Grape Quality Zoning and Selective Harvesting in Small Vineyards—To Adopt or Not to Adopt
Abstract
:1. Introduction
- Information costs, related to the necessary investments in the technology, including rental fees for specific hardware or machinery;
- Costs involving data processing, specific licence fees, software and hardware products for data analysis;
- Learning costs, mainly due to the additional time required for the farmer to develop management schemes, calibration of the machinery, as well as “lost” opportunity costs due to inefficient use of the precision agriculture technology.
2. Materials and Methods
2.1. Characterisation of the Study Area
2.2. Sampling and Measurement of Vegetative, Yield, and Grape Components
2.3. UAV-Based Image Acquisition and Vegetation Index Analyses
2.4. Data Analysis
2.5. Data Collection and Analysis on the Economic Efficiency of Grape Quality Zoning and Selective Harvesting
3. Results
3.1. The Most Predictive Vegetation Index in 2019 and 2020–TOMAC Site
3.2. The Most Predictive Vegetation Index in 2019 and 2020–ŠEMBER Site
3.3. Economic Efficiency of Grape Quality Zoning and Selective Harvesting
3.3.1. Fixed and Variable Costs of Grape Quality Zoning and Selective Harvesting
3.3.2. Pinot Noir Wine Prices in the Plešivica Subregion
3.3.3. Potential Revenues after Grape Quality Zoning and Selective Harvesting
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Grape Quality Components | ||||
---|---|---|---|---|
2019 (n = 9) | F (1,7) | Sig. | First Cluster (n = 2) | Second Cluster (n = 7) |
M ± SD | M ± SD | |||
Sugar concentration (°Oe) | 8.365 | 0.023 | 91.00 ± 4.24 | 84.71 ± 2.36 |
Total titratable acidity (g/L) | 10.647 | 0.014 | 5.56 ± 0.55 | 6.83 ± 0.47 |
pH | 7.402 | 0.030 | 3.15 ± 0.02 | 3.09 ± 0.03 |
2020 (n = 13) | F (1,11) | Sig. | First cluster (n = 5) | Second cluster (n = 8) |
M ± SD | M ± SD | |||
Sugar concentration (°Oe) | 13.162 | 0.004 | 88.00 ± 3.39 | 81.00 ± 3.38 |
Total titratable acidity (g/L) | 3.703 | 0.081 | 6.86 ± 0.85 | 7.66 ± 0.65 |
pH | 1.776 | 0.210 | 3.09 ± 0.08 | 3.01 ± 0.11 |
Vegetation Index | NDRE | NDVI | OSAVI | ||||||
---|---|---|---|---|---|---|---|---|---|
UAV image acquisition | GS 34 | GS 36 | GS 38 | GS 34 | GS 36 | GS 38 | GS 34 | GS 36 | GS 38 |
2019 (n = 9) | |||||||||
Number of equally classified vines | 4 | 7 | 7 | 7 | 6 | 8 | 6 | 6 | 6 |
Percentage of equally classified vines | 44% | 78% | 78% | 78% | 67% | 89% | 67% | 67% | 67% |
2020 (n = 13) | |||||||||
Number of equally classified vines | 8 | 7 | 11 | 8 | 8 | 8 | 8 | 6 | 8 |
Percentage of equally classified vines | 62% | 54% | 85% | 62% | 62% | 54% | 62% | 46% | 62% |
Analysed Variables | High-Vigour Target Vines (n = 6) | Low-Vigour Target Vines (n = 3) | SS of Differences (Average) Results/Ranks | ||||
---|---|---|---|---|---|---|---|
