High potential of variable rate fertilization combined with a controlled released nitrogen form at affecting cv. Barbera vines behavior

European Journal of Agronomy 112 (2020) 125949

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High potential of variable rate fertilization combined with a controlled released nitrogen form at affecting cv. Barbera vines behavior M. Gattia,b, M. Schippac, A. Garavania,b, C. Squeria, T. Frionia, P. Dossoa,d, S. Ponia,b,

T

⁎

a

Department of Sustainable Crop Production, Università Cattolica del Sacro Cuore, Piacenza, Italy Remote Sensing and Spatial Analysis Research Center (CRAST), Università Cattolica del Sacro Cuore, Piacenza, Italy c Haifa Italia Srl, Bologna, Italy d Studio di Ingegneria Terradat, Paderno Dugnano, MI, Italy b

A R T I C LE I N FO

A B S T R A C T

Keywords: Variable rate fertilization Controlled release fertilizers Vigor Nutrition Yield Grape composition

Variable rate technologies allow site-specific management of parcels characterized by different levels of vigor and/or yield. Fertilization based on actual plant needs is one of the most promising applications of precision farming aiming at improving efficiency, optimizing vine balance, as well as limiting environmental impact. Although this strategy appears suitable for developing new vineyard management models, few experiences validating this hypothesis are available in the literature. Based on a pre-trial remotely sensed vigor map (NDVIderived, 5 m resolution), a three-year study was performed in a Vitis vinifera L. cv. Barbera vineyard situated in the Colli Piacentini area. Vigor level (L = low, M = medium and H = high) and fertilization technique (Standard, Variable Rate Application, and unfertilized Control) were the main factors in a randomized block design. The controlled release fertilizer Multicote™ Agri ([NPK fertilizer 13-5-21 + 7MgO+14SO3 (Controlled Release Nitrogen > 46% on the total nitrogen, with longevity 2÷4 months), low in chloride] was used and the input rate calculated according to the N-supply. For each vigor level the study compared no fertilization (0 kg/ ha), standard supply (40 kg of N /ha) and Variable Rate Application (VRA) supply delivering 0, 40 and 80 kg of N/ha to H, M and L, respectively. Vine growth, yield, leaf nutritional status and fruit composition were assessed. Results show that the classified L vigor plots had significantly less growth (i.e leaf area or pruning weight per vine) than M and H vigor plots, whereas yield components and grape composition followed a linear variation with vigor. There was a large prevalence of vigor x technique interactions suggesting that VRA had a differential impact on vine behavior depending upon the initial level of vigor. For vegetative and yield parameters, in the L vigor vines, increased Multicote™ Agri dosage delivered as control (0 kg of N/ha), standard (40 kg of N/ha) and VRA (80 kg of N/ha) caused a very close and linear increase in total leaf and yield per vine, whereas, within the M and H vigor plots, the effect due to fertilization technique was very mild. Such a behavior was nicely mirrored by grape composition at harvest as, in L vines, applying 40 or 80 kg of N in the form of Multicote™ Agri induced a progressive and significant reduction in both must soluble solids and total anthocyanins concentration, although the oenological quality of the resulting must was still satisfactory and in compliance with the oenological target. The novelty of the present work is that, unlike previous variable rate fertilization attempts where a rapid nitrogen release fertilizer such as urea was used, L vigor vines showed a very prompt response to the amount of Multicote™ Agri application, confirming higher effectiveness of this chemical form and higher flexibility in adjusting the level of vigor and yield according to specific needs. Conversely, when the initial level of vigor was medium or high, differential fertilization resulted in overall minor modifications of the vine behavior.

1. Introduction Nitrogen is likely the most powerful nutrient able to affect vine behavior due to its crucial role in several processes and its well-known mobility in the soil and through the plant (Keller, 2015; Marschner,

⁎

1995). Nitrogen supply is fundamental for effective growth and tissue completion of developing sinks (Gastal and Lemaire, 2002); nitrogen is the main component of the most abundant photosynthetic enzyme ribulose, 1,5 bis-phosphate carboxilase (Rubisco) (Seemann et al., 1987) and, with it, a linear correlation between assimilation rates and leaf

Corresponding author at: Via Emilia Parmense 84, 29122, Piacenza, Italy. E-mail address: [email protected] (S. Poni).

https://doi.org/10.1016/j.eja.2019.125949 Received 7 July 2019; Received in revised form 14 September 2019; Accepted 15 September 2019 1161-0301/ © 2019 Elsevier B.V. All rights reserved.

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grower might decide to move to a site-specific fertilization technique, e.g. adapting the amount of supplied fertilizer units to the effective vine needs. More specifically, once the ground truthing procedure has identified the vigor level achieving maximum vineyard efficiency, VR fertilization should aim to make vines showing excessive or too low vigor converge towards the most balanced vigor level. Despite such tempting perspective, medium- or long-term work on response to VR fertilization in orchards and vineyards is surprisingly poor. In a pioneer work, Davenport et al. (2003) tested variable rate application of nitrogen, potassium, and phosphorous over four years on cv. Concord. Although the VR plan was drawn from a standard soil sampling protocol, VR did not alter in-field yield variability. Yield correlated positively with N, negatively to K, and was virtually non-responsive to P. More related work has been conducted recently on citrus (Colaço and Molin, 2017). Over five years, yield responses of citrus trees to variablerate prescriptions were evaluated based on soil and leaf grid sampling and on yield maps. The results were quite contradictory, since on the site with greater intra-field variability, a yield increase of 13.1% versus uniform application was associated with reducing K2O by 37.4%, while on the other site, characterized by lower intra-field variability, yield was not affected. In the grapevine, the most comprehensive studies provided insofar were those by Gatti et al. (2018, 2019) who, in a small cv. Barbera vineyard (less than 1 ha surface) identified pre-trial three vine vigor levels classified as low, medium, and high (L, M, H) from normalized difference vegetation index (NDVI) values calculated from remote satellite imaginery (5 m pixel resolution). Then, the response to VR fertilization performed with urea to supply no N (0 kg/ha as a control), standard rate (60 kg/ha), and variable rate application (VRA) of 0, 60 or 120 kg/ha to H, M, and L was followed over four consecutive seasons leading to the following key points : i) L vines were most balanced, suggesting a change in fertilization strategy to no N application in M and H areas, and for maintenance supply in L plots ; ii) within vigor variability for total leaf area, pruning weight, yield and berry weight was considerably reduced in years 3 and 4 of the trial; iii) in the long term, VRA reduced the within-field canopy size variability as compared to standard fertilization, and iv) a bit surprisingly, L vines had a quite slow or negligible response to increase N supply and most of the observed responses were due to reduced vine capacity. This latter item poses a serious concern in terms of readiness of vine response to the fertilizer VRA. Clearly, type of fertilizer, N form, mode and timing of distribution as related to maximum uptake capacity by roots, plant demand vis-à-vis phenological stage, soil proprieties and localization of the grapevine root system can greatly affect vine response to the metered supply. The hypothesis that we pursue in this study is that combining variable rate vineyard fertilization with distribution of a controlledrelease form of nitrogen might dramatically improve the promptness of vine response to the amount of supplied fertilizer units, thereby rendering the tool much more effective and flexible. The trial ran for three years in a small Barbera vineyard and included a comprehensive assessment of vegetative growth, leaf nutrition, yield components and grape composition.

