.1        64.3
SAR                  --             3.7         2.9        3.2
TCC          MPN [100.sup.-1] ml   9,450      102,666     16,350
EC           MPN [100.sup.-1] ml    495        6,370      11,650

Factors             Average           Acceptable level

pH              7.0 [+ or -] 0.3          5-9 (a)
EC             0.46 [+ or -] 0.01          <3 (b)
TOC            49.4 [+ or -] 19.1            --
N[O.sub.3]      4.5 [+ or -] 2.4          <10 (c)
N[O.sub.2]     0.25 [+ or -] 0.8         <0.02 (c)
N[H.sub.3]     33.3 [+ or -] 15.8         1-40 (c)
Total N        52.9 [+ or -] 7.0             --
Total Fe       0.53 [+ or -] 0.3           <5 (b)
K              20.3 [+ or -] 7.2         10-40 (c)
P               1.1 [+ or -] 0.4           <2 (b)
Ca             15.5 [+ or -] 6.4         20-120 (c)
Mg              6.2 [+ or -] 2.6         10-50 (c)
Zn             0.27 [+ or -] 0.32          <5 (a)
Na             58.8 [+ or -] 8.7         50-250 (c)
SAR             3.3 [+ or -] 0.6        4.5-7.5 (c)
TCC          51,371 [+ or -] 62,795     <10,000 (c)
EC            6,200 [+ or -] 8,267       <1,000 (c)

Obs.: pH: Hydrogen ionic potential; EC: Electrical conductivity; TOC:
Total organic carbon; N[O.sub.3]: Nitrate; N[O.sub.2]: Nitrite;
N[H.sub.3]: Ammonium; Total N: Total nitrogen; Total Fe: Total iron;
K: Potassium; P: Phosphorus; Ca: Calcium; Mg: Magnesium; Mn:
Manganese; Zn: Zinc; Na: Sodium; SAR: Sodium absorption rate; TCC:
Total coliform count; EC: Escherichia coli. MPN: Most probable
number. Source: (a) Brasil (2011); (b) Ayers and Westcot (1976); (c)
Feigin, Ravina, and Shalhevet (1991).

Table 3. Total water depth (water and effluent) and precipitation
applied in the experiment in the summer, fall-winter and spring
seasons of 2013 and 2014.

Year     Season      Precipitation   Irrigation   Irrigation depth
                                        (mm)

2013     Summer           748           678            1,426
       Fall-winter        221           500             721
         Spring           424           675            1,089
          Total          1,393         1,853           3,246
2014     Summer           348           750            1,098
       Fall-winter        102           661             763
         Spring           271           842            1,113
          Total           720          2,252           2,974

Table 4. Nitrogen fertilization through TSW (kg [ha.sup.-1]) in the
summer, fall-winter and spring seasons of 2013 and 2014.

Year   Season         E5     E4    E3    E2    E1

       Summer         307    270   186   95    34
2013   Fall-winter    258    227   156   80    28
       Spring         365    321   221   112   40
       Total          931    817   564   287   102
       Summer         346    304   210   107   38
2014   Fall-winter    366    321   222   113   40
       Spring         420    369   255   130   46
       Total         1,132   994   687   350   124

Table 5. Average chemical characteristics of the soil in the
experimental area at 0-1.0 m depths in September of 2014,
Jaboticabal, Sao Paulo State, Brazil.

Treatment   ph    OM     P resin   K     Ca     Mg

                         g [dm.sup.-3]   mg [dm.sup.-3]

E5          5.7   21.0   41.5      3.7   31.7   13.7
E4          5.7   18.5   31.5      3.2   30.0   13.7
E3          5.6   21.0   43.8      3.8   32.2   14.2
E2          5.6   18.5   29.8      3.3   26.5   12.3
E1          5.5   17.3   26.5      3.5   22.8   10.7
E0          5.5   20.7   34.2      3.4   27.7   12.3

Treatment   H+Al   BS     CEC    V

                mmol [dm.sup.-3] %

E5          24.0   49.1   73.1   65.5
E4          22.3   46.9   69.2   65.7
E3          23.7   50.1   73.8   66.0
E2          23.5   42.1   65.6   61.5
E1          24.3   37.0   61.3   57.7
E0          26.0   43.4   69.4   60.0

Treatment   B     Cu    Fe     Mn     Zn    S-S[O.sub.4]   Al

                        mg [dm.sup.-3]      mmol [dm.sup.-3]

E5          0.3   3.7   13.2   17.7   1.7       42.0       0.0
E4          0.3   3.3   11.8   12.7   1.4       42.0       0.0
E3          0.3   3.5   14.7   9.9    1.7       39.8       0.0
E2          0.3   3.1   14.2   9.5    1.4       32.7       0.0
E1          0.2   2.8   13.2   8.5    1.0       31.5       0.0
E0          0.2   3.3   15.2   15.2   1.5       25.3       0.0

Table 6. Dry biomass yield during cutting cycles in 2013.

