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Methodical approach to assessing risks of possible yield losses during implementation of agricultural technologies
- Authors: Yakushev V.V.1, Voropayev V.V.1, Lomakin V.S.1
-
Affiliations:
- Agrophysical Research Institute
- Issue: Vol 17, No 2 (2022)
- Pages: 232-244
- Section: Risk management in agriculture
- URL: https://agrojournal.rudn.ru/agronomy/article/view/19769
- DOI: https://doi.org/10.22363/2312-797X-2022-17-2-232-244
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Abstract
The methods of risk assessment and decision-making in the management of agrotechnology were studied in order to develop a methodical approach to assessing the risks of possible yield losses in case of deviations from the project parameters in the implementation of agrotechnology. The study uses methods of analyzing information from the subject area of risk management in the management of agricultural technology. A registry of possible deviations in the design values of process parameters in the implementation of agricultural technologies has been compiled. A new approach has been developed to assess the risks of possible yield losses in the implementation of agrotechnology with deviations in process parameters from project values. Using the proposed approach will provide an automated ranking of options for decisions on the degree of risk of possible crop failure in case of deviations from the designed values, which will facilitate the transition to intelligent management of crop production.
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Table 1. Risk Matrix
Probability | Probability description | Scale of effect | s |
| ||
1 | 2 | 3 | 4 | 5 | ||
Very low | Low | Medium | High | Very high | ||
5 | Certain | В | В | В | К | К |
4 | Almost certain | С | С | В | К | К |
3 | Probable | М | С | С | В | В |
2 | Probably not | М | М | С | С | С |
1 | Almost certainly not | М | М | М | М | М |
Note. М — low risk; C — m edium risk; B — h igh risk; K — v ery high risk.
Table 2. Scale of effects of subjective errors in the management of technological processes as part of agricultural technology
Technological process | Description of possible error | Possible yield losses and other error effects |
1 | 2 | 3 |
Deep tillage | Dry soil | Drying and overcompaction of soil causes an increase in its resistance to plow by 150 % (+ 11…16 l/ha of additional diesel fuel). When the soil dries to a depth of 30 cm, it makes no sense to count on a high yield. |
Deep tillage | Waterlogged soil | Waterlogged soil is difficult to cultivate. During processing, huge layers are formed, which quickly dry out, it ultimately leads to an increase in evaporation surface area. Probability of yield reduction is by 1.7—1.8 times |
Violation of agrotechnical requirements (terms of plowing or pre-sowing treatment) | The delay in pre-sowing tillage hinders sowing. In case of violation of the optimal sowing time, which lasts for 5—7 days after the onset of physical ripeness of the soil, yield loss per one day of sowing delay averages 0.8 c/ha for Belarus | |
Pre-sowing tillage | Insufficient field alignment | Yield reduction up to 30 % due to sifting and failures in operation modes of sowing and planting machines |
Basic fertilization | Overdosing | Decrease in grain yields due to lodging up to –43 %, in row crops — decrease in yield due to the spread of diseases |
Underdosing | Lack of nitrogen leads to a decrease in grain yields up to 60 %. The lack of calcium stops the vegetation of plants. For row crops, when the dose is underestimated, the losses are in the range of 30…56 % | |
Sowing (planting) | Ahead of the optimal period | Losses can be up to 5 % |
Missing the optimal time | Barley: 20 days up to –30 %; oats: for 20 days up to –20 %; spring wheat: for 10…12 days: up to –23…27 %. Losses of row crops can reach 1.5…2 % for each day of delay | |
Overseeding | All indicators of crop structure are reduced — productive tillering, number of grains and mass of grains per ear, weight of 1000 grains | |
Crop tending | Deviation from optimal timing of events | Yield losses are estimated at 15…17 % |
Harvesting | Harvesting unripe crops | There are losses, but they are not estimated, crop quality is significantly reduced |
Harvesting overripe crops | Harvesting delay by 10…14 days leads to yield loss up to 60 %; every day of overstay, grain yield decreases by 1—2 %, and under adverse weather conditions, it decreases significantly. | |
Preparing for storage | Violation of the modes of sorting, drying, cooling | Reduced quality of finished products |
Table 3. Risk levels of yield losses as an effect of subjective errors in the management of agricultural technological processes
Technological process | Description of possible error | Scale of effects | Probability of an error | Risk level of yield losses due to management error |
1 | 2 | 3 | 4 | 5 |
Deep tillage | Dry soil | Very high (5) | Certain (5) | Very high (В) |
Waterlogged soil | Very high (5) | Certain (5) | Very high (В) | |
Violation of agrotechnical requirements (terms of plowing or pre-sowing treatment) | Medium (3) | Almost certain (4) | Medium (С) | |
Pre-sowing tillage | Insufficient field alignment | Medium (3) | Probable (3) | Medium (С) |
Basic fertilization | Overdosing | Medium (3) | Probably not (2) | Medium (С) |
Underdosing | Low (2) | Almost certain (4) | Low (М) | |
Sowing (planting) | Ahead of the optimal period | Low (2) | Probably not (2) | Low (М) |
Missing the optimal time | Medium (3) | Almost certain (4) | Medium (С) | |
Overseeding | Very low (1) | Probably not (2) | Low (М) | |
Crop tending | Deviation from optimal timing of events | Medium (3) | Probable (3) | Medium (С) |
Harvesting | Harvesting unripe crops | High (4) | Probably not (2) | Medium (С) |
Harvesting overripe crops | High (4) | Probable (3) | High (В) | |
Preparing for storage | Violation of the modes of sorting, drying, cooling. | Medium (3) | Probable (3) | Medium (С) |
About the authors
Vyacheslav V. Yakushev
Agrophysical Research Institute
Email: mail@agrophys.com
ORCID iD: 0000-0001-8434-5580
Doctor of Agricultural Sciences, Corresponding Member of the Russian Academy of Sciences, Head of the Laboratory for Information Support of Precision Farming
14 Grazhdansky av., St. Petersburg, Russian FederationValeriy V. Voropayev
Agrophysical Research Institute
Email: valeriy.voropaev.70@mail.ru
ORCID iD: 0000-0002-7537-4862
Candidate of Agricultural Sciences, Leading Researcher, Laboratory for Information Support of Precision Farming
14 Grazhdansky av., St. Petersburg, Russian FederationVladimir S. Lomakin
Agrophysical Research Institute
Author for correspondence.
Email: lomakinv2014@yandex.ru
ORCID iD: 0000-0003-2051-3877
Candidate of Technical Sciences, Leading Engineer, Laboratory for Information Support of Precision Farming
14 Grazhdansky av., St. Petersburg, Russian FederationReferences
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