M ± SD (CV) | Shapiro–Wilk | M ± SD (CV) | Shapiro–Wilk | F | t (7) | Mann–Whitney U | |
Sugar concentration (°Oe) | 84.33 ± 2.34 (2.77) | 0.836 | 89.67 ± 3.79 (4.22) | 0.855 | 1.514 | −2.667 * | |
Total titratable acidity (g/L) | 6.90 ± 0.49 (7.04) | 0.898 | 5.86 ± 0.65 (11.01) | 0.984 | 0.146 | 2.739 * | |
Yield (kg) | 2.71 ± 0.61 (22.56) | 0.860 | 1.56 ± 0.77 (49.32) | 0.896 | 0.184 | 2.448 * |
Analysed Variables | High-Vigour Target Vines (n = 8) | Low-Vigour Target Vines (n = 5) | SS of Differences (Average) Results/Ranks | ||||
---|---|---|---|---|---|---|---|
M ± SD (CV) | Shapiro–Wilk | M ± SD (CV) | Shapiro–Wilk | F | t (11) | Mann–Whitney U | |
Sugar concentration (°Oe) | 81.13 ± 3.52 (4.34) | 0.901 | 87.80 ± 3.63 (4.14) | 0.914 | 0.015 | −3.286 ** | |
Total titratable acidity (g/L) | 7.75 ± 0.62 (8.01) | 0.924 | 6.73 ± 0.70 (10.40) | 0.973 | 0.063 | 2.749 * |
Grape Quality Components | ||||
---|---|---|---|---|
2019 (n = 12) | F (1,10) | Sig. | First Cluster (n = 4) | Second Cluster (n = 8) |
M ± SD | M ± SD | |||
Sugar concentration (°Oe) | 32.502 | 0.000 | 75.75 ± 2.22 | 84.63 ± 2.67 |
Total titratable acidity (g/L) | 10.146 | 0.010 | 9.84 ± 1.08 | 8.02 ± 0.86 |
pH | 26.378 | 0.000 | 2.93 ± 0.02 | 3.07 ± 0.05 |
2020 (n = 22) | F (1,20) | Sig. | First cluster (n = 13) | Second cluster (n = 9) |
M ± SD | M ± SD | |||
Sugar concentration (°Oe) | 40.046 | 0.000 | 84.15 ± 3.02 | 94.22 ± 4.47 |
Total titratable acidity (g/L) | 4.063 | 0.057 | 7.69 ± 1.84 | 6.27 ± 1.23 |
pH | 8.492 | 0.009 | 3.07 ± 0.11 | 3.21 ± 0.11 |
Vegetation Index | NDRE | NDVI | OSAVI | ||||||
---|---|---|---|---|---|---|---|---|---|
UAV image acquisition | GS 34 | GS 36 | GS 38 | GS 34 | GS 36 | GS 38 | GS 34 | GS 36 | GS 38 |
2019 (n = 12) | |||||||||
Number of equally classified vines | 7 | 9 | 6 | 8 | 7 | 6 | 8 | 5 | 5 |
Percentage of equally classified vines | 58% | 75% | 50% | 67% | 58% | 50% | 67% | 42% | 42% |
2020 (n = 22) | |||||||||
Number of equally classified vines | 16 | 15 | 15 | 19 | 15 | 15 | 17 | 16 | 16 |
Percentage of equally classified vines | 73% | 68% | 68% | 86% | 68% | 68% | 77% | 73% | 73% |
Analysed Variables | High-Vigour Target Vines (n = 7) | Low-Vigour Target Vines (n = 5) | SS of Differences (Average) Results/Ranks | ||||
---|---|---|---|---|---|---|---|
M ± SD (CV) | Shapiro–Wilk | M ± SD (CV) | Shapiro–Wilk | F | t (10) | Mann–Whitney U | |
Sugar concentration (°Oe) | 78.29 ± 3.55 (4.53) | 0.729 ** | 86.40 ± 1.34 (1.55) | 0.552 *** | 0.000 ** | ||
Total titratable acidity (g/L) | 9.32 ± 1.07 (11.49) | 0.934 | 7.66 ± 0.83 (10.89) | 0.914 | 0.115 | 2.872 * | |
pH | 2.98 ± 0.07 (2.20) | 0.805 * | 3.08 ± 0.06 (2.07) | 0.818 | 3.000 * | ||
Leaf N content (% on a dry matter basis) | 2.21 ± 0.12 (5.28) | 0.926 | 2.01 ± 0.10 (4.94) | 0.843 | 0.278 | 3.009 * |