Month       Date       Cycle   (Ms [ha.sup.-1])

                                 E5       E4

February    02/05/13   1st     6,826    6,224
March       03/05/13   2nd     2,774    2,998
April       04/03/13   3rd     5,131    4,166
May         05/01/13   4th     1,397    1,639
May         05/28/13   5th     2,036    1,959
June        06/25/13   6th     2,444    2,530
July        07/23/13   7th     2,211    1,899
August      08/20/13   8th     1,526    1,440
September   09/17/13   9th     1,529    1,287
October     10/15/13   10th    5,376    4,356
November    11/12/13   11th    6,358    5,665
December    12/10/13   12th    5,512    6,001
January     01/07/14   13th    4,265    5,025
Total                          47,385   45,189

Month                (Ms [ha.sup.-1])

              E3       E2       E1       E0

February    6,543    6,272    5,996    6,028
March       2,650    2,397    2,841    3,242
April       3,783    3,485    2,700    4,874
May         1,495    1,390    1,405    1,957
May         1,376     968      880     1,657
June        1,834    1,184    1,058    1,941
July        1,688    1,430    1,104    2,071
August      1,120     896      920     1,201
September    914      716      761     1,130
October     2,823    2,080    1,936    3,167
November    3,898    3,778    3,303    5,270
December    4,470    4,939    4,032    5,417
January     4,266    4,305    4,323    4,963
Total       36,862   33,840   31,260   42,918

Table 7. Dry biomass yield per treatment over the cutting cycles
in 2014.

Month       Date       Cycle   (Mg [ha.sup.-1])

                                 E5       E4

February    02/04/14   14th    4,332    3,285
March       03/04/14   15th    5,074    4,761
April       04/01/14   16th    3,611    4,077
April       04/29/14   17th    4,985    4,541
May         05/27/14   18th    2,816    2,768
June        06/24/14   19th    1,958    1,803
July        07/22/14   20th    2,397    1,955
August      08/19/14   21st    2,278    1,512

September   09/16/14   22nd    3,183    2,806
October     10/14/14   23rd    6,834    5,687
November    11/11/14   24th    7,127    6,462
December    12/09/14   25th    6,813    7,152
January     01/06/15   26th    5,497    4,444
Total                          56,907   51,253

Month                (Mg [ha.sup.-1])

              E3       E2       E1       E0

February    3,169    3,369    3,026    4,610
March       2,973    3,707    3,125    3,837
April       3,247    2,732    2,850    4,293
April       4,232    4,054    3,842    3,908
May         2,037    1,717    1,686    2,590
June        1,649    1,241    852,0    1,896
July        1,251    797,0    626,0    1,915
August      1,287    993      682      1,536
September   1,431    1,004    717      2,203
October     3,563    2,363    1,455    3,833
November    4,789    3,055    2,106    7,030
December    5,132    3,657    2,793    6,910
January     3,902    3,503    1,974    6,237
Total       38,662   32,191   25,736   50,797

Table 8. Variance analysis summary (ANOVA) and comparison of biomass
yield averages of Brachiaria brizantha fertigated with treated
sewage wastewater (TSW) in the summer of 2013 and 2014.

Variation source   DF     Mean square      Pr (>F)

Block (B)          3    2,132,262.5 (ns)   0.4801
Year (Y)           1     69,547,860.1 *    <0.0001
Interaction BXY    3    5,984,640.0 (ns)   0.0901
TSW                5    41,835,894.5 **    <0.0001
Interaction        5     7,312,756.4 *     0.0299
TSWxY
V.C. (%)                                     9.6

Year     Average yield of dry
       biomass (Mg [ha.sup.-1])

2013            17.7 a
2014            15.3 b

Treatment     2013 (Mg       2014 (Mg       Average
            [ha.sup.-1])   [ha.sup.-1])   [ha.sup.-1])

E5             19.0 a         18.5 a          18.9
E4             18.4 a        16.6 ab          17.5
E3             17.2 a        13.3 bc          15.3
E2             16.5 a        13.3 bc          14.9
E1             15.8 a         10.9 c          13.4
E0             19.1 a         19.0 a          19.0
Average         17.7           15.3            --

DF--degree of freedom; Significant at 0.05 * and at 0.01 ** of
probability; (ns) nonsignificant; V.C.--variation coefficient;
Averages followed by the same letter in the upper right do not
differ by Tukey's test (p < 0.05).

