Abstract
The management of symbiotic Microbial Biota (MB) in the soil as agents that promote the yield and health of crops, is aimed at inducing modifications of the phenotype of plants, both over and under the ground. It is here shown, in
Author Contributions
Copyright© 2018
Masoero Giorgio, et al.
License
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Introduction
A credible increase of 50% in the world feed and food necessities can be expected at the end of the next thirty years Experiments with AM may be divided into two categories, that is, practical and scientific In a first field experiment with maize fertilized by a Micosat F® complex microbial consortium The aim of the present study has been to ascertain whether the decrease in the varied raw pH in leaves is due to AM or to a whole complex of a microbial consortium, and to assess how AM can be considered effective modifier agents of the Two rapid methods: the measurement of the raw pH, according to Masoero and Giovannetti
Materials And Methods
Three categories were considered: i) MB from finely ground cultivated MB from finely ground cultivated The leaves were harvested after 66 d and measured to establish the raw pH of the leaves by means of direct contact of the split central vein with a combined plastic-glass Double Pore Knick® electrode (Hamilton, Reno, USA) using an XSpH 70 pH meter (Giorgio Bormac S.r.l., Carpi, Italy). The whole leaves from each of the 16 theses were chopped and dried at 60 °C to a constant weight, air-equilibrated, ground in a Cyclotec mill and stored for later analysis by means of NIRS. The ground leaves were repeatedly examined (three scans) with a Spectrum IdentiCheckTM FT-NIR/MIR system (Perkin-Elmer, Beaconsfield, Buck, England) and the chemical composition was predicted via NIRS, using equations that were established on twelve different forage crops, as reported in Tassone et al. A smart NIR miniaturized web-based wireless spectrophotometer, SCIO version 1.2 (Consumer Physics, Tel Aviv, Israel), with a 740-1070 nm range, was used to scan the fresh leaves on the upper foliar tinge (one scan) and the ground dry matrices (10 replicates). An ANOVA one-way model was used to fit the effect of the categories or of the 16 theses using PROC GLM from SAS-STAT 9.0 software (SAS Institute, Inc., Cary, NC, USA), while the Tukey test was used to adjust for LSMEANS PDIFF. Univariate analyses were conducted on the values of the raw pH and on the predicted composition. The means values of the 14 variables pertaining to the 16 theses plus the total foliar dry weight and percentage, were then related to the foliar pH, as a key-variable, using a standard Partial Least Square (PLS) model (StatBox 6.5 v., Grimmer Logiciels, Paris, France) which allows two latent variables to be achieved; in this way, it was possible to identify the variables that were favoured or contrasted by the raw foliar pH variations among the theses. A categorical discrimination of the three main groups of the fresh and dried leaves was performed by means of chemometrics of the 331-point spectra using the SCIO Lab proprietary software, based on AKA (Also Known As), the confusion matrix, without any mathematical pre-treatment of the spectra.
AM -
AM01
AM -
AM02
AM -
AM03
AM -
AM04
AM -
AM05
AM -
AM06
AM -
AM07
AM -
AM08
AM -
AM09
AM -
AM10
AM -
AM11
AM -
AM12
AM -
AM13
MB - Microbial Biota
MB1
Micosat F© (CCS-Aosta, Quart, Italy)
MB - Microbial Biota
MB2
MycUp© (Symborg, Murcia, Spain)
C- Control not inoculated
C
Results
The raw pH of the leaves appeared as a very narrow-distributed variable, which was characterized by a variation coefficient of 3.8% ( The normal mean value of 5.18±0.03 in the leaves from the C non-inoculated plants was significantly decreased to 5.10±0.02 in the MB category (-1.5%, P=0.0336), and decreased to a value of 5.00±0.01 in the AM category (-3.5%, P<0.001). Moreover, the AM As far as the biofertilizers are concerned, MB1 (-1.1%) was more acidifying than MB2 (-2.0%), and the AM were scaled according to three gradients of acidity: the most acidic strains, that is, below -4%, were the AM01, AM13, AM05, AM02 and AM08 strains. The weight of the leaves harvested from the plants was much more reduced in the non-inoculated Control than in all other theses ( As can be observed in The PLS standard model ( In general, the discriminations of the three categories when the SCIO instrument was used were highly significant (
