The in-vivo raw pH measurements were conducted using a BORMAC XS pH 70 pH meter (www.giorgiobormac.com), range pH 0÷14, two decimals, provided with a combined plastic-glass electrode Hamilton Peek Double-PoreF, / Knick, dimensions (LxØ) mm 35×6, terminating with a very small and sensible tip sensor; other types were unstable and unreliable. The insertion of the tip in the petiole was facilitated by a small drill fitted with a 2 mm bit. In total 4181 leaves were examined for raw pH in the petiole axis, basal side. When the petiole was too thin for a tip insertion (olive, grape) then an axial cut by a lancet was executed, and the sensitive tip was wrapped by the two wings of petiole fork. For the Arabidopsis thaliana examination, several small packages of leaf blades were pierced with the tip. The maize pH was measured in the stem at the middle of 2^nd internode 6 and not in a part of the leaf.

As a total forty-nine species (Table 1, Table 2) were sampled from twenty-nine botanic families, relevant to several orchards, trees, vegetables and ornamental species. The grapevine was the most represented species (No. 2190) suited by the maize (792). Geographic origins were Piedmont (vine, vorn and several other), Emilia (hazelnut, blueberry, cherry and kiwi) and Puglia (olive). The pH values were analysed according the species, by a one-way ANOVA, using PROC GLM, Tukey s HSD, by SAS V. 9 software (SAS Institute, Cary, NC, USA).

Four Barbera grapevines were grown in-pot outdoor at the DISAFA experimental implant (45°03'58.6"N 7°35'23.8"E). The pH was measured on fifty-six leaves, without automatic correction for temperature, and sampled at three different timepoints (8-9; 12-13 and 19-20) during October 2016. In this part of the study were comprised other raw pH measurements recorded on Barbera grapevines from the same implant and sampled in July on the late morning. The external temperature was considered as the independent variable in a regression study of pH. The hour of the day was also plotted to consider the daily timeline effect.

The pH was measured on 176 leaves from 15 Grenache variety grapevines grown in pot at 25±2 °C in a greenhouse at the same implant as above. The leaves belonged from a control well watered and from a water-stresses thesis, monitored by Ψ_stem. The pH and the hydronium [H⁺] were related with the stress condition by a mixed model considering the plant random within stress group, and fixed the watering factor. Further regression analyses considered the pH and [H⁺] individual values on the Ψ_stem of the plant, established on some protected leaves at the moment when the plant was cut for the sap extraction.

Sixteen pots of Arabidopsis thaliana forty-days old were conditioned for thermo-light in a small phytotrone set at +18°C and + 30°C with 12 h day-night photoperiod. A first run was conducted at high level of watering where half of the pots were kept in dark for 24 h before the raw pH measurements, at the end of the daylight period. A following run was developed at normal watering, without dark period and a third run interested the residual plants, that were inducted in water stress at the two temperature levels in a normal daylight period. An IR pyrometer established the leaf temperature, while the pH-meter was disconnected for the thermal compensation. A total of 104 measurements were developed in the three runs.

In a framework of symbiotic biofertilization on fields experiments, a complex commercial consortium mycorrhizal-based (Micosat F ®, by CCS Aosta s.r.l.)11(S) was used and compared to internal control not inoculated (C). Different systems were adopted for root inoculation. In adult vineyards and other orchards was practiced a cut depth 30 cm at a distance of 50 cm from the row, distributing 20 kg ha^-1of bio-fertilizer. In a very minor cases, with young orchards, the plants have been pudding-treated. As a total seven species, were collected from four farms in 2014 (corn) and from nineteen orchards in 2015 (vine, hazelnut, blueberry, cherry, kiwi and olive); geographic origins were Piemonte (vine and corn), Emilia (hazelnut, blueberry, cherry and kiwi) and Puglia (olive). A two way ANOVA with interaction was used for statistical analysis. The model included the species and symbiotic factors

In the report published from the EFSA EU-ERA network12, in the original Table 1712 were exposed the frequencies of the fungicide and insecticide sprays for 13 orchards and crops. Because no data were available for pear, a key species for pH involvement, and coffee, some specialist colleagues were asked about. These mean values were colligated with the mean pH of the species by using polynomial models. A special study concerned the differential outbreaks of the fire blight (Erwinia amylovora) in apple and pear, as meticulously monitored in the Bolzano Province13 from 1999 to 2016 in some 8.185 farms; the relative incidence and odds ratio referred to farms and hectares.