blade or petiole nitrogen concentration has been consistently reported in literature (Evans, 1989; Keller, 2005; Williams et al., 1994); finally, nitrogen is also involved in the leaf longevity process, as it has been demonstrated that photosynthetic decline in a mature grapevine leaf links to increased N export towards growing sinks (Conradie, 1986; Poni et al., 1994; Lim et al., 2007). While such a critical role would not admit large deviations for optimal or at least non limiting N supply to the grapevine plant at different phenological stages, cases of N deficiency or excess are anything but rare. Leaf N deficiency is especially harmful when occurring around flowering (May, 2004) as it can severely curtail fruit set of the current season, while having also negative effects on next-year bud induction (Guilpart et al., 2014); N excess can likely be even more detrimental as it can lead to: i) too high shoot growth rates early in the season, with negative consequences on fruit set; ii) excessive canopy density with obvious negative impact on bud induction and ripening (e.g. conferring excessive green aroma compounds and rot susceptibility) (Mundy, 2008; Mendez-Costabel et al., 2014; Thomidis et al., 2016); iii) too prolonged shoot growth late in season leading to excessive competition towards ripening and formation of less cold-resistant wood; iv) compact clusters with larger berries leading again to higher rot incidence and less favorable skin-to-berry ratio; v) down-regulation of transcripts expression of both structural and regulatory genes involved in anthocyanin biosynthesis (Soubeyrand et al., 2014) and vi) surface- and ground-water pollution. Such quite frequent phenomena of either N deficiency or excess witness for an objective difficulty to fine tune N supply and availability with actual vine demand during key phenological stages (Linsenmeier et al., 2008). To some extent, well-known mobility of N forms in soil and through a plant is a factor that might aggravate the mismatch between supply and demand functions. For instance, it is still quite common in viticulture to distribute > 50% of the yearly total N amount before bud-break through prompt-formulations such as ammonium nitrate or urea. While being prone to leaching in the case of rainy postbudburst conditions, such N amount is unlikely to match an effective vine demand, as it has been shown that up until the stage of 5–6 expanded leaves on the developing shoot, a great deal of the N requirement is met through re-translocation from storage reserves (Schreiner et al., 2006; Zapata et al., 2004). Conversely, if it is true that the highest demand for N by the vine plant is from flowering through fruit-set, fertilization management at these stages should be skilled enough to ensure the required amount without letting eventual N excess to produce negative effects. Therefore, a much better matching seems to be needed between the timing the fertilizer is placed in the soil and the timing when the vine truly needs it and, within such a context, fertilization strategy can play a primary role. Controlled-release fertilizers (CRF) seems to be the best option in achieving these requirements. A CRF is defined as a fertilizer capable of releasing nutrients in the environment on a slow or controlled manner (Shaviv and Mikkelsen, 1993). Modern CRF are often based on the coating of granules of conventional fertilizers with various materials that reduce their dissolution rate (Jarosiewicz and Tomaszewska, 2003). The best coating substances that carry out this semi-permeable action consist of hydrophobic organic polymers (resins). The two main families of common resins in practical use are the alkyd-type resins and polyurethanes coatings (Trenkel, 2010). The release of nutrients from these products is mainly temperature dependent (Raban, 1994), while moisture content in the soil, pH, wetting and drying, and soil microbial activity have little effect on the release (Christianson, 1988). A second item that needs to be introduced if the dual goal of achieving better supply-demand equilibrium in N fertilization as well as significant savings in the amounts of applied fertilizer wants to be pursued is a variable rate (VR) application technique (Zaman et al., 2005; Schumann, 2010; Aggelopoulou et al., 2011; Maghsoudi and Minaei, 2014; Matese and Di Gennaro, 2015). It implies that, once intra-vineyard variability in terms of vine vigor and yield has been properly described and validated by suitable ground truthing, the

2. Materials and methods 2.1. Plant material, vigor maps and experimental layout The trial was conducted over three years (2016–2018) in a commercial, non-irrigated vineyard of cv. Barbera grafted on Kober 5BB at a spacing of 2.5 x 1.2 m (inter- and intra-row) for a resulting density of 3333 vines/ha. The vineyard was planted in 2011 at Ziano Piacentino, Malvicini Paolo Estate, (44°98′ N, 9° 36′E, 272 m a.s.l.), Italy. The vineyard is located on an east-facing gentle slope with East-West oriented rows; vines are trained to a single-cane vertically shoot positioned (VSP) Guyot trellis with a bud-load of about 11 nodes per vine. The 2

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Fig. 1. Map of normalized difference vegetation index (NDVI) showing the high vigor (H, green), medium vigor (M, yellow), and low vigor (L, brown) zones derived from a multispectral remotely-sensed image of the Barbera vineyard taken on 17 July 2015 at full canopy development. Each vigor level encompasses equal surface. Sensor bands and wavelengths were: blue: 440 to 510 nm, green: 520 to 590 nm, brown: 630 to 685 nm, red edge: 690 to 730 nm, and near infrared: 760 to 850 nm (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article).

samples were air dried and sifted through a 2 mm sieve. The chemicalphysical analyses of the soil were performed by an external laboratory including the following determinations: percentages of sand, silt and clay for the description of the texture, total and active carbonates, organic matter, organic carbon, as well as pH, total nitrogen (g/kg), cation exchange capacity (meq/100 g), electrical conductivity (mS/cm) and the determination of available, exchangeable and soluble ions (expressed as ppm of P, K+, Ca2+, Mg2+, Cl−, Na+).

cane is tied onto the horizontal support wire at 0.9 m above the ground and three pairs of catch wires forms a vertical canopy wall of about 1.5 m above the main cane. During each season, daily minimum, mean and maximum temperature (°C) and total rainfall (mm) from 1 Apr (DOY 91) to 31 Oct (DOY 304) were recorded by a weather station located within the vineyard. Remotely sensed imagery of the vineyard acquired in July 2014 using a RapidEye constellation satellite with a ground resolution of 5 m was used to calculate the NDVI index. The vigor map was computed using the ‘equal area’ algorithm implemented by the engineering company Studio Terradat (Paderno Dugnano, Italy), resulting in the segmentation of the vineyard into three vigor classes. The low (L), medium (M) and high (H) vigor areas were associated to the NDVI ranges 0.276 - 0.329, 0.290 - 0.382 and 0.382 - 0.435, respectively (Fig. 1). Thereafter, a prescription map was defined to implement a variable rate fertilization technique, adjusting N supply to each vigor level. Fertilization techniques consisted of: i) an unfertilized control (C); a standard, single dose application (S) and a variable rate application (VRA). N was supplied as a controlled-release fertilizer (Multicote™ Agri – Haifa, Italy) and varied as it follows: control (C: 0 kgN/ha), standard (S: 40 kgN/ha), VRA (0, 40 and 80 kgN/ha for H, M and L vigor levels, respectively). Multicote™ Agri is a NPK (13.5.21) + Mg + S controlled release fertilizer warranting not less than 46% of its total N is provided under a controlled release formula based on a semi permeable polymer coating. Three blocks encompassing all vigor levels were identified and, within each block, the three fertilization techniques were randomly assigned; for each block x treatment combination, four vines were tagged as sub-replicates and used for subsequent determinations. Nitrogen fertilization was performed 4 May 2016, 20 April 2017 and 27 April 2018 distributing Multicote™Agri through a variable-rate fertilizer spreader (Casella Macchine Agricole S.r.l., Carpaneto Piacentino, Italy) equipped with a GPS receiver and an automatic weighing system. The system incorporates the fertilizer into the soil at a depth of 15 cm using two 130 cm spaced plowshares each one operating 55 cm away from the row axis. Canopies were mechanically trimmed once in the season when most of the shoots outgrew the top foliage wire, on 22 June 2016, 7 June 2017 and 18 June 2018.

2.3. Vegetative growth Each season, at the end of growth and for each vigor x technique x block combination, four vines, other than those tagged, were selected and all main and lateral leaves from one shoot per plant were sampled; then each blade was measured through a leaf-area meter (LI−COR 3000 Bioscience, Lincoln, NE). In each season, on test vines, the total number of nodes per vine on main and lateral shoots was counted each year after leaf fall. Leaf area (LA) was subsequently calculated by combining average leaf size and the number of counted nodes separating main and lateral wood contributions. One-year-old pruning mass was recorded at winter pruning for main and lateral canes. Vine balance was then given as the leaf area-to-yield ratio (m2/kg). 2.4. Leaf nutritional and water status Each season, at veraison, 50 main opposite-to the cluster basal leaves were sampled for each V x T treatment combination. After removing the petioles, the blades were dried at 75 °C until reaching a constant weight. Thereafter, the ground samples were sent to the laboratory for determination of N, P, K, Mg, Ca, S, Fe e B according to standard methods. On 26 July 2016 and 3 July 2017, eight representative vines per each vigor area were selected to assess leaf water potential. Two leaves per vine were sampled for pre-dawn (ΨPD) and midday (ΨM) leaf water potential determined using a Scholander pressure chamber. 2.5. Yield components and ripening When inflorescences were clearly visible [BBCH 53, according to Lorenz et al. (1995)], the total number of shoots and inflorescences per vine was counted and shoot fruitfulness determined in each season. Harvest was performed when the grape technological maturity in low vigor areas was reached (TSS ∼ 23°Brix; TA ∼ 8 g/L). At harvest, 19 September 2016, 29 August 2017 and 19 September 2018, all clusters from the tagged vines were picked, counted and promptly weighted. A

2.2. Soil analysis For each vigor level, soil samples were performed in untilled and non-fertilized spots in spring 2016 (9 samples in total). After removing 10 cm of top soil, holes were drilled to a maximum depth of 70 cm using stainless-steel sampling probe (3-cm inner diameter). Thereafter, soil 3

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Table 1 Characterization of the chemical-physical properties of the soil according to different vigor zones (H = high, M = medium, L = low).

