The phrase "acreage data" is correct and usable in written English.
It can be used when referring to information or statistics related to the size of land measured in acres.
Example: "The acreage data collected from the survey will help us understand land use patterns in the region."
Alternatives: "land area information" or "land size statistics".
Using available location-specific crop acreage data, a weighted crop water stress function is computed.
We obtain planted wheat acreage data from CANSIM Canadian socioeconomic database of statistics Canada.
We obtain planted wheat acreage data from the Australian Government Department of Agriculture and Australian wheat prices from the Economic Research Service ERSS) of the USDA.
However, for the total area, timely available acreage data were taken from the FAO and prices from the agricultural ministry website.
Table 1 shows the correlation coefficients between harvested and planted area for those countries where we have obtained planted acreage data from national statistical offices.
Agricultural reports must contain information on the identity, quantity, location, method, date, and other volume and acreage data of restricted-use applications.
The performance of the resulting forecasting tool is validated with ex-post prediction of acreage against historical data.
The correlation coefficients are mostly (except in the case of wheat for the USA) close to unity, indicating that data on harvested acreage can be used as good proxy for planted acreage in our econometric models.
The final model is the one that best explains acreage with the minimum input data requirement.
There is enough data about castles, remodeling, acreage, equerries, swan upping, royal mews and queen's beasts to put even the most ardent monarchist to sleep.
This paper explains methods and data used to forecast acreage of four crops that are particularly important staple commodities in the world, namely wheat, corn, rice, and soybeans for major global producer countries.