The raw pH appeared as a very wide-distributed parameter across the species (Figure 1)

An apparent scenario of acidity, (Table 1, Table 2) spaced from Vitis riparia (pH = 3.06) to pumpkin (Sechium edule, 6.38) with a wide range of 974 to 1 in term not in potenz but in hydronium ^H+ concentration, respectively. The grapevine, Vitis vinifera, appeared as the most acidic species (3.68), followed by the maize (4.84), oak (4.87), apple (4.99), apricot (5.03), peach (5.09), plum (5.17), cherry (5.24), olive (5.26), pepper (5.32), coffea (5.31), tomato (5.46), aubergine (5.48), poplar (5.50), pear (5.52), potato (5.77), lettuce (5.97), basil (6.08), cauliflower (6.10), and pumpkin (6.38).

In the experiment with grapevine aimed to an assessment of the pH to the aerial temperature, it was observed a saddle trend from morning to evening (Figure 2). The value was stable overnight and it depended on the combination between sunlight and aerial temperature. Otherwise during the dark period the pH remained stable. Such rise of acidity in the middle day can be ascribed both to a thermal factor or to a sun irradiance available abundance.

Where regressing the pH and the aerial temperature (Figure 3) the two variables appeared as inversely and closely related with a linear regression coefficient of -0.073±0.003 pH °C^-1 (Eq. A, P<0.0001 in Table 3).

The raw petiole pH was also sensible to divergent conditions in the soil moisture. In the pot experiment, with grapevines from Grenache vineyard (Table 4 and Figure 4) the pH was significantly different in the well watered (pH = 4.29) and in the stressed conditions (4.12). The pH decay was 3.9%, but in terms of ^H+ the increase was 47%.

Where looking at the individual values (Table 5) the relationships direct and inverse appeared significant but veak (P = 0.04): in the direct sense the pH regressed on the Ψstem as +0.05 Mpa^-1, but on averages the increase would be +0.17 Mpa^-1. In the reverse sense, an average reduction of 0.10 unit of pH would signal an increase in water stress about -0.59 Mpa.

The experiment with Arabidopsis thaliana in a phytotrone raised highly significant level (Table 6) showing that in the dark the raw pH did not change in the interval from +18 to +35 °C (b = -0.0027 N.S.; Figure 5; Table 7) while under the light, the regression coefficients were significant and negative, progressing in acidification from a water levels high (-0.0097), to a normal (-0.0127), and to a low (-0.0370) .

The main factors were significant, with the two factor interaction near significant (Table 8). With reference to Table 9 the symbiotic factor was highly significant in all species except kiwi, with maximum effect in cherry (-7%), high effect in olive and hazelnut (-4%), medium effect in corn and blueberry (-3%), minor effect in vine (-2%).

According to the EFSA Report on Collection of Pesticide Application Data in EU12 in 2013 the average number of active ingredients, formulations, products and sprays (spray rounds/spray passes) applied to each of the environmental field crops was very variable among crops. As far as apple, grapes and carrots crops are concerned in Italy, Poland, UK, and Spain the number of fungicides sprays applied were on average 16.67, 12.03 and 2.25 respectively (Table 10).

When looking at the fungal pest occurrences a strong inverse polynomial relationship (R2 = 0.9) was interpolated among the mean pH of 15 species and the number of fungicide sprays (Table 11 and Figure 6).

The apple (pH = 4.99,Table 10) appeared as highly inclined to fungal attacks (NFS = 13.8) while the pear (5.52) was much less damaged by fungal diseases (NFS = 4). As opposite, for a bacterial disease (Table 12) the propensity of the farms to fire blight was 11.3% in pear vs. 0.89% in apple (P<0.0001), but when calculated per hectare the incidence were 22.48% vs. 0.35%, respectively. If one want to express the degree of relative risk, in the two species, we refer to the Odds Ratio (OR) method, then we see that a farm of pear will have and OR of 13 to be concerned with fire blight than a farm of apples. But according to the small size of the two kind of farms (0.45 vs. 2.55 ha for pear and apple, respectively) the OR will grow to 65 when considering a single plant of fruit, apple or pear.