Vigor (V) H M L F-prob

Vigor (V) H M L F-prob

pHH2O

Total carbonates (%)

Organic matter (%)

Organic carbon (%)

Total nitrogen (g/kg)

CEC (meq/ 100 g)

Sand (%)

Silt (%)

Clay (%)

Ψ pre-dawn (MPa)

Ψ mid-day (MPa)

8.09b 8.10b 8.20a

18.33b 15.22b 23.00a

1.73a 1.71a 1.34b

1.00a 0.99a 0.78b

1.208a 1.191a 0.933b

30.59ab 31.88a 29.78b

24.5b 33.1a 37.0a

47.4a 39.1b 33.4c

−0.29a −0.58c −0.49b

−1.00a −1.18b −1.23b

**

**

**

**

**

*

**

28.1 27.8 29.6 ns

**

**

**

Available P (ppm)

Available P2O5 (ppm)

Exchangeable K+ (ppm)

Exchangeable K2O (ppm)

Exchangeable Na+ (ppm)

Exchangeable Ca2+ (ppm)

Exchangeable Mg2+ (ppm)

Soluble Cl− (ppm)

Soluble K+ (ppm)

Soluble Na+ (ppm)

Soluble Ca2+ (ppm)

Soluble Mg2+ (ppm)

14.0a 9.9b 7.3b

32.1a 22.6b 16.8b

296a 310a 215b

355a 372a 258b

5655a 5887a 4964b

**

**

**

538 574 771 ns

16.0 15.0 15.9 ns

9.0 10.7 7.5 ns

4.5b 4.2b 6.3a

**

39 46 44 ns

64.2 61.7 58.7 ns

7.2 7.3 11.3 ns

**

**

Within column, in case of significant F test, mean separation was performed by SNK test. * = p < 0.05. ** p < 0.01, ns = not significant.

and anthocyanins profiles by HPLC. A second 50-berry subsample was used to measure the concentration of total anthocyanins and phenols after Iland (1988) and final data were expressed as mg/g of fresh berry mass. The remainder of each three-bunch sample was crushed and the resulting musts were immediately analyzed for total soluble solids concentration (TSS, as Brix), pH and titratable acidity (TA). TSS concentration was determined using a temperature-compensating refractometer (RX-5000 ATAGO U.S.A., Bellevue, WA), pH was assessed with a pH-meter CRISON GLP 22 (Crison, Barcelona, Spain) and TA was measured by titration with 0.1 N NaOH to a pH 8.2 endpoint and expressed as g/L of tartaric acid equivalents. The must potassium (K+) concentration was measured by an ion-selective electrode (Model 9661, Crison). From veraison until harvest, ripening curves were determined and average berry weight, must TSS, TA and total anthocyanin concentration were weekly assessed according to the methods described above from a 100-berry sample per each vigor x technique x block combination. At harvest, a visual rot assessment was performed on each cluster of each tagged vine. Six classes (healthy: 0%, 1–5%, 6–25%, 26–50%, 51–75% and 76–100%) were used to score the percentage of infected clusters over total (incidence) and the extent of damage within cluster (severity).

Table 2 Different leaf area components per vine (main, lateral, total) and winter pruning weight per vine (main, lateral, total) recorded over three years (2016–2018) on field-grown cv. Barbera grapevines growing in different vigor zones (H = high, M = medium, L = low) and subjected to different N fertilization regimes. C = non-fertilized control; S = standard N supply at 40 kg/ha; VRA = variable rate N application (0 kg in H, 40 kg/ha in M and 80 kg/ha in L).

Vigor (V) H M L F-prob Technique (T) C S VRA F-prob Year (Y) 2016 2017 2018 F-prob VxT VxY TxY

Main leaf area/ vine (m2)

Lateral leaf area/ vine (m2)

Total leaf area/ vine (m2)

Main pruning weight/ vine (g)

Lateral pruning weight/ vine (g)

Total pruning weight/ vine (g)

3.16a 2.80b 2.73b

0.99a 0.83b 0.71c

4.15a 3.63b 3.35c

927a 880a 711b

283a 291a 211b

1210a 1171a 922b

**

**

**

**

**

**

2.71b 2.93a 3.04a

0.79b 0.84ab 0.93a

3.50b 3.77a 3.97a

813b 717b 988a

224b 189b 372a

1034b 906b 1360a

**

**

**

**

**

**

2.77b 2.39c 3.53a

0.99a 0.87b 0.69c

3.76b 3.26c 4.22a

878b 528c 1112a

252b 132c 401a

1130b 660c 1513a

**

**

**

**

**

**

**

**

**

**

*

ns

ns

ns

*

*

ns ns

ns ns

**

**

**

2.6. HPLC analyses

ns

The quantification of organic acids was performed injecting musts into HPLC after filtering through a 0.22 μm polypropylene filter. The identification was performed by external calibration with standards and concentration was calculated measuring the peak area and expressed in g/L. Samples deriving from ripening curves were 4 times diluted before filtration and then transferred to HPLC auto-sampler vials. For this analysis an Allure Organic Acid Column, 300 × 4.6 mm, 5 μm (Restek, Bellefonte, PA, USA) was used. Separation was performed in isocratic conditions using water, pH adjusted at 2.5 by adding ortho-phosporic acid. The column temperature was maintained at 30 ± 0.1 °C, 15 μl of sample was injected. The elution was monitored at 200–700 nm and detected by UV–vis absorption with DAD at 210 nm. Anthocyanins and flavonols were analyzed according to Poni et al. (2017). Phenolic compounds were extracted from skins after Downey et al. (2006): 0.100 g of freeze-dried skin were extracted in 1.0 ml of 50% (v/v) methanol in water for 15 min with sonication. The skin extracts were centrifuged for 5 min at 10,000×g at 4 °C, fltered through a 0.22 μm polypropylene syringe for HPLC analysis and transferred to HPLC auto-sampler vials. The chromatographic method was developed

Within column, in case of significant F test, mean separation was performed by SNK test. * = p < 0.05. ** p < 0.01, ns = not significant.

three-basal-cluster sample was also collected from each tagged vine, each cluster was individually weighted and rachis length measured to calculate a compactness index, given as total berry fresh mass/rachis plus main shoulder length ratio (g/cm). From each of the three clusters, 10 berries were collected, weighed and immediately frozen at −20 °C. Skin, flesh and seed mass were then determined through the use of a razor blade and a small metal spatula. Seeds and flesh were carefully removed from each berry without rupturing any pigmented hypodermal cells, then the seeds carefully separated by hand from the flesh and the number of seeds per berry was simultaneously counted. Both skins and seeds were rinsed in deionized water, blotted dry, and weighed. The skins were stored and lyophilized to determine flavonol 4

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1.5

2.0 1.0

C

0.9 0.6 0.3 0.0

0.0 L

M

M

1.2 0.9 0.6 0.3 0.0

Total puning weight/vine (kg)

1.5

M

H

2.0 1.0

L

M

H

2.2

E

2.1

F 2.1

1.8 2.0

1.5 1.2 0.9

1.9 1.8

0.6 1.7

0.3 0.0

L

3.0

H

2.4

D

4.0

0.0 L

H

1.8

Main pruning weight (kg/vine)

1.2

Total leaf area (m2/vine)

3.0

5.0

B

N (%)

4.0

A

C S VRA

Lateral leaf area (m2/vine)

Main leaf area (m2/vine)

5.0

1.6

L

M

H

L

M

H

Fig. 2. Partitioning of the interaction between vigor levels (H M, L) and fertilization technique (C, S, VRA) for main, lateral and total leaf area per vine (panels A,B,C), main and total pruning weight per vine (panels D,E) and leaf N concentration (% DM) at veraison (panel F). Each treatment combination mean is calculated over years and sub-replicates (n = 12). Vertical bars of each column represent Standard error (SE). Within each vigor level, N supplied per hectare under C, S and VRA were, in order; 0, 40 and 80 kg in L, 0, 40 and 40 kg in M and 0, 40 and 0 kg in H.

= < 0.05 was used for multiple comparisons within dates. Equality of variances of the differences between all possible pairs of within-subject conditions (i.e., levels of vigor or fertilization techniques) was assessed through the Mauchly’s sphericity test.

after Poni et al. (2017). Phenolic compounds were identified using authentic standards and expressed as mg/g dry skin according to their respective calibration curve. 2.7. Chemicals

3. Results Water Milli-Q quality, acetonitrile and methanol were obtained from VWR (Radnor, PA, USA). Formic acid, sodium hydroxide, orthophosphoric acid 85%, L-(+)-tartaric acid, L-(-)-malic acid, citric acid, (+)-catechin, (-)-epicatechin, were purchased from Sigma-Aldrich (St. Louis, MO, USA). The following commercial standards from Extrasynthese (Genay, France) were used: t-resveratrol, t-piceid, myricetin (Myr), myricetin 3-O-glucoside (Myr 3-O-glc), quercetin 3-Oglucuronide (Quer 3-O-glu), quercetin 3-O-glucoside (Quer 3-O-glc), kaempferol 3-O-glucoside (Kmp 3-O-glc), delphinidin 3-O-glucoside (Dp 3-O-glc), cyanidin 3-O-glucoside (Cy 3-O-glc), petunidin 3-O-glucoside (Pt 3-O-glc), peonidin 3-O-glucoside (Pn 3-Oglc) and malvidin 3O-glucoside (Mv 3-O-glc).

3.1. Weather course The 2016 season was fairly typical of the area with Winkler’s Index setting at 1944 DD and annual rainfall of 758 mm, with a notably wet spring (Fig.S1). Despite a fairly cool spring, 2017 was the driest year with 2143 DD accumulated from 1 April to 31 October and only 289 mm of rain over the same period. In greater detail, rainfall was unevenly distributed from flowering to harvest, with a single event contributing 43 mm out of a total of 99 mm. June, July and August were quite hot, with Tmax often exceeding 35 °C. The following year (2018) had a more uniformly distributed rainfall (425 mm from 1 Apr to 31 Oct, 725 mm in the entire year, in line with the district average). Even if June and July were slightly cooler than 2017, the total heat accumulation in the period 1 Apr-31 Oct was the highest recorded among the three experimental years (2200 GDD).