Analysed Variables | High-Vigour Target Vines (n = 10) | Low-Vigour Target Vines (n = 12) | SS of Differences (Average) Results/Ranks | ||||
---|---|---|---|---|---|---|---|
M ± SD (CV) | Shapiro–Wilk | M ± SD (CV) | Shapiro–Wilk | F | t (20) | Mann–Whitney U | |
Sugar concentration (°Oe) | 83.40 ± 3.06 (3.67) | 0.974 | 92.33 ± 5.12 (5.55) | 0.925 | 2.532 | −4.831 *** | |
Total titratable acidity (g/L) | 8.05 ± 1.93 (23.93) | 0.768 ** | 6.33 ± 1.12 (17.78) | 0.840 * | 19.000 ** | ||
pH | 3.05 ± 0.11 (3.54) | 0.921 | 3.19 ± 0.11 (3.31) | 0.957 | 0.034 | −3.136 ** | |
Leaf N content (% on a dry matter basis) | 1.98 ± 0.10 (4.99) | 0.978 | 1.86 ± 0.10 (5.14) | 0.903 | 0.053 | 2.914 ** |
Fixed Costs–Equipment Purchase Costs | PRICE (EUR) | |||
---|---|---|---|---|
DJI Phantom 4 Multispectral UAV | 5600.00 | |||
Additional battery | 160.00 | |||
Computer for data processing | 1300.00 | |||
Software Pix4D | 2600.00 | |||
DPO crew mandatory training for drone pilot | 530.00 | |||
Training for the UAV image analysis and data processing (Pix4D fields) | 1000.00 | |||
Insurance and registration of UAV | 1000.00 | |||
TOTAL | 12,190.00 | |||
Variable Human Labour Costs (1 ha) | Time required | EUR/h | Quantity | PRICE (EUR) |
Manual sampling on target vines | 4 | 6.70 | 3 | 80.40 |
Education on the use of UAV | 30 | 6.70 | 1 | 201.00 |
Education on the data processing | 40 | 6.70 | 1 | 268.00 |
UAV data acquisition | 3 | 6.70 | 3 | 60.30 |
Data processing and creation of quality zones | 3 | 6.70 | 3 | 60.30 |
Selective harvesting | 220 | 3.30 | 1 | 726.00 |
Extra costs of selective harvesting | 50 | 3.30 | 1 | 165.00 |
TOTAL | 1561.00 | |||
Variable Service Costs | Area (ha) | EUR/ha | PRICE (EUR) | |
COMMERCIAL SERVICE–UAV image acquisition | 1 | 400.00 | 3 | 1200.00 |
COMMERCIAL SERVICE–data processing | 1 | 400.00 | 3 | 1200.00 |
TOTAL | 2400.00 |
Wine | Market (Retail) Price (EUR/Bottle 0.75 l) |
---|---|
Pinot noir Šember Vučjak * | 20.00 |
Sparkling wine Šember Rose * | 16.00 |
Pinot noir Tomac * | 19.33 |
Sparkling wine Tomac Rose * | 16.67 |
Pinot Noir Wine From the Plešivica Subregion | |
Pinot noir Ledić * | 4.66 |
Pinot noir Filipec * | 10.66 |
Pinot noir Braje * | 11.33 |
Pinot noir Šoškić * | 13.60 |
Average Market Price | 10.07 |
TOMAC Site | ŠEMBER Site | |||
---|---|---|---|---|
Year | 2019 | 2020 | 2019 | 2020 |
Vineyard area (ha) | 0.33 | 0.33 | 0.65 | 0.65 |
Quantity of grapes harvested (kg) | 1800 | 0.900 | 6570 | 4815 |
Amount of produced wine (l) | 1260 | 1330 | 599 | 3371 |
Number of produced bottles (0.75 l) (pcs) | 1680 | 1773 | 6132 | 4494 |
Average bottle price (EUR/bottle 0.75 l) | 10.07 | 10.07 | 10.07 | 10.07 |
Sales revenue without selective harvesting (EUR) | 16,917.60 | 17,854.11 | 61,749.24 | 45,254.58 |
Percentage of low-vigour zone (%) | 61.97 | 54.33 | 49.47 | 47 |
Percentage of high-vigour zone (%) | 38.03 | 45.67 | 50.53 | 53 |
