Crop Yield Forecasting

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Annex B4.4. Concepts and definitions used by the CEC I Annual and perennial crops 1. Annual crops are those that are planted and harvested during the same production season. 2. Perennial crops need not be replanted after each harvest. II Annual crops: definition, classification and specific recommendations 1. Grains Grains refer to the harvested produce of cereals, pulses and oil-bearing crops, excluding crops harvested or used green for forage, silage and grazing and in the case of maize harvested green, also for food. 2. Cereals (e.g. white maize, yellow maize, sorghum, wheat, barley and oats) 2.1 General Cereals are annual plants, generally of the gramineous family, which yield grains used for food, feed, seed and industrial purposes. It is recommended that the definition of “cereals” be limited to crops harvested for dry grain only, therefore excluding crops harvested or used green for forage, silage, grazing, etc; and, in the case of maize harvested green, also for food. 2.2 Definition Cereals are defined as annual plants of the gramineous family which yield dry grains used for food, feed, seed and industrial purposes. 3. Pulses (e.g. dry beans) 3.1 General Pulses are annual leguminous plants yielding seeds used for food, feed and seed purposes. In addition to their value as food and feed, pulses are also important in cropping systems for their ability to produce nitrogen and therefore increase soil fertility. The definition “pulses” should be limited to crops harvested for dry seeds only. 3.2 Definition Pulses are defined as annual plants of the leguminous family yielding dry seeds used for food, feed, seed and industrial purposes. 4. Oilseeds (e.g. sunflower seed, soybeans, groundnuts and canola) 4.1 General Oil crops are annual plants whose seeds or fruit are used mainly for extraction of culinary and industrial oils. The definition of “oilseeds” should be limited to crops harvested for dry seeds only, excluding crops harvested green and used for food or feed, or used for grazing and green manure. The production of oilseeds should always relate to the quantities actually harvested, irrespective of their use after harvest. Crop Yield Forecasting: Methodological and Institutional Aspects 209
4.2 Definition Oilseeds are defined as dry seeds harvested from annual oil-bearing crops used for food, feed, seed or industrial purposes. III Additional definitions: 1. Farming unit (farm/farming operation) 1.1 General A farming unit consists of one or more farms, holdings or pieces of land (whether adjacent or not), operated as a single unit and situated within the same magisterial district/province. A farming unit is a unit on which cultivation is carried out for both commercial and non-commercial purposes, in the open air or under cover (Agricultural survey 1996). 1.2 Definition A farming unit consists of one or more farms, holdings or areas of land (whether adjacent or not), farmed on as a single unit and situated within the same province. It includes land rented from others, the farmstead and other buildings, cropland, pasture, veld, wasteland and dams, and excludes land leased to others. 2. Commercial farmer 2.1 General The commercial farmer earns an ongoing and primary revenue from his/her farming business, which forms the major source of income for the family. He/she has access to the technical, financial and managerial instruments necessary to utilize the global market potential. 2.2 Definition A commercial farmer is a person who produces agricultural products intended for the market. 3. Non-Commercial farmer 3.1 General The Non-commercial farmer earns very little from his/her farming activities. The crops/livestock generated from the farming activities are merely for home consumption. The surpluses brought to the market constitute a small percentage and usually generate very low incomes. Non-commercial farmers are alienated from the market due to technical, financial and managerial barriers. The family must look for other non-farming ways to generate income. Eventually, the Non-commercial farmer will earn more from the non-farming activities and leave the farming business. This is a farming operation in which output is produced primarily for consumption 210 Crop Yield Forecasting: Methodological and Institutional Aspects
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Crop Yield Forecasting: Methodologi
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This publication was prepared with
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Contents Acknowledgements 9 Preface
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3. Linking up with crop production
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ANNEXES............................