2.8. Statistical analysis Data were processed according to the MIXED procedure by SAS (SAS Institute, Inc.). Traditional mixed linear models contain both fixed- and random-effects parameters; the latter become the covariance parameters. In our study, the need for covariance parameters arises from measurements taken over years (random factor). Multiple comparisons within fixed factors (vigor levels and fertilization technique) were performed according to the Restricted Maximum Likelihood Method (REML) as described by Corbeil and Searle, 1976. Repeated measures of grape composition parameters taken during the ripening season were analyzed with the Repeated Measure analysis of variance (ANOVA) routine embedded in the XLSTAT software package (Addinsoft). The least squared (LS) mean method at p

3.2. Soil properties, vegetative growth and leaf nutrition Soil sampling performed on the three vigor area during the first trial season showed that several physico-chemical properties of L vigor plots differed from H plots as higher pH, total carbonates, sand fraction and soluble Na and, in contrast, lower organic matter and carbon, total nitrogen, clay fraction, available P, exchangeable K and Ca (Table 1). Pre-dawn and midday leaf water potentials taken in 2016 and 2017 on two dates in July also showed that L vines reached the most negative values for both parameters. 5

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Main leaf area (m2 /vine)

5.0

4.0

components vs. C, whereas when pruning weight components were evaluated VRA only was effective at increasing vigor (Table 2). As expected, lower vigor and vine capacity values were reached during the quite dry 2017 season, whereas the most vigorous year was 2018, with total pruning weight per vine exceeding the threshold of 1.5 kg. Vine response in terms of vegetative growth also highlighted a number of first order interactions (V x T and T x Y as shown in Table 2) needing adequate partitioning. For V x T interactions, L vines displayed a linear increase of total and main LA per vine with increasing Multicote ™ Agri dosage supplied through C, S and VRA approaches (Fig. 2 A,C) in the L plots. Conversely, for the same parameters, M and H vines were quite unresponsive to the amount of applied fertilizer. Lateral leaf area (Fig. 2B) and main pruning weight per vine (Fig. 2D) showed a somewhat different behaviour; the former displaying, in L vines, no further increase with VRA supplying 80 kg of N/ha, the latter instead showing a significant increase only when the N supply increased from 40 to 80 kg/ha. Quite interestingly, in H vines, total and main pruning weight per vine (Fig. 2 D,E) were decreased in S vs. VRA despite S supplied 40 kg/ha and VRA provided no input. Significant T x Y interactions were also ascertained for main and total pruning weight per vine (Fig. 3A,C) showing that, within each year and albeit with varying magnitude, the same amount of Multicote™ Agri (40 kg/ha) applied within a VRA technique was, especially in 2016 and 2018, much more effective at increasing such parameters as compared to the same dosage delivered within a standard application. Leaf blade concentrations of several nutrients assessed each year at veraison showed that, within vigor levels, leaf N (% DM) did not differ whereas L vines had generally lower concentrations in P, K and Na vs. M and L vines. A somewhat contradictory trend was shown by Ca, Mg and Fe concentrations (Table 3). Occasional effects on leaf nutrition were seen in response to fertilization technique where both S and VRA approaches were able to increase Mn and Cu concentrations in leaf blades. Overall, leaf nutrition prompted almost no interactions among factors except for leaf N evaluated as V x Y treatment combinations (Fig. 2F) and showing that in L vines, increasing Multicote™ Agri amounts provided with different fertilization techniques resulted in a linear increase on leaf N concentration (y = 0.003x + 1.8426, R2 = 0.94), whereas in M and H vines such a response was not significant.

A

C S VRA

3.0

2.0

1.0

0.0 2016

2017

2018

1.5

Lateral leaf area (m2/vine)

B 1.2

0.9

0.6

0.3

0.0 2016

2017

2018

2.4

Total pruning weight (kg/vine)

C 2.0 1.6

3.3. Yield components and vine balance 1.2

Throughout the three-year trial, L vines showed remarkably lower total yield per vine (4.37 kg) as compared to M (6.09 kg) and H (7.04 kg) vines (Table 4). Main yield components inducing such a response were cluster and berry weight and, albeit to a lesser extent, clusters per shoot and per vine. Despite L vines having a reduced rachis length, cluster compactness was the lowest in this vigor level. Due to relative changes in yield and leaf area (see data reported in Table 2) the total final leaf area-to-yield ratio significantly increased in L vines (0.92 m2/kg fruit fresh mass) vs. the other vigor levels, setting slightly above 0.6 m2/kg fruit fresh mass. Fertilization technique had no impact on any yield component and neither affected vine balance (Table 4). The highest cropping season was 2018, mostly due to quite heavy clusters as compared to the two other years. Similarly to vegetative growth parameters, a number of significant V x T interactions occurred (Fig. 4). The most consistent response was seen for L vines, whose yield per vine linearly increased with applied Multicote™ Agri amount (y = 0.0231x + 3.45, R2 = 0.98) (Fig. 4A.) The main driver of this response was cluster weight (Fig. 4B), whereas berry weight and clusters per vine showed a prompt and significant response shifting from 0 to 40 Kg/ha, whilst doubling the amount did not result in any further change (Fig. 4,C,D). Conversely, within M and H vines, the response to fertilization technique was milder and, in most cases, non significant. Yield parameters did not display any significant

0.8 0.4 0.0 2016

2017

2018

Fig. 3. Partitioning of the interaction between years (2016, 2017, 2018) and fertilization technique (C, S, VRA) for main leaf area, lateral leaf area and total pruning weight per vine (panels A,B,C). Each treatment combination mean is calculated over vigor levels and sub-replicates (n = 12). Vertical bars of each column represent Standard error (SE). Within each year, N supplied per hectare under C, S and VRA were, in order, 0, 40 and 40 kg.

For the two most commonly used indicators of vine capacity and vigor (i.e. total leaf area and wood pruning weight per vine, respectively) and for any other sub-component of vegetative growth, main effects calculated over vigor level indicated that H vines had higher values than L vines with M vines resulting in intermediate responses (Table 2). Main effects related to different fertilization techniques (T) showed that S and VRA generally increased total LA/vine and its 6

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Table 3 Ion concentration of opposite-to-the-cluster leaf blades sampled at veraison over three years (2016–2018) on field-grown cv. Barbera grapevines growing in high (H), medium (M), and low (L) vigor zones and subjected to different N fertilization regimes. C = unfertilized control; S = standard N supply at 40 kg/ha; and VRA = variable rate N application (0 kg in H, 40 kg/ha in M, and 80 kg/ha in L).

Vigor (V) H M L F-prob Technique (T) C S VRA F-prob Year (Y) 2016 2017 2018 F-prob VxT VxY TxY

N (%DM)

P (%DM)

K (%DM)

Ca (%DM)

Mg (%DM)

S (%DM)

Na (ppm)

Fe (ppm)

Mn (ppm)

B (ppm)

Cu (ppm)

Zn (ppm)

1.991 1.980 1.964 ns

0.179a 0.176a 0.152b

1.003a 0.976a 0.913b

2.643b 2.681ab 2.835a

0.141b 0.154b 0.185a

155a 142b 129b

78b 83b 95a

**

**

*

**

0.221 0.224 0.220 ns

**

**

66 66 73 ns

33 32 3 ns

155 147 146 ns

95 87 84 ns

1.940 1.990 2.004 ns

0.178 0.166 0.164 ns

0.991 0.940 0.961 ns

2.760 2.681 2.717 ns

0.159 0.154 0.167 ns

0.214 0.221 0.231 ns

129b 157a 140b

84 83 89 ns

57b 72a 76a

33 33 32 ns

135 150 162 ns

80b 83b 102a

1.960 1.995 1.980 ns

0.216a 0.153b 0.138c

1.076a 0.958b 0.859c

2.842a 2.650b 2.667b

0.266a 0.203b 0.197b

170a 125b 131b

99a 80b 76b

123a 58b 24c

28b 38a 31b

179a 126b 143b

124a 61c 81b

**

**

*

**

**

**

**

**

**

**

ns ns ns

ns ns ns

ns ns ns

0.159 0.160 0.162 ns ns ns ns

ns ns ns

ns ns ns

ns ns ns

ns ns ns

ns ns ns

ns ns ns

ns ns ns

**

ns ns

**

**

**

Within column, in case of significant F test, mean separation was performed by SNK test. * = p < 0.05. ** p < 0.01, ns = not significant. Table 4 Yield components and cluster characteristics recorded over three years (2016–2018) on field grown cv. Barbera grapevines growing in different vigor zones (H = high, M = medium, L = low) and subjected to different N fertilization regimes. C = non-fertilized control; S = standard N supply at 40 kg/ha; VRA = variable rate N application (0 kg in H, 40 kg/ha in M and 80 kg/ha in L).