Number of produced bottles from low-vigour zone (pcs) | 1041 | 963 | 3034 | 2112 |
Number of produced bottles from high-vigour zone (pcs) | 639 | 810 | 3098 | 2382 |
Wine price from low-vigour zone (EUR/bottle 0.75 l) | 19.33 | 19.33 | 20 | 20 |
Wine price from high-vigour zone (EUR/bottle 0.75 l) | 16.67 | 16.67 | 16 | 16 |
Total revenue from low-vigour zone (EUR) | 20,122.53 | 18,614.79 | 60,680.00 | 42,240.00 |
Total revenue from high-vigour zone (EUR) | 10,652.13 | 13,502.70 | 49,568.00 | 38,112.00 |
Potential sales revenue after selective harvesting (EUR) | 30,774.66 | 32,117.49 | 110,248.00 | 80,352.00 |
Potential revenue increase after selective harvesting (EUR) | 13,857.06 | 14,263.38 | 48,498.76 | 35,097.42 |
Potential revenue increase after selective harvesting (%) | 45.03 | 44.41 | 43.99 | 43.68 |
TOMAC Site | ||||||||
---|---|---|---|---|---|---|---|---|
S1 | S2 | |||||||
A1 | A2 | Differential Amount | A2 Is: | A1 | A2 | Differential Amount | A2 Is: | |
Sales revenue (EUR) | 16,917.60 | 30,774.66 | 13,857.06 | higher | 16,917.60 | 30,774.66 | 13,857.06 | higher |
Variable costs (EUR) | 0.00 | 829.36 | 829.36 | higher | 0.00 | 2694.03 | 2694.03 | higher |
Fixed costs (EUR) | 0.00 | 12,190.00 | 12,190.00 | higher | 0.00 | 0.00 | 0.00 | equal |
Profit (EUR) | 16,917.60 | 17,755.30 | 837.70 | higher | 16,917.60 | 28,080.63 | 11,163.03 | higher |
ŠEMBER Site | ||||||||
S1 | S2 | |||||||
A1 | A2 | Differential Amount | A2 Is: | A1 | A2 | Differential Amount | A2 Is: | |
Sales revenue (EUR) | 61,749.24 | 110,248.00 | 48,498.76 | higher | 61,749.24 | 110,248.00 | 48,498.76 | higher |
Variable costs (EUR) | 0.00 | 1178.80 | 1178.80 | higher | 0.00 | 2979.15 | 2979.15 | higher |
Fixed costs (EUR) | 0.00 | 12,190.00 | 12,190.00 | higher | 0.00 | 0.00 | 0.00 | equal |
Profit (EUR) | 61,749.24 | 96,879.20 | 35,129.96 | higher | 61,749.24 | 107,268.85 | 45,519.61 | higher |
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Rendulić Jelušić, I.; Šakić Bobić, B.; Grgić, Z.; Žiković, S.; Osrečak, M.; Puhelek, I.; Anić, M.; Karoglan, M. Grape Quality Zoning and Selective Harvesting in Small Vineyards—To Adopt or Not to Adopt. Agriculture 2022, 12, 852. https://doi.org/10.3390/agriculture12060852
Rendulić Jelušić I, Šakić Bobić B, Grgić Z, Žiković S, Osrečak M, Puhelek I, Anić M, Karoglan M. Grape Quality Zoning and Selective Harvesting in Small Vineyards—To Adopt or Not to Adopt. Agriculture. 2022; 12(6):852. https://doi.org/10.3390/agriculture12060852
Chicago/Turabian StyleRendulić Jelušić, Ivana, Branka Šakić Bobić, Zoran Grgić, Saša Žiković, Mirela Osrečak, Ivana Puhelek, Marina Anić, and Marko Karoglan. 2022. "Grape Quality Zoning and Selective Harvesting in Small Vineyards—To Adopt or Not to Adopt" Agriculture 12, no. 6: 852. https://doi.org/10.3390/agriculture12060852