Table 9. Variance analysis summary (ANOVA) and comparison of
biomass

yield averages of Brachiaria brizantha fertigated with treated
sewage
 wastewater (TSW) during the fall-winter of 2013 and 2014.

Variation source           DF           Mean square         Pr (>F)

Block (B)                  3           6,222,510.2ns         0.018

Year (Y)                   1          122,212,110.0 **      <0.0001

Interaction B x Y          3           1,631,663.1ns         0.3949

TSW                        5          36,929,215.3 **       <0.0001

Interaction TSW x Y        5           1,432,577,0ns         0.4932

V.C. (%)                                                      13.5

Year                  Average yield of dry biomass (Mg [ha.sup.-1])

2013                  7.8 b

2014                  11.0 a

Treatment                 2013              2014            Average

                          (Mg               (Mg               (Mg

                      [ha.sup.-1])      [ha.sup.-1])      [ha.sup.-1])

E5                        9.6               14.5             12.0 a

E4                        9.5               12.6             11.0 a

E3                        7.5               10.5             9.0 bc

E2                        5.9               8.8              7.4 cd

E1                        5.4               7.7              6.6 d

E0                        8.8               11.8            10.3 ab

Average                   7.8               11.0               --

Table 10. Variance analysis summary (ANOVA) and comparison of biomass
yield averages of Brachiaria brizantha fertigated with treated sewage
wastewater (TSW) in the spring of 2013 and 2014.

Variation source    DF    Mean square      Pr (>F)

Block (B)           3    11,248,379 **     0.0091
Year (Y)            1    59,748,413 **     <0.0001
Interaction BxY     3     10,628,428 *     0.0116
TSW                 5    207,980,458 **    <0.0001
Interaction TSWxY   5    25,456,396 **     <0.0001
V.C. (%)                                    10.3

Year     Average yield of dry
       biomass (Mg [ha.sup.-1])

2013            16.3 a
2014            14.1 a

Treatment    2013 (Mg        2014 (Mg        Average
            [ha.sup.-1])  [ha.sup.-1])  (Mg [ha.sup./-1])

E5          18.8   Abc    24.0    a           21.4
E4          17.3    Bc    22.1    ab          19.7
E3          12.1    De    14.9    de          13.5
E2          11.5    De    10.0    fg          10.8
E1          10.0    Ef    7.0     g            8.5
E0          15.0    Cd    20.0    bc          17.5

Average     14.1          16.3                 --

DF--degree of freedom; Significant at 0.05 * and at 0.01 ** of
probability; (ns) nonsignificant; V.C.--variation coefficient;
Averages followed by the same letter in the upper right do not
differ by Tukey's test (p < 0.05).

Table 11. Crude protein (%) of dry biomass of Brachiaria brizantha
due to the application rates of TSW and mineral fertilizing in 2013
and 2014.

Year     Season                     Treatments                 Average

                      E5     E4     E3     E2     E1     E0

2013     Summer      10.6   11.1   10.3   10.5   10.5   11.1    10.7
       Fall-winter   16.4   15.0   14.0   13.4   12.6   13.9    14.2
         Spring      12.3   11.0   11.8   10.7   13.2   13.6    12.1
         Average     13.1   12.4   12.0   11.5   12.1   12.9     --

2014     Summer      15.0   14.9   13.0   10.9   12.2   12.8    13.1
       Fall-winter   17.7   17.8   15.7   14.4   12.7   17.5    16.0
         Spring      15.5   12.0   10.6   10.2   8.1    11.8    11.4
         Average     16.1   14.9   13.1   11.8   11.0   14.0     --

Table 12. Neutral detergent fibre (%) of dry biomass of Brachiaria
brizantha due to the application rates of TSW and mineral fertilizing
in 2013 and 2014.

Year     Season                    Treatments                  Average

                      E5     E4     E3     E2     E1     E0

2013     Summer      65.8   61.0   66.7   65.2   58.1   66.4    63.9
       Fall-winter   57.1   56.8   60.4   61.5   61.2   55.5    58.8
         Spring      62.6   60.5   62.9   57.8   64.9   62.4    61.9
         Average     61.8   59.4   63.3   61.5   61.4   61.4     --

2014     Summer      55.1   55.8   57.0   60.6   61.1   55.1    57.5
       Fall-winter   52.8   52.7   56.0   57.6   59.5   56.4    55.8
         Spring      58.4   62.0   62.4   67.3   61.4   63.5    62.5
         Average     55.4   56.8   58.4   61.8   60.7   58.3     --
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Author:Santos, Gilmar Oliveira; de Faria, Rogerio Teixeira; Rodrigues, Gilberto Aparecido; de Figueredo Dan
Publication:Acta Scientiarum. Agronomy (UEM)
Date:Oct 1, 2017
Words:7187
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