Vigor (V) H M L F-prob Technique (T) C S VRA F-prob Year (Y) 2016 2017 2018 F-prob VxT VxY TxY

Clusters/ shoot

Clusters/vine

Cluster weight (g)

Berry weight (g)

Berries/ cluster

Yield/vine (kg)

Cluster compactness (g/ cm)

Rachis length (cm)

Leaf area-to-yield ratio (m2/kg)

1.9a 1.8ab 1.7b

23a 22a 19b

301.7a 280.5b 219.3c

2.32a 2.21b 2.05c

130a 128a 107b

7.04a 6.08b 4.37c

21.54a 20.38b 17.20c

13.4a 13.9a 12.6b

0.67b 0.61b 0.92a

*

**

**

**

**

**

**

**

**

1.8 1.8 1.8 ns

22 22 21 ns

261.1 264.3 276.0 ns

2.13 2.23 2.22 ns

123 120 124 ns

5.71 5.87 5.92 ns

18.91 20.30 19.91 ns

13.5 13.3 13.2 ns

0.70 0.73 0.78 ns

2.0a 1.8b 1.6c

23a 21b 22b

244.8b 241.6b 315.9a

2.29a 1.95b 2.34a

107c 124b 135a

5.62b 5.01c 6.86a

19.69 19.43 20.01 ns ns ns ns

13.4b 12.5c 14.1a

0.73 0.76 0.72 ns ns ns ns

**

**

**

**

**

**

ns ns ns

**

**

**

**

**

ns ns

ns ns

ns ns ns

ns

ns ns

**

ns ns ns

Within column, in case of significant F test, mean separation was performed by SNK test. * = p < 0.05. ** p < 0.01, ns = not significant.

increase in the flesh-to-berry ratio (Fig. 5 A,C). At the same time, in L vines, relative skin growth was markedly decreased by the same amount (40 kg/ha) of applied fertilizer (Fig. 5B,D). Notably the above effects did not occur in M and H vines.

V x Y or T x Y interactions. Looking at growth of single berry organs (Table 5), total skin fresh mass (g/berry) was not affected by vigor levels and, concurrently, total berry fresh mass decreased with decreasing vigor. As a consequence, relative skin mass, given as both skin-to-berry and skin-to-flesh ratios, increased in L vines as compared to M and H vines. L vines also showed, as a main effect, the lowest cluster rot incidence and severity (Table 5). Main effects related to fertilization technique showed that relative skin growth was higher in the unfertilized control plots. Supplying 40 kg/ha of N in the S and VRA, however, did not affect skin and flesh mass as well as rot susceptibility vs no N application. Several V x T interactions occurred for growth of single berry organs indicating that, in L vines, flesh mass was very sensitive to Multicote™ Agri supply up to the 40 kg/ha dose leading, in turn, to a significant

3.4. Ripening kinetics and grape composition Ripening curves are shown only for those parameters demonstrating, in at least one season, a significant time x treatment interaction. Within vigor levels this occurred for berry fresh mass, TSS, total anthocyanins and phenolics (Fig. 6A-L), whereas for different fertilization techniques the above requirement was met by total anthocyanins and phenols (Fig. 7A-F). In 2016, effects due to low vigor manifested only at the end of season with a reduced berry size (Fig. 6A) and overall 7

European Journal of Agronomy 112 (2020) 125949

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340

8.0

B

310 280

Cluster weight (g)

Yield (kg/vine)

7.0

A

C S VRA

6.0 5.0 4.0

250 220 190 160

3.0

130 100

2.0 L

M

H

L

M

H

26

2.6

C

2.4

D 24

2.0

Clusters/vine

Berry weight (g)

2.2

1.8 1.6

22 20 18

1.4 16

1.2 1.0

14 L

M

H

L

M

H

Fig. 4. Partitioning of the interaction between vigor levels (H M, L) and fertilization technique (C, S, VRA) for yield per vine (panel A), cluster weight (panel B), clusters/vine (panel C) and berry weight (panel D). Each treatment combination mean is calculated over years and sub-replicates (n = 12). Vertical bars of each colum represent Standard error (SE). Within each vigor level, N supplied per hectare under C, S and VRA were, in order; 0, 40 and 80 kg in L, 0, 40 and 40 kg in M and 0, 40 and 0 kg in H. Table 5 Absolute and relative growth of berry components and grape health recorded over three years (2016–2018) on field grown cv. Barbera grapevines growing in different vigor zones (H = high, M = medium, L = low) and subjected to different N fertilization regimes. C = non fertilized control; S = standard N supply at 40 kg/ ha; VRA = variable rate N application (0 kg in H, 40 kg/ha in M and 80 kg/ha in L).

Vigor (V) H M L F-prob Technique (T) C S VRA F-prob Year (Y) 2016 2017 2018 F-prob VxT VxY TxY

Skin mass (g/ berry)

Flesh mass (g/ berry)

Total seed mass (g/berry)

Seeds/ berry (n)

Skin/berry ratio (%)

Flesh/berry ratio (%)

Seed/berry ratio (%)

Skin/flesh ratio (%)

Rot incidence (%)

Rot severity (%)

0.1409 0.1394 0.1406 ns

2.0840a 1.9545b 1.7886c

0.0758a 0.0725a 0.0676b

2.2a 2.1a 2.0b

6.38b 6.62b 7.45a

90.33a 90.09a 89.15b

7.13b 7.41b 8.49a

6.69a 7.10a 4.01b

0.47a 0.40a 0.19b

**

**

**

**

**

3.29 3.29 3.40 ns

**

**

**

0.1413 0.1389 0.1408 ns

1.8624b 1.9821a 1.9839a ns

0.0694b 0.0717b 0.0752a

2.0b 2.1b 2.2a

7.24a 6.57b 6.64b

89.38b 90.22a 89.94a

3.38a 3.20b 3.42a

8.21a 7.35b 7.47b

*

**

*

*

*

*

4.78 7.03 5.88 ns

0.31 0.41 0.33 ns

0.1369 0.1385 0.1455 ns ns ns ns

2.0676a 1.6881b 2.0748a

0.0672b 0.0800a 0.0686b

2.0b 2.2a 2.0b

6.20c 7.61a 6.63b

90.87a 88.34c 90.37b

2.93b 4.05a 2.99b

6.86c 8.74a 7.42b

10.78a 0c 7.00b

0.60a 0b 0.45a

**

**

**

**

**

**

**

**

**

**

ns ns ns

ns ns ns

**

**

**

ns ns

ns ns

ns ns ns

ns ns ns

ns ns ns

ns ns

ns ns

Within column, in case of significant F test, mean separation was performed by SNK test. * = p < 0.05. ** p < 0.01, ns = not significant.

differences were found for both parameters in 2016 (Fig. 7A,D), next season showed that vines receiving no N inputs had higher anthocyanins and phenols concentration over the four last sampling dates (Fig. 7B,E). Such behaviour was partially maintained in 2018 for total

improved grape composition (Fig. 6D,G,L). In the dryer 2017, the above described behaviour was more pronounced and apparent at nearly all sampling dates (Fig. 6B,E,H,M). A quite similar pattern was also seen in 2018 (Fig. 6C,F,I,N). For Y x T interactions, while no significant 8

European Journal of Agronomy 112 (2020) 125949

M. Gatti, et al. 2.4

B 9

2.0

Skin/berry ratio (%)

Flesh mass (g/berry)

2.2

10

A

C S VRA

1.8 1.6 1.4

8

7

6 1.2 1.0

5 L

M

H

L

95

M

H

12

C

D

11

Skin/flesh ratio (%)

Flesh/berry ratio (%)

92

89

86

10 9 8 7

83 6 80

5 L

M

H

L

M

H

Fig. 5. Partitioning of the interaction between vigor levels (H M, L) and fertilization technique (C, S, VRA) for berry fresh mass (panel A) and for flesh-to berry, skinto-berry and skin-to-flesh ratios (panels B,C,D). Each treatment combination mean is calculated over years and sub-replicates (n = 12). Vertical bars of each colum represent Standard error (SE). Within each vigor level, N supplied per hectare under C, S and VRA were, in order; 0, 40 and 80 kg in L, 0, 40 and 40 kg in M and 0, 40 and 0 kg in H.

treatment except for myricetin-3glucoside that resulted significantly higher in L vines (Table 1S). Conversely, the abundance of the different anthocyanin forms basically followed the same trends found for total anthocyanins, with L vines showing highest values.

anthocyanins only (Fig. 7C). Grape composition at harvest was highly responsive to vigor and fertilization technique. L vines showed striking differences in must biochemistry as compared to M and L vines, whereas M vines, with the exception of tartrate, also differed from H vines for all remaining parameters, setting themselves in an intermediate position (Table 6). Overall must composition achieved in L vines was ideal as related to the characteristics of the pursued final wine and performance was outstanding for total anthocyanins and phenols (+50% and + 37% vs H vines) (Table 6). Differences recorded among fertilization technique levels were lower in magnitude, albeit reaching significance for several parameters: grapes sampled from C vines had higher TSS, tartrate, total anthocyanins and phenols than S and VRA vines. Fertilization technique had a differential impact on several grape composition parameters according to vigor level (Fig. 8). In particular, in L vines, must TSS linearly decreased with increasing Multicolte™ supply (y = -0.0341x + 24.823, R2 = 0.98) (Fig. 8A) and a similar response was also shown by total anthocyanins and phenolics although the larger drop occurred over the first increment of fertilizer supply (i.e. 0–40 kg/ha) (Fig. 8, B,C). M and L were much less responsive although in H vines a tendency was shown for decreased color and phenolics when the S technique applied 40 kg/ha of N vs. no supply performed under C and VRT techniques. Interactive V x Y effects were found for titratable acidity and malic acid (Fig. 9) indicating that although the relative amounts of Multicote™ Agri supplied every year to the vigor zones was constant, the differential in such parameters largely changed with season, reaching a maximum in 2018 and maintaining relatively similarity in the other two years. Besides a quite expected annual effect, concentrations of different flavonols in berries at harvest was not affected by the imposed

