COMPARATIVE EVALUATION OF NEW SYSTEMS TO PROTECT AND FORECAST CROP YIELDS BASED ON NDVI DATA

The purpose of the study is to evaluate the effectiveness of the use of a new biopesticide and develop a predictive model for crop yields based on Earth remote sensing data. Tasks – acquisition, processing and analysis of retrospective data and current seasonal NDVI values for spring barley and winter wheat; comparative evaluation of the action of a new biological plant protection product (PPP) of the protective and stimulating action "Nigor ++"; numerical assessment of the long-term correlation relationship between the maximum values of NDVI and crop yields and the conclusion about the possibility of using the vegetation index as an indicator of crop yields with the development of an adequate regression equation under the conditions of the experimental production farm of the Orel State Agrarian University. Field studies for the 2021 season were carried out at the pilot production sites of the Orel State Agrarian University. Soil type is gray forest. Crops are winter wheat Moskovskaya 39 (crop area 48.1 ha), spring barley Raushan (crop area – 17.4 ha). Sowing of winter wheat was carried out on 09/10/2020, spring barley – on 05/07/2021 with seeds treated with the Scarlet fungicide. The dynamics of changes in the NDVI index for crops treated with a new biological product is 10–15 days ahead of the control, up to the heading phase, and the maximum values of the vegetation index of the experimental crops are 5–6 % higher than the control plots. The average long-term correlation coefficients between yield and peak NDVI values are 0.79 for winter wheat and 0.75 for spring barley, which confirms the reliability of using the maximum seasonal values of the vegetation index as a controlled variable in the predictive yield model. The error in assessing the yield of crops, made using the proposed predictive models, relative to the actual yield values does not exceed 6.7 %. This gives the right to recommend the obtained models for planning production and economic tasks in the experimental production facility of the university.

Authors

Publication Details

Journal
Bulletin of KSAU
Published
2024-12-24
DOI
https://doi.org/10.36718/1819-4036-2023-1-69-79
Citations
1
Primary Topic
Agricultural Productivity and Crop Improvement
Type
article
Field-Weighted Citation Impact
0.57
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

COMPARATIVE EVALUATION OF NEW SYSTEMS TO PROTECT AND FORECAST CROP YIELDS BASED ON NDVI DATA

N.E. Pavlovskaya, Sergey Rodimcev
1 citations
Bulletin of KSAU
Agricultural Productivity and Crop Improvement
0.57
article

COMPARATIVE EVALUATION OF NEW SYSTEMS TO PROTECT AND FORECAST CROP YIELDS BASED ON NDVI DATA

N.E. Pavlovskaya, Sergey Rodimcev
article en
1 citations

Abstract

The purpose of the study is to evaluate the effectiveness of the use of a new biopesticide and develop a predictive model for crop yields based on Earth remote sensing data. Tasks – acquisition, processing and analysis of retrospective data and current seasonal NDVI values for spring barley and winter wheat; comparative evaluation of the action of a new biological plant protection product (PPP) of the protective and stimulating action "Nigor ++"; numerical assessment of the long-term correlation relationship between the maximum values of NDVI and crop yields and the conclusion about the possibility of using the vegetation index as an indicator of crop yields with the development of an adequate regression equation under the conditions of the experimental production farm of the Orel State Agrarian University. Field studies for the 2021 season were carried out at the pilot production sites of the Orel State Agrarian University. Soil type is gray forest. Crops are winter wheat Moskovskaya 39 (crop area 48.1 ha), spring barley Raushan (crop area – 17.4 ha). Sowing of winter wheat was carried out on 09/10/2020, spring barley – on 05/07/2021 with seeds treated with the Scarlet fungicide. The dynamics of changes in the NDVI index for crops treated with a new biological product is 10–15 days ahead of the control, up to the heading phase, and the maximum values of the vegetation index of the experimental crops are 5–6 % higher than the control plots. The average long-term correlation coefficients between yield and peak NDVI values are 0.79 for winter wheat and 0.75 for spring barley, which confirms the reliability of using the maximum seasonal values of the vegetation index as a controlled variable in the predictive yield model. The error in assessing the yield of crops, made using the proposed predictive models, relative to the actual yield values does not exceed 6.7 %. This gives the right to recommend the obtained models for planning production and economic tasks in the experimental production facility of the university.

Bulletin of KSAUVol. 0(1)
Life in Land
Openalex Percentile: Top 27%
Agricultural Productivity and Crop Improvement
0.57
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.