Bulletin

CropWatch bulletin
ArgentinaMain producing and exporting countries

Authors: 超级管理员 | Edit: Miao

The monitoring period covers the main growing season of winter crops, as well as the sowing of Maize and Rice (Figure X0). Rainfall shows a negative anomaly of almost 4 %. Temperature was 0.7°below average and RADPAR was reduced 7.7 % compared to average conditions. Compared with the recent five years average, however, BIOMSS showed a 16.3 % increase.

The spatial distribution of NDVI profiles shows a pattern of high increases at the end of the reporting period in south Entre Rios Province (Figure X1). Late positive anomalies occur mainly in South West Buenos Aires province and the Central Pampas. Below average NDVI occurs mostly in the western Pampas.

CropWatch subdivides Argentina into eight agro-ecological zones (AEZ) based on cropping systems, climatic zones, and topography; they are identified by numbers in the NDVI profiles map (Figure X1). Only four of them are found to be relevant for crops cultivation: the Chaco, Mesopotamia, the Pampas, and the Subtropical highlands for which the crop conditions will be discussed with some detail in this section.

The four zones showed different behavior in RAIN. High positive anomalies were observed for Subtropical highlands (+119 %), and negative anomalies were observed in Mesopotamia (-10 %), Chaco (-4 %) and Pampas (-3 %). TEMP showed negative anomalies for the four zones: Subtropical highlands (-1.2℃), Chaco (-1.2℃), Mesopotamia (-0.8℃) and Pampas (-0.3℃). Significant negative anomalies were observed for RADPAR in Subtropical highlands (-10 %), Chaco (-9 %), Pampas (-8 %) and Mesopotamia (-6 %). The four regions showed increases of BIOMSS above the recent 5YA, especially in the Subtropical highlands (+122 %) in relation to high amounts of RAIN observed there. For the other zones, BIOMSS rose just 14 % for Chaco, 10 % for the Pampas, and 6 % for Mesopotamia.

The behaviour of the cropped arable land fraction indicator (CALF) differed between the Subtropical highlands (-11 %) and Pampas (-1 %) with decreases and the  Chaco (+7 %) and Mesopotamia (+1 %) where increases took place.

NDVI development graphs for the whole country show changes from below average crop condition at the beginning of the reporting period to positive anomalies at the end (Figure X2). The pattern was also observed in the zones of Chaco and Mesopotamia, while the Pampas showed a change from near average values at the beginning to positive anomalies at the end of the period (Figure X3.a, b and c). During most of the period the Subtropical highlands showed negative anomalies which, however, tended to reduce at the end of the reporting period (Figure X3.d).

Maximum VCI showed a west-east gradient with low values in East Pampas and Chaco and high values in the East (Figure X4). Considering subregions, Maximum VCI was high for Pampas (0.79) and Mesopotamia (0.77) but lower for the Chaco (0.67) and Subtropical highlands (0.52).

Compared with 2017, CropWatch estimates that production is down for Soybean (8%) , Maize (6%), Rice (5%) and Wheat (4%), due mostly to marked reduction in yield: Soybean -14 % and Maize -15%.

Figure x Crop calendar of Argentina

Figure.X0. Argentina’s crop condition, July-October 2018.

Figure.X1 Spatial distribution of NDVI profiles


Figure.X2. Crop condition development graph based on NDVI_Argentina

Figure.X3.a. Crop condition development graph based on NDVI_Pampas

Figure.X3.b. Crop condition development graph based on NDVI_Chaco

Figure.X.3.c Crop condition development graph based on NDVI_Mesopotamia

Figure.X.3.d. Crop condition development graph based on NDVI_Subtropical highlands

Figure.X4 Maximum VCI


Table X0. Argentina’s agroclimatic indicators by sub‐national regions, current season's values and departure from 15YA, July-October 2018.

Table X1. Argentina’s agronomic indicators by sub‐national regions, current season's values and departure from 15YA, July-October 2018.


Table X2. CropWatch‐estimated maize, rice, wheat and soybean production for Argentina in 2018 (thousand tons).