4. Discussion Data analyses carried out on main effects related to vineyard zone showing different vigor confirm that even remote satellite images taken at fairly low spatial resolution (5 m pixels) are fully adequate to distinguish among vigor levels (Lamb et al., 2004; Gatti et al., 2017) and the concurrent detailed ground truthing demonstrated that such differences, albeit referring to a small size vineyard, are wide enough to lead to totally different vine performances. Notably, almost any recorded parameter for vine capacity, vigor, yield and grape composition did show that L and H led to opposite vine responses. Vine balance as well as mean grape composition at harvest identified in L plots those providing the best fit to the desired wine type. While M vines showed a behavior more similar to H, such differentiation seems large enough to justify either different harvest dates or the recourse to mechanical selective harvesting (Bramley et al., 2005). Coupling vineyard vigor mapping with proper ground truthing also allowed identification of those factors leading L vines to reach optimal performances and namely : i) vine balance given as leaf-to-fruit ratio was increased until almost reaching the supposedly adequate threshold of 1 m2/kg of fresh fruit mass (Kliewer and Dokoozlian, 2005), ii) lower berry size and, in turn, higher relative skin mass played a role, indeed, for more favourable anthocyanins and phenols concentrations at harvest. It is more troublesome explaining if and how observed different vine vigor over the three vineayard zones relates to soil characteristics. 9

European Journal of Agronomy 112 (2020) 125949

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2016

3.0

H M L

2.8 2.6

Berry weight (g)

2017

* *

* *

2.4 2.2

*

2.0 1.8

1.4

24

Total soluble solids (Brix)

* * *

A

1.2

*

21

*

B

*

*

18

*

15

*

12 9

*

*

3

*

*

*

*

F

*

*

*

0.9

*

E

*

1.2

*

*

* * * *

*

D

1.5

C

*

*

6

0

Total anthocyanins (mg/g)

*

* *

*

1.6

*

*

*

*

* *

*

*

*

0.6

*

0.3

G *

2016

0.0

*

H

*

*

*

I

*

3.5

Total phenolics (mg/g)

2018

3.0 2.5 2.0

*

*

* * *

*

*

1.5

* * * *

*

*

1.0 0.5 0.0 190

J 210

230

250

*

*

* * *

K 190

210

230

250

190

*

L 210

230

250

270

DOY Fig. 6. Berry growth and ripening trends, from veraison until harvest, recorded each year for each vigor level (panels A–N). Ripening trends included total soluble solids (panels D–F), total anthocyanins (panels G–I) and total phenols (J–L). Within each sampling date, data were pooled over fertilization technique and subreplicates (n = 12). Repeated measure ANOVA carried out for each panel showed that F test performed on between subject effects (vigor) was always significant at P > 005; F test performed for within-subject effects (time x vigor) was significant at p < 0.05 for panels D,G,H,I,J,K,L. Within each sampling date, the asterisk indicates significant differences among vigor levels at P < 0.05 according to the Student-Newman-Keuls (SNK) test. Vertical bars indicate SE. 10

European Journal of Agronomy 112 (2020) 125949

M. Gatti, et al.

Total anthocyanins (mg/g)

1.8

A

C S VRA

1.5

B

1.2

*

*

C

*

*

* *

*

0.9 0.6 0.3 0.0

Total phenolics (mg/g)

D

E

F

*

3.5 3.0 2.5

* * *

*

2.0

*

1.5 1.0 190

210

230

250

190

210

230

250

190

210

230

250

270

DOY Fig. 7. Annual ripening trends, from veraison until harvest, of total anthocyanins (panels A–C) and total phenols (panels D–F). Within each sampling date, data were pooled over fertilization technique and sub-replicates (n = 12). Repeated measure ANOVA carried out for each panel showed that F test performed on between–subject effects (vigor) was significant at P > 005 for panels B and E; F test performed for within-subject effects (time x vigor) was significant at p < 0.05 for panels A,B, E. Within each sampling date, the asterisk indicates significant differences among vigor levels at P < 0.05 according to the Student-Newman-Keuls (SNK) test. Vertical bars indicate SE.

Table 6 Must composition recorded over three years (2016–2018) on field grown cv. Barbera grapevines growing in different vigor zones (H = high, M = medium, L = low) and subjected to different N fertilization regimes. C = non fertilized control; S = standard N supply at 40 kg/ha; VRA = variable rate N application (0 kg in H, 40 kg/ ha in M and 80 kg/ha in L).

Vigor (V) H M L F-prob Technique (T) C S VRA F-prob Year (Y) 2016 2017 2018 F-prob VxT VxY TxY

TSS (°Brix)

pH

TA (g/L)

Tartrate (g/L)

Malate (g/L)

Anthocyanins (mg/g)

Phenolics (mg/g)

20.8c 21.4b 23.5a

3.19b 3.17b 3.22a

9.65a 9.08b 7.94c

9.80b 10.22a 9.71b

3.43a 2.78b 2.25c

0.892c 1.056b 1.338a

1.573c 1.770b 2.159a

**

**

**

*

**

**

**

22.5a 21.6b 21.5b

3.19 3.18 3.21 ns

8.78 8.98 8.92 ns

10.42a 10.03a 9.29b

2.62b 2.99a 2.85a

1.204a 1.027b 1.055b

1.993a 1.705c 1.804b

**

**

**

**

3.27a 3.11c 3.19b

8.93 8.92 8.82 ns ns

9.62b 9.66b 10.46a

3.15a 2.56b 2.75b

1.283a 1.004b 0.999b

1.882a 1.949a 1.671b

**

**

**

**

ns ns ns

ns

**

**

**

ns ns

ns ns

**

22.7a 21.9b 21.0c **

**

**

ns ns ns

ns ns

**

ns

ns

Within column, in case of significant F test, mean separation was performed by SNK test. * = p < 0.05. ** p < 0.01, ns = not significant.

2016 from unfertilized plots confirm some differences in soil texture between different vigor areas, defining H areas as « clay » soil and both M and L areas as « clay loam » soil. However, when a calculator for soil hydrology parameters (Saxton et al., 1986) was used to derive hydrological constants from soil texture data and organic matter, it turned

Previous work has shown that intra-vineyard variability seems to be rather constant in time (Bramley and Hamilton, 2004; Kazmierski et al., 2011), being likely related to changes in physical soil properties (for instance variability in texture might affect available water hence vine growth throughout the season). Soil analyses performed in our study in 11

European Journal of Agronomy 112 (2020) 125949

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26 25

Total soluble solids (Brix)

suggest that L plots, likely due to faster water percolation, encountered higher water stress. Evaluating data against the second main factor (i.e. fertilization technique) also showed interesting outcomes. On one side, supplying 40 kg of N through S and VRA techniques (means averaged over vigor levels) did not affect yield (Table 4) but slightly worsened grape composition (less TSS and color, as shown in Table 6) as compared to the control plots; more interestingly though, for any winter pruning weight components, when the same amount of N (40 kg/ha) was provided within a VRA technique, vine vigor was enhanced, whereas when it was applied as standard practice it had no impact (Table 2). Such inference is nicely confirmed through the analyses of the significant V x T interaction that occurred for both total and main pruning weight per vine (Fig. 2 D,E). In particular, within each vigor level, VRA application always enhanced vine vigor as compared to S technique. The behaviour of H vines is quite enlightening: total and main pruning weight was higher in VRA, albeit such approach supplied no N vs the 40 kg of N furnished with the standard technique. A likely explanation is when N is supplied under already high vigor - as it is confirmerd by the fairly high total pruning weight per vine reaching 1210 g - excessive and too prolonged shoot growth will also lead to poorer wood maturity hence lowering actual total pruning weight at harvest. Significant V x T interactions also found for all LA components (Fig. 2A–C) contain a lot of valuable information. The main trait of the above interactions is that while in L vines there was a linear increase in total and main leaf area per vine, M and H vines were overall non responsive to a N supply reaching a maximum of 40 kg/ha. L vines response hints to the followings : i) it provides a different scenario as compared to what previously reported from Gatti et al., (2018, 2019) who showed, on a 4 year basis very low reactivity of low vigor Barbera vines to a N supply up to 120 kg/ha provided as urea, emphasizing the importance of the N form within a VR technique ; ii) the fact that, in L vines, lateral leaf area was less responsive to increased N supply (e.g virtually no change going from 40 to 80 kg/ha) suggests that most of the effect was expressed over the first part of the season as main total pruning weight essentially confirms; iii) as related to the previous point, Multicote™ Agri supply is therefore effective at correcting a deficiency in source availability early in the season that, on one side, might exert negative effects on fruit-set (May, 2004) and, most importantly, can be quite detrimental to bud induction for next year cropping (Guilpart et al., 2014) ; iv) reactivity of LA components to Multicote™ Agri is also supported by the significant increase that leaf N concentration showed in L vines upon Multicote ™ Agri applications (Fig. 2F). Efficiency in soil-to-vine N transfer when a controlled release nitrogen is used had been previously shown in orange trees (Maquieira et al., 1984) where a single dose of sulfur-coated urea maintained, in different tree organs, the same N concentration reached with a double amount of ammonium nitrosulphate. In terms of V x T interactions, the pattern described above also fits with yields components; it is highly relevant that, in disagreement with what Gatti et al. (2018, 2019) have reported using urea-based VR, cluster weight and yield per vine showed a linear positive response to the amount of applied Multicote™Agri. However, when the two key yield components (clusters/vine and berry size) were analyzed, it was quite apparent that all of them reached a saturation already at 40 kg/ha suggesting that this is a quite sensitive threshold, beyond which no further significant effects might be seen. Such high sensitivity of the yield components turns out to be very useful as calibrated Multicote™ Agri supply can be used to correct deficiencies in shoot fertility, fruit set or final berry size. Not surprinsingly, differential effect of fertilization technique on vegetative growth and yield components of L vines were mirrored by final grape composition at harvest as L vines receiving no N supply reached full maturity while both M and L vine lagged behind. It was also confirmed that an even moderate N supply provided to already vigorous vines can further impair berry pigmentation (Keller, 2005;

