Precision farming methods, especially crop mapping or monitoring weather conditions, are perfect not only for agricultural commodities important for global food security. They are also being successfully applied to citrus crops, for example. This is particularly true of oranges, whose juice is a commodity traded on global exchanges. Source: https://www.investing.com/commodities/orange-juice-streaming-chart?GL_Ad_ID=647257167588&GL_Campaign_ID=19652104510https://www.investing.com/commodities/orange-juice-streaming-chart?utm_source=google&GL_Ad_ID=647257167588&GL_Campaign_ID=19652104510&ISP=1 Crop mapping and monitoring weather […]
Precision farming methods, especially crop mapping or monitoring weather conditions, are perfect not only for agricultural commodities important for global food security. They are also being successfully applied to citrus crops, for example. This is particularly true of oranges, whose juice is a commodity traded on global exchanges.
Crop mapping and monitoring weather conditions provide key information for decision-making in agricultural applications, such as yield prediction, and information enabling price modeling.
Machine learning is being used in this case to predict the value of crop vegetation indices, and, ultimately, in the process of estimating orange juice prices.
Currently, the world’s largest orange-growing regions are located in several countries:
Brazil: Capao Bonito, Registro, Ribeirao Preto, Frutal, Limeira da Oeste, Limeira, Bebedouro, Araraquqra
USA: California – Borrego region, San Joaquin region , Florida – Hendra region, DeSoto region
China: Changsha, Ganzhou, Xiamen, Zhangzhou, Jiangmen
Spain – Valencia region
Italy (Sicily) – Catania region
The role and importance of monitoring planting areas.
The dynamics of orange crop planting areas are related to a number of socioeconomic measures, such as food supply, income, and crop insurance. For the quality of decision-making, it is particularly important to track current and forecast weather conditions in growing regions and compare them with „normal” conditions, as described by multi-year averages. Below is data for one of the main orange-growing locations in Brazil.
CAPAO BONITO Brazil – State of São Paulo
Latitude: -24.004
Longitude: -48.3393
24° 0′ 14″ South, 48° 20′ 21″ West
The growing season for orange crops typically lasts from August to November in this region, although it can vary somewhat depending on conditions from season to season.
Current and forecast weather conditions against their norms:
Precipitation [mm] – the most significant variable from the point of view of crop yield, with a decisive impact on the vegetation index.
Maximum temperature.
Minimum temperature.
Average wind speed.
Cloudiness.
Depending on cloud cover, knowing the exact geographic location of a particular growing region, the amount of energy of short-wave solar radiation reaching the earth’s surface is estimated. Short-wave radiation includes visible light and ultraviolet radiation. This parameter is the most important for the process of photosynthesis.
Forecasting vegetation indices.
Vegetation indices are closely related to weather conditions in the growing region. In particular, with the cumulative value of precipitation and the amount of solar radiation reaching the ground surface, as well as with humidity and temperature.
The forecast values of the indicators depend strongly on the forecasts of the weather factors themselves and the forecasts of the amount of radiation.
Based on historical data, a model of the indicator’s relationships with these factors is created, and the strength of these relationships is determined using machine learning.
The tool used in the process of determining the strength of relationships can be, for example, neural networks.
Other important factors determining fruit quality and yield.
In this case, the subject of separate considerations should be the threats of crop-damaging diseases and pests and growers’ ability to counter them, as well as conditions related to crop fertilization.
All of the above-mentioned factors constitute a set of variables relevant to the process of modeling orange juice prices.