LSMeans
5.18
5.10
5.00
0.0336
<.0001
0.0002
SE ±
0.03
0.02
0.01
RMSE
0.19
R2
0.12
Thesis
pH
Dry Mass g
Hemicellulose %
NDF digestible %
Ether Extr. %
ADF, %
Crop Maturity Index
Crude Fiber %
Nitrogen Free Extract %
AM01
4.93b
21.1
7.9
29.1
1.4
46.0
2.3
24.2
47.0
AM02
4.96b
14.3
7.1
28.9
1.7
45.5
2.1
24.6
42.5
AM03
4.97b
14.3
8.2
27.0
1.4
43.7
2.0
25.0
45.9
AM04
5.03ab
9.0
8.8
27.9
1.5
48.3
2.1
24.3
45.4
AM05
4.95b
16.0
6.1
27.4
1.7
48.8
2.4
26.5
42.7
AM06
5.08ab
17.2
6.4
27.3
1.5
45.8
2.1
24.0
45.6
AM07
5.04ab
16.9
4.8
27.7
1.4
46.9
2.2
23.9
43.9
AM08
4.97b
17.6
5.5
29.2
1.5
46.8
2.0
23.7
43.5
AM09
5.03ab
15.7
8.3
27.4
1.6
44.6
1.9
20.3
46.9
AM10
5.04ab
8.8
5.6
30.1
1.7
43.2
1.5
22.2
45.7
AM11
5.01b
15.5
5.3
29.1
1.5
47.0
2.0
23.7
43.3
AM12
5.06ab
15.5
5.4
27.7
1.5
47.4
2.3
26.4
43.3
AM13
4.94b
18.4
7.9
27.1
1.6
47.9
2.2
25.9
43.7
MB1
5.08a
12.1
7.4
28.4
1.4
42.6
1.9
20.2
46.3
MB2
5.12a
14.7
8.4
28.3
1.4
44.1
1.9
21.1
46.7
C
5.18a
6.7
5.6
25.0
1.3
45.5
2.3
25.8
43.9
MB/C
-1%
99%
42%
13%
10%
-5%
-18%
-20%
6%
Prob
0.03
-
0.01
0.00
0.37
0.24
0.01
0.00
0.019
AM/C%
-3%
129%
20%
12%
18%
2%
-8%
-6%
1%
Prob
<.0001
-
0.20
<.00
0.00
0.94
0.13
0.34
0.80
Thesis
Ash %
NDF non dig. %
NDF digestibility %
ADL %
NDF %
Crude Protein %
Cellulose %
Dry Matter %£
AM01
8.0
70.4
29.6
42.3
6.3
54.5
6.7
22.1
32.6
AM14
8.7
72.0
28.0
47.3
8.8
50.9
9.1
19.9
30.3
AM06
7.6
71.1
28.9
45.6
8.8
49.6
8.7
18.2
28.9
AM02
10.1
72.5
27.5
52.3
8.4
51.1
10.1
17.5
29.7
AM09
9.5
71.6
28.4
44.6
8.4
51.4
9.3
19.1
28.9
AM03
9.1
71.8
28.2
43.1
7.9
51.2
9.6
22.4
29.4
AM12
9.6
71.4
28.6
44.1
8.5
51.6
9.3
18.8
29.7
AM10
10.3
72.2
27.8
44.9
7.8
52.2
11.5
24.5
29.3
AM05
7.3
72.0
28.0
46.1
8.8
54.1
9.8
22.4
29.0
AM11
10.8
76.6
23.4
52.9
8.2
50.4
9.5
19.7
28.8
AM08
8.5
71.1
28.9
40.3
7.0
52.4
8.3
20.6
31.0
AM13
7.7
69.6
30.4
43.3
9.5
52.1
8.3
21.0
33.0
AM07
8.6
70.9
29.1
43.7
8.0
53.3
9.6
22.2
30.2
MB1
10.5
72.9
27.1
49.4
7.3
49.3
10.5
23.8
29.4
MB2
10.3
72.7
27.3
47.7
6.8
53.0
10.4
22.9
30.8
C
7.1
70.0
30.0
42.3
7.5
52.7
7.1
23.6
33.6
MB/C%
46%
4%
-10%
15%
-7%
-3%
48%
-1%
-10%
Prob
0.00
0.06
0.07
0.13
0.37
0.57
0.01
0.99
-
AM/C%
25%
3%
-6%
7%
9%
-1%
30%
-12%
-11%
Prob
0.03
0.12
0.12
0.48
0.78
0.89
0.03
0.03
-
Arbuscular Mycorrhizae (AM)
22%
31%
96%
30%
48%
94%
Microbial Biota (MB)
5%
59%
2%
5%
51%
3%
Control (C)
74%
11%
1%
65%
0%
1%
Prob. Diagonal elements
P
< 0.0001
< 0.0001
< 0.0001
< 0.0001
< 0.0001
< 0.0001
Discussion
A luxuriating effect has been displayed in foliar development. A meta-analysis of the field studies on the responses of wheat to AM has highlighted that field AM inoculation can be proposed as an effective agronomic practice for wheat production As expected, a more juvenile ontogenic status emerged for the leaves of inoculated plants but graded among the inocula types. Claps et al. Other AA have conducted experiments on AM at more mature stages, but hay and silages have rarely been studied. Uzun As far as maize forage is concerned, Sibi et al. In our short modification experiment, low pH steadily favoured the dry mass weight and, to a lesser extent, the hemicellulose, digestible NDF and the ether extract contents of the leaves. If the raw pH is a real key-variable, the modifier direction in The field surveys of AM communities over a wide range of soil pH suggest that it is also the major driving force in structuring these communities It was found, in the microcosm experiments The direct NIRS discrimination of bio-fertilized crops is rare. A first work on
Conclusion
In a meta-analysis concerning nearly half a million species x sites worldwide on twenty-one plant traits, Moles et al. In this work, the fall out of the raw pH responded as a simple sign of AM inoculation and activities. However, various responses were observed for the same The vibrational spectroscopy of leaves can be used to rapidly classify the outcomes linked to symbiotic agents, and a smart network can be used to capitalize on useful information in an NIRS leaf data-base. From a practical point of view, it may be recommended to monitor raw pH for traceability purposes in an AM multiplication framework. Pursuing the study of pH from a plant-to-soil point of view is better than the inverse, and each search conducted to connect the microbial soil fingerprint (hay-litter-bags The authors wish to thank the Fondazione CRT, Torino – Italy, for the financial support to the scientific activities of the “Accademia di Agricoltura di Torino”.