A

24

C S VRA

23 22 21 20 19 18 L

M

H

1.8

Total anthocyanins (mg/g)

B 1.6 1.4 1.2 1.0 0.8 0.6 L

M

H

3.0

C Total phenolics (mg/g)

2.7 2.4 2.1 1.8 1.5 1.2 L

M

H

Fig. 8. Partitioning of the interaction between vigor levels (H M, L) and fertilization technique (C, S, VRA) for total soluble solids (TSS, panel A), total anthocyanins (panel B) and total phenols (panel C). Each treatment combination mean is calculated over years and sub-replicates (n = 12). Vertical bars of each colum represent Standard error (SE). Within each vigor level, N supplied per hectare under C, S and VRA were, in order; 0, 40 and 80 kg in L, 0, 40 and 40 kg in M and 0, 40 and 0 kg in H.

out that soil available water was almost the same across vigor levels (∼130 mm of water/m of soil depth). Indeed, lower organic matter and total nitrogen content measured in L plots (Table 1) can explain, in part, the lower vigor, yet hints offered by pre-dawn and midday leaf water potential measured in 2016 and 2017 mid July (Table 1) strongly 12

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4.0

12

B 3.5 3.0

10

Malate (g/L)

Titratable acidity (g/L)

11

A

L M H

9 8 7

2.5 2.0 1.5

6

1.0 2016

2017

2016

2018

2017

2018

Fig. 9. Partitioning of the interaction between years (2016, 2017, 2018) and vigor levels (H M, L) and fertilization technique (C, S, VRA) for titratable acidity (panel A) and malic acid concentration (panel B). Each treatment combination mean is calculated over fertilization techniques and sub-replicates (n = 12). Vertical bars of each colum represent Standard error (SE). Each year, N supplied per hectare to each vigor level was: 13.3, 16.6 and 40.0 kg for L, M and H, respectively.

year basis, for most vegetative and yield parameters a linear positive response vs. the amount of applied N and grape composition were modified accordingly. Promptness of vine response to supplied N unit is of most significance as it will greatly help anytime N demand exceeds N supply at given crucial phenological stages (i.e flowering or fruit-set) and the time lapse between supply and apparent vine response needs to be correctly predicted or, at least, estimated. Then, if promptness of vine response is increased, chances are that the number of total seasonal N applications can be decreased. Furthermore, since the application of N to M and H vigor parcels had mild or even negative effects, initial VRA fertilization technique planned in this experiment, delivering 40.0, 26.6 and 13.3 kg/ha of N to L, M and H plots, respectively, for a resulting mean of 26 kg/ha, can be recalibrated ex-post into a more profitable scheme that could deliver to L, M and H vigor parcels 40, 0 and 0 kg of N (average 13.3 kg/ha on a vineyard basis) in that order. Reducing N supply/ha by 13.3 kg means that, based on current market price of Multicote™ Agri, the user can save about 75 euros/ha more. Then, the resulting change in yield and grape composition should also be considered; based on our data it can be estimated that shifiting from the VR fertilization technique we performed into the post-trial hypothesised strategy will not significantly affect total sugar per vine, summing up to 1274 g/vine and 1292 g/vine, respectively.

Soubeyrand et al., 2014) (Fig. 8B). While achievement of full maturity is usually a desired goal, the impact of global warming is increasing, in warm areas, the frequency of too early ripening. Under those circumstances, excessive alcohol content is reached quite early in the season while noble components (i.e. polyphenols and aroma compounds) are still far from their optimal concentrations (Palliotti et al., 2014). The behavior that we observed in our trial, in regard to low vigor vines, suggests that a moderate dosage of a slow-release N fertiliser can prove to be a user-friendly agent for getting a calibrated ripening delay, shifting color and aroma formation towards a cooler season. The fact that very few vine parameters showed a V x Y interaction clearly indicated that, over the three year span of the trial, the mean dosage delivered to L, M and H vines (40.0, 26.5 and 13.3 kg/ha, respectively, for data averaged over technique levels) was still ineffective at reducing relative differences between vines grown in areas of varying vigor. As hypothesed by others (Arnó et al., 2012; Tardaguila et al., 2011; Bramley et al., 2017) such a goal probably needs a higher number of trial years with reiterated applications of the same fertlization inputs. In their four-year trial on Barbera, Gatti et al. (2018, 2019) showed a tendency towards a narrowing of relative differences among vigor zones only on year 4 despite N supply varied from 20 kg/ha in H vigor vs 60 kg/ha in L vigor. In our work, some T x Y interactions were also found for parameters related to vine vigor (Fig. 3). It was quite apparent that, while fertilization technique had an overall mild effect on pruning weight components in the quite dry 2017 season, in the wetter 2016 and 2018 years, 40 kg of N/ha furnished within a variable rate configuration were more effective at pushing vigor than the same amount uniformly applied throughout the vineyard. This is a further confirmation that when the highest Multicote™ Agri N dosage (80 kg/ha) is applied to plots having lowest vigor, vine reaction is especially prompt and able to easily outscore vine response to 40 kg of N / ha (supplied under the S technique). Concurrently, in H vines, while the S supply (40 kg/ha) likely caused excessive growth with poor cane maturation, no supply under the VR technique better preserved wood quality and maturity.

Declaration of Competing Interest None. Acknowledgments The authors want to thank Paolo Malvicini Estate for hosting the trial and Casella Macchine Agricole S.R.L. for skilled technical support. Research carried out within the Nutrivigna project funded by the Emilia Romagna Region under the POR-FESR program (2014-2020). Grant n. J32J16000090007. Appendix A. Supplementary data

5. Conclusions

Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.eja.2019.125949.

The main hypothesis pursued in this study that combining fertilizer variable rate technology in grapevines with distribution of a controlledrelease form of nitrogen might result in a prompt vine response to the amount of supplied fertilizer units was successfully validated. Although we were not able to provide a concurrent comparison, within the same vineyard blocks, of vine response to either urea and a controlled-release N form, it is counter-intuitive that this latter formulation might increase promptness of vine reaction. In fact, low vigor vines showed, on a three

References Aggelopoulou, K.D., Pateras, D., Fountas, S., Gemtos, T.A., Nanos, G.D., 2011. Soil spatial variability and site-specific fertilization maps in an apple orchard. Precis Agric 12, 118–129. Arnó, J., Rosell, J.R., Blanco, R., Ramos, M.C., Martínez-Casasnovas, J.A., 2012. Spatial variability in grape yield and quality influenced by soil and crop nutrition