De acidula plantarum natura subtitle could have shaped this paper, when looking at the low pH in leading crops and orchards. The model species Arabidopsis thaliana appeared as a low acidic one: the average raw pH value of the leaves at 25°C was 5.96. This value is near the vacuole pH (5.2) and the Golgi apparatus (6.3-6.8) but quite below the nucleus, plastid stroma and cytoplasm (7.2-7.3) and far below the mitochondria matrix (8.1)5. The first measurement results of pH on finely cut leaves of avocado were published long ago: Haas14 stated that no significant change in the pH of finely cut leaves or juice was noted over a wide pH range in the soil of avocado cultures; however, he did not consider the water status of the avocado trees. The mean observed value in avocado was 5.53 ±0.13, thus it could have been be placed at the 33th 50-1 position, just after pear in the ranking shown in Table 1. When regarding the literature, the raw pH has been ignored, except in the work of the proponents of the Acid Growth Theory 15. A rare observation16 of leaves along a highway regarded the surface pH, which was found to be lower than that of the leaves at a distance from the road, but the pH level was found to increase when dust was deposited on the leaves. In fact, the acidic status of the plant depends on the sugars circulating in the phloem. An increasing level of sugars in sap extracted from non-functional poplars vessels was correlated to a decrease in the pH to around 5.5, while values of 6÷7 were registered in the functional vessels, which only contained traces of sugar17.

In an acidic environment, around 4.9 pH values, young barley leaves equipped by microprobes for [H⁺] and infected by powdery mildew fungus, apoplastic pH showed a rapid increase towards 5.4, then a more stable decrease around 4.8 at 2 h after infection, but at longer-term pH increased at 5.2 values (+6%)18. According the Authors, alkalization process seems to have the general goal to minimize and obstruct fungal growth biochemically.

In a broad scenario of plants the pH of phloem exudate is characteristically alkaline (pH 8.0 to 8.5) and belong from non-reducing sugars (sucrose), amides (glutamine and asparagine), amino acids (glutamate and aspartate) and organic acids19. Acidity of the whole green tissues has longely been utilized in silage operations; methods adopted to improve silage feeding value include rapid wilting and acidification, either by acids products or use of anaerobic inoculants20; however the pH of the raw material is not considered, at most the buffering power is taken into account.

The team of Cornelissen9,10elicited the leaf pH as a new plant trait and explored it as featuring in the carbon or nutrient cycling context in the framework of 92 species (Table 11) which quintile distribution appears quite similar to that of the present 49 species but discarded towards less acidic values (Figure 7).

The authenticity of the pH parameter has been highlighted10, upsetting the myth of the soil pH: as shown in Figure 8 in fresh leaves the leaf pH will rise only of 0.036 pH_soil^-1 (about 0.7%) but in pre-dried herbages the inverse occurred (-0.4%). Important to note the differences in pHs: after pre-drying at 60°C for 48 h and reidratatying, the increase of pH was about 4.3%. This confirm the sense of the relationships pH-temperature-humidity (Table 13).

As to the positive relationships between the pH and the water availability a primary apparent sign of stress is the rise in leaf temperature, an infrared sensed measurement basic for plant-water relations, and specifically for stomatal conductancemonitoring21. In the present work we have commensurate the drop in petiole raw pH to a water stress condition, but chiefly the linear drop was accounted for by the increase of aerial temperature (-0.07 pH °C^-1); in fact in the equations C (Table 3) when the quadratic term was considered, the fit did not improve. It is well known that when the temperature roses over 25°C, the pH declines in force of the normal autoprotolysis - autoionization of the water. But it should be pointed out that the acidic solutions are affected less by this phenomenon than the alkaline ones, and especially when natural buffers are present. In eighteen selected deep eupeptic green solvents (DES, i.e. glycerol, ethylen glycol, lactic acid, malic acid .. etc.) the regression of the pH on the temperature over a range +25 ÷ +60°C was -0.018 ± 0.00622. These values are near our data from Arabidopsis thaliana in normal watering, but in high watering the value was reduced to -0.093 and, especially, in the dark the value was grown to zero, a null autoprotolysis - autoionization mechanism. Our findings highlight that the pH adjustment of the plant to a water-thermal-light environment is an active dynamic and not a passive process, which demand the presence of the light and may be different according the species. Lindenthal et al.23 showed in cucumber that downy mildew initial development shifted down -0.8°C the leaf temperature and this cooling was due to a correlated increase of transpiration rate (r = - 0.762).