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10 Crop Yield Forecasting: Methodol
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org) monitors current year conditio
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eference dataset, whereas actors of
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Remaining challenges The main unkno
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DAFF DBMS DEM DG-AGRI DMN DMP DPO D
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RMSE RS RSAC RSS RVI SACOTA SAFEX S
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FIGURE 4.10 FIGURE 4.11 FIGURE 4.12
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24 Crop Yield Forecasting: Methodol
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FIGURE 1.1 B-CGMS descriptive flowc
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the CGMS. The CGMS uses daily meteo
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estimate is computed by interviewin
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FIGURE 1.2. Synthetic flowchart of
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B1.8., Annex B1.2). The historical
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• CIPF; • CRA-W; • Centre de
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2.2.8. The Crop Growth Simulation M
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take place, and the maximum daily t
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sought to minimize the prediction e
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Therefore, to optimize and automate
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FIGURE 1.6. Architecture of the B-C
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2.5. Human, financial and technical
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in 2014 49 . Preliminary yield esti
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national level) for 2014. GIS syste
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1.2. Inventory of forecasts availab
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and production can be predicted one
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1.4. How do these different forecas
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2. China national official sources:
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The NSRCP’s key technology includ
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2.1.2. Methodology and practices of
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FIGURE 2.2 Flow chart of NDVI-based
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2.1.3 Methodology and practices of
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various periods. By integrating thr
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indices have been developed, and th
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FIGURE 2.3 Data sources and institu
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2.4. Human, financial and technical
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method is applied to choose three t
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accuracy of the RS indicator and th
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TABLE 2.4 Crop calendar and release
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Institute for Research and Technolo
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■■ Yield • Phenological Event
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2. Morocco’s national official so
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• Level 3: Forecast of crop yield
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TABLE 3.5 Meteorological variables
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two are pre-processing tasks (see F
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FIGURE 3.5 Output data from Levels
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• The agricultural mask, that wil
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FIGURE 3.8 The coefficient of deter
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involved in agriculture, and is sup
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3.1.1.1. Area and Methodology used
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variable and the total rainfall of
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TABLE 3.8 Crop calendars and releas
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110 Crop Yield Forecasting: Methodo
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In administrative terms, South Afri
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1.2.1.1. The role of the Crop Estim
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to submit information. The main aim
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SAGIS releases the following inform
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FIGURE 4.2 Percentage of over/under
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the results from a subjective telep
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a point sample frame. Three types o
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Sample frame To set up the sample s
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North West are allocated proportion
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FIGURE 4.7 Methodology for determin
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2.2.3. Provincial Department of Agr
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• Southern Annular Mode (SAM) fro
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To facilitate the running of such a
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2.6. Innovation and integration wit
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Digitization has been completed for
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FIGURE 4.11 Random selection of a p
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georeferenced. In addition to the o
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of generating signature classes for
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and along with the infra-red bands
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150 Crop Yield Forecasting: Methodo
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the National Agricultural Statistic
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1.2.3. Other regional and global so
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1.4. How do these different forecas
Page 159 and 160: commodity of interest within the op
Page 161 and 162: Potato and winter wheat acres are c
Page 163 and 164: During the growing season, the NASS
Page 165 and 166: 3. Linking up with crop production
Page 167 and 168: 166 Crop Yield Forecasting: Methodo
Page 169 and 170: drying have been taken into account
Page 173 and 174: Meteorological data • USA-NOAA ht
Page 175 and 176: FIGURE B1.2 Grid covering the area
Page 177 and 178: Annex B1.2 - The JRC-MARS Crop Yiel
Page 179 and 180: FIGURE B1.8 MCYFS: Synthetic schema
Page 181 and 182: FIGURE B1.10 The CGMS Statistical T
Page 183 and 184: IDSL indicates whether pre-anthesis
Page 185 and 186: Annex B1.5 - Websites Country Natio
Page 187 and 188: N_A5 By August 25 Seasonal report o
Page 189 and 190: IV. Official releases of crop produ
Page 191 and 192: M P7 M P8 _ By October 25 _ By Nove
Page 193 and 194: Annex B2.2 - Websites Country China
Page 195 and 196: FIGURE B3.2 Agrometeorological bull
Page 197 and 198: FIGURE B3.6 CGMS-MAROC’s web-mapp
Page 199 and 200: FIGURE B3.10 Crop production foreca
Page 201 and 202: from the various models are inserte
Page 203 and 204: FIGURE B3.14 Descriptive schema of
Page 205 and 206: Annex B3.3 - Websites Country Natio
Page 207 and 208: FIGURE B4.2 Gross income (South Afr
Page 209: Annex B4.3 - Example of SAGIS publi
Page 213 and 214: Other countries estimate production
Page 215 and 216: Annex B4.5 - Advanced Sample Framew
Page 219 and 220: FIGURE B5.2 USDA-FAS-PECAD: Crop Ex
Page 221 and 222: FIGURE B5.3A CropScape: Cropland Da
Page 223 and 224: FIGURE B5.7 Global Agricultural Mon
Page 227 and 228: Navalgund, R.R., Parihar J.S., Ajai
Page 229 and 230: Royer, A. & Genovese, G. (eds). 200
Page 231 and 232: Huang, J., Wang, X., Li, X., Tian,
Page 233 and 234: Wang, M. & Wei, G. 2014. Promoting
Page 235 and 236: Zhao, J., Shi, K. & Wei, F. 2007. R
Page 237 and 238: Hutson, J.L. 1984. Estimation of hy
Page 239 and 240: Huddleston, H.F. 1978. Sampling tec
Page 241: Layout: • Laura Monopoli Cover ph
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Crop Yield Forecasting

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