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riesling vineyard. Am. J. Enol. Vitic. 59, 255–264. Lorenz, D.H., Eichorn, K.W., Bleiholder, H., Klose, R., Meier, U., Weber, E., 1995. Phenological growth stages of the grapevine (Vitis vinifera L. Ssp. vinifera)—codes and descriptions according to the extended BBCH scale. Aust. J. Grape Wine Res. 1, 100–103. Maghsoudi, H., Minaei, S., 2014. A review of applicable methodologies for variable-rate spraying of orchards based on canopy characteristics. J. Crop Prot. 3, 531–542. Marschner, H., 1995. Mineral Nutrition of Higher Plants. Academic Press Ed., London, pp. 889. Matese, A., Di Gennaro, S.F., 2015. Technology in precision viticulture: a state of the art review. Int J Wine Res 7, 69–81. May, P., 2004. Development after fertilisation. In: May, P. (Ed.), Flowering and Fruitset in Grapevines. Lythrum Press, Adelaide, pp. 63–72. Maquieira, A., Climent, M.D., Puchades, R., et al., 1984. Plant Soil 80, 247. https://doi. org/10.1007/BF02161180. Mendez-Costabel, M.P., Wilkinson, K.L., Bastian, S.E.P., Jordans, C., Mccarthy, M., Ford, C.M., Dokoozlian, N.K., 2014. Effect of increased irrigation and additional nitrogen fertilisation on the concentration of green aroma compounds in Vitis vinifera L. Merlot fruit and wine. Austr J Grape Wine Res 20, 80–90. Mundy, D.C., 2008. A review on the direct and indirect effects of nitrogen on botrytis bunch rot in wine grapes. N. Z. Plant Prot. 61, 306–310. Palliotti, A., Tombesi, S., Silvestroni, O., Lanari, V., Gatti, M., Poni, S., 2014. Changes in vineyard establishment and canopy management urged by earlier climate-related grape ripening: a review. Sci. Hortic. 178, 43–54. Poni, S., Intrieri, C., Silvestroni, O., 1994. Interactions of leaf age, fruiting, and exogenous cytokinins in sangiovese grapevines under non-irrigated conditions. II. Chlorophyll and nitrogen content. Am. J. Enol. Vitic. 45, 278–284. Poni, S., Chiari, G., Caffi, T., Bove, F., Tombesi, S., Moncalvo, A., Gatti, M., 2017. Canopy physiology, vine performance and host-pathogen interaction in a fungi resistant cv. Sangiovese x Bianca accession vs. a susceptible clone. Sci. Rep. 7, 6092. Raban, S., 1994. Mechanisms of Controlled Release from Coated Fertilizers. M Sc Thesis. Faculty Agric Engn Technion-IIT, Haifa, Israel. Saxton, K.E., Rawls, W.J., Romberger, J.S., Papendick, R.I., 1986. Estimating generalized soil-water characteristics from texture. Soil Sci. Soc. Am. J. 50, 1031–1036. Schreiner, R.P., Scagel, C.F., Baham, J., 2006. Nutrient uptake and distribution in a mature Pinot noir vineyard. HortScience 41, 336–345. Schumann, A.W., 2010. Precise placement and variable rate fertilizer application technologies for horticultural crops. HortTechnology 20, 34–40. Seemann, J.R., Sharkey, T.D., Wang, J., Osmond, C.B., 1987. Enviropnmental effects on photosynthesis, nitrogen use efficiency and metabolite pools in leaves of sun and shade plants. Plant Physiol. 84, 796–802. Shaviv, A., Mikkelsen, R.L., 1993. Controlled-release fertilizers to increase efficiency of nutrient use and minimize environmental degradation-A review. Fert res 35, 1–12. Soubeyrand, E., Basteau, C., Hilbert, G., Van Leeuwen, C., Delrot, S., Gomes, E., 2014. Nitrogen supply affects anthocyanin biosynthetic and regulatory genes in grapevine cv. Cabernet Sauvignon berrries. Phytochemistry 103, 38–49. Tardaguila, J., Baluja, J., Arpon, L., Balda, P., Oliveira, M., 2011. Variations of soil properties affect the vegetative growth and yield components of “Tempranillo” grapevines. Precis Agric 12, 762–773. Thomidis, T., Zioziou, E., Koundouras, S., Karagiannidis, C., Navrozidis, I., Nikolaou, N., 2016. Effects of nitrogen and irrigation on the quality of grapes and the susceptibility to Botrytis bunch rot. Sci. Hortic. 212, 60–68. Trenkel, M., 2010. Slow-and Controlled-release and Stabilized Fertilizers: an Option for Enhancing Nutrient Use Efficiency in Agriculture. Int’l Fertilizer Industry Association, Paris, France. Williams, L.E., Dokoozlian, N.K., Wample, R., 1994. Grape. In: Schaffer, B., Andersen, P.C. (Eds.), Handbook of Environmental Physiology of Fruit Crops. Vol. I. Temperate Crops. CRC Press, Boca raton, FL, pp. 85–133. Zaman, Q.U., Schumann, A.W., Miller, W.M., 2005. Variable rate nitrogen application in Florida citrus based on ultrasonically-sensed tree size. Appl. Eng. Agric. 21, 331–335. Zapata, C., Deléens, E., Chaillou, S., Magné, C., 2004. Pertitioning and mobilization of starch and N reserves in grapevine (Vitis vinifera L.). J. Plant Physiol. 161, 1031–1040.

characteristics. Precis Agric 13, 393–410. Bramley, R.G.V., Hamilton, R.P., 2004. Understanding variability in winegrape production systems. Within vineyard variation in quality over several vintages. Aust. J. Grape Wine Res. 10, 32–45. Bramley, R.G.V., Proffitt, A.P.B., Hinze, C.J., Pearse, B., Hamilton, R.P., 2005. Generating benefits from precision viticulture through selective harvesting. In: Proceedings of the 5th European Conference on Precision Agriculture; 9–12 June. Uppsala, Sweden (Wageningen Agricultural Publishers: Wageningen, The Netherlands). pp. 891–898. Bramley, R.G.V., Siebert, T.E., Herderich, M.J., Krstic, M.P., 2017. Patterns of withinvineyard spatial variation in the ‘pepper’ compound rotundone are temporally stable from year to year. Aust. J. Grape Wine Res. 23, 42–47. Christianson, C.B., 1988. Factors affecting N release of urea from reactive layer coated urea. Fert Res 16, 273–284. Colaço, A.F., Molin, J.P., 2017. Variable rate fertilization in citrus: a long term study. Precis Agric 18, 69–191. Conradie, W.J., 1986. Utilization of nitrogen by the grapevine affected as affected by time of application and soil type. South Afr J Enol Vitic 7, 76–83. Corbeil, R.R., Searle, S.R., 1976. Restricted maximum likelihood (REML) estimation of variance components in the mixed model. Technometrics 18, 31–38. Davenport, J.R., Marden, J.M., Mills, L.J., Hattendorf, M.J., 2003. Response of Concord grape to variable rate nutrient management. Am. J. Enol. Vitic. 54, 286–293. Downey, M.O., Dokoozlian, N.K., Krstic, M.P., 2006. Cultural practice and environmental impacts on the favonoid composition of grapes and wine: a review of recent research. Am. J. Enol. Vitic. 57, 257–268. Evans, J.R., 1989. Photosynthesis and nitrogen relationship in leaves of C3 plants. Oecologia 78, 9–19. Gastal, F., Lemaire, G., 2002. N uptake and distribution in crops : an agronomical and physiological perspective. J. Exp. Bot. 53, 789–799. Gatti, M., Garavani, A., Vercesi, A., Poni, S., 2017. Ground-truthing of remotely sensed within-field variability in a cv. Barbera plot for improving vineyard management. Aust. J. Grape Wine Res. 23, 399–408. Gatti, M., Squeri, C., Garavani, A., Vercesi, A., Dosso, P., Diti, I., Poni, S., 2018. Effects of variable rate nitrogen application on cv. Barbera performance: vegetative growth and leaf nutritional status. Am. J. Enol. Vitic. 69, 196–209. Gatti, M., Squeri, C., Garavani, A., Frioni, T., Dosso, P., Diti, I., Poni, S., 2019. Effects of Variable Rate Nitrogen Application on cv. Barbera Performance: Yield and Grape Composition. Am. J. Enol. Vitic. 70, 188–200. Guilpart, N., Metay, A., Gary, C., 2014. Grapevine bud fertility and number of berries per bunch are determined by water and nitrogen stress around flowering in the previous year. Eur. J. Agron. 54, 9–20. Iland, P.G., 1988. Leaf removal effects on fruit composition. In: Smart, R., Thornton, R., Young, S.R.J. (Eds.), Proceedings of the Second International Symposium for Cool Climate Viticulture and Oenology; 11–15 January 1988. Auckland, New Zealand (New Zealand Society for Viticulture and Oenology: Auckland, New Zealand). pp. 137–138. Jarosiewicz, A., Tomaszewska, M., 2003. Controlled-release NPK fertilizer encapsulated by polymeric membranes. J. Agric. Food Chem. 51, 413–417. Kazmierski, M., Glemas, P., Rousseau, J., Tisseyre, B., 2011. Temporal stability of within‐field patterns of NDVI in non irrigated mediterranean vineyards. J Int Sci Vigne Vin 45, 61–73. Keller, M., 2005. Deficit irrigation and vine mineral nutrition. Am. J. Enol. Vitic. 56, 267–283. Keller, M., 2015. The Science of Grapevines: Anatomy and Physiology. Academic Press Ed., London, pp. 1–509. Kliewer, W.M., Dokoozlian, N.K., 2005. Leaf area/crop weight ratios of grapevines: influence on fruit composition and wine quality. Am. J. Enol. Vitic. 56, 170–181. Lamb, D.W., Weedon, M.M., Bramley, R.G.V., 2004. Using remote sensing to predict grape phenolics and colour at harvest in a Cabernet Sauvignon vineyard: timing observations against vine phenology and optimising image resolution. Am. J. Enol. Vitic. 10, 46–54. Lim, P.O., Kim, H.J., Nam, H.G., 2007. Leaf senescence. Ann Rev Plant Biol 58, 115–136. Linsenmeier, A.W., Loos, U., Löhnertz, O., 2008. Must composition and nitrogen uptake in a long-term trial as affected by timing of nitrogen fertilization in a cool-climate

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