An objective reason for the lack of studies is that measurement of the in vivo raw pH of green vegetable organs is not easy and, essentially, this measurement cannot be automated by chemical or (till now) spectroscopy. Instead, several attempts have been made in the liquid background to optimize the ingredients of the nutritive solution. Ferentinos and Albright3 in a hydroponic system, modelled the pH and the electrical conductivity in deeptrough devices by mean of a neural network. Domingues et al.4 developed an automated system to control the pH and concentration of nutrient solution in hydroponic crops. However, no monitoring or responsible feed-back from the plant was considered in terms of pH response. Yu et al.24 made several attempts to predict the so-called apoplastic pH , using agar or bead indicators, measurements of juices, weak acid influxes, ion-selective electrodes and optical probes, but no reliable method was found. Ten years later, Mc Millan et al.25, made new attempts to conduct inferential measurements, solution temperature correction, efficient calibration, noise minimization, location optimization, and predictive maintenance, by taking advantage of smart features and wireless communication. As published in New Frontiers in Plant Science26 the development and properties of genetically encoded pH sensors is a progredient research theme.

Faced with a multifaceted nature of the raw pH acidic wide range, it is possible to ask which lowest common denominator (a large entity) or which greatest common divisor (a small entity) should be considered? In the authors opinion, assuming the pH as a common divisor, in the pseudo-relationships NFS / pH (Figure 6) a common denominator is the propensity towards fungal attack when the pH is more acidic, with vinegrape and apple as driving species, but also the propensity towards bacterial attack when the pH is less acidic, where a clear demonstration outcomes from a balance among the apple vs. pear diseases (Table 12). Maize is a very acidic species; in Table 1 it is positioned as 8th /49, but it is excluded from the Table 10 because the number of fungicide treatments is very variable according the insecticide necessities; in fact, the resistance to fungal attacks is normally higher than what is actually recognized in the intensively cropped orchards and no one or few fungicide treatments are necessary; nevertheless, mycotoxin in cereals is a historical problem, but also an emergency in exceptionally warm and dry summers. Otherwise the occurrence of bacterial diseases in plants is much less frequent than in animals, and one reason could be exactly the acidic nature of the green matrices. Severe cases of bacterial Pseudomonas in Italy concerned the kiwifruit27. Note that the kiwi has a 5.49 pH, ranked as 27th /49, a not highly acidic band. On the other hand the Xylella fastidiosa rouinous attacks28 on Salento olive trees thrive in a intermediate raw pH band (olive is 13 / 49) and moreover the Flavescence doree of grapevine7 is an incursion of phytoplasmas in a very acid environment.

In perspective, the warming from climate change scenarios, could affect a rise in raw acidity of plants, fearing that fungicide sprays could be increased by one per C° degree rise. In the Figure 9 we have hypothesized a very high increase of +1.8°C in the average temperature; the major incidences as percentage of NFS increase, reside in the median 5.5 ÷ 5.9 pH range.

The rise in aerial temperature will grew fungal as well as bacterial disease pressure. In a grapevine district Salinari et al.29have calculated that two more fungicide sprays were necessary under the most negative climate scenario, compared with present management regimes. The increase of presumed 1.8 C° will correspond in the present paper (Table 3, eq. A) at about -0.13 units of raw petiole pH and consequently the elevation in fungicide treatments could be estimated by Eq. D (Table 7) as 13.8 when the actual reference was 12.0. This means that in spite of the the external events regarding the life of the fungi and bacteria out of the crops, it could be introduced an internal category of biological mechanism, leading to increase the acidity circulating in the petiole and leaves, and - unfortunately - this event is favourable to a further increase of fungal diseases. Indeed already now vinegrape are being subjected to an ever increasing problem from fungi. A notable increasing trend of fungicide treatments in France30 is apparent, as the national vineyard district showed 12.4 ± 3.3 NFS in 2013 vs 9.7 ± 2.7 in 2010, which means a rise of +10% per year.