PIIRS Digitization
PIIRS FY16
PIIRS FY17
PIIRS FY18
PIIRS FY19
- FY19 guidance - defining participants
- FY19 guidance - treating double counting
- FY19 guidance - reporting on carbon footprint
- FY19 Frequently Asked Questions
PIIRS FY20
- FY20 guidance - reporting on carbon footprint
- FY20 guidance - reporting on gender pay gap
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| INDICATOR 2: Increased yield per unit area (or productivity (in yield) per unit area; also to cover forests, fisheries, livestock etc.) | |
| Why this indicator? What will it measure and provide information for? This indicator will provide information on agriculture yield growth rate (cereal, livestock, aquaculture, fisheries, etc.) (% p.a.), with sustainable agriculture practices. This will help to measure how well sustainable agriculture practices are helping to close the yield gap (productive and sustainable parts of the SuPER principles). Methodology includes standard monitoring of yields against baseline over time and at post-harvest intervals. FGDs and KIIs can provide qualitative verification. |
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| What Sustainable Development Goal is the indicator connected to? * SDG Goal 2 * SDG Goal 13 * SDG Goal 15 |
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| Definitions and key terms Changes to productivity can be measured in different ways. The most common approach is to measure yields. Yield measurement techniques vary between crops, and range from weighing harvested grain from the entire field to weighing representative samples from a plot area after plants have reached physiological maturity (Lauer 2002). There are also many mathematical approaches for computing basic yield. Improving the nutritional relevance of food security measurement means using indicators that capture both macro- and micronutrient consumption at the individual level and give some sense of acute food insecurity (such as seasonal shortfalls or consumption shocks). Examples of indicators used to measure productivity include: * Yield (e.g. product per unit of land or area, water, energy, nutrients, labor) * Income (e.g. gross margin, net present value – covered in Pillar 2) * Labor (e.g. person hours, labor allocations by gender – covered in Indicator 4 below and Pillar 2) In the case of agriculture, the most commonly used unit is kg/ha or MT/ha which can evolved depending on the physical elements (soil quality, water availability, temperatures, etc.) and on technological aspects (agricultural techniques). |
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| Data and information required to calculate the indicator * Numerator: total output per unit area for each crop/product (kg/ha or MT/ha for example) * Denominator: total unit area cultivated for each crop (in ha for example) |
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| Suggested method for data collection * Methodology would include standard monitoring of yields against baseline over time and at post- harvest intervals. |
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| Possible data sources * Data from different administrative levels: local, national, and regional * Primary data collection: project household surveys * Secondary data |
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| Resources needed for data collection * Primary data collection: project household surveys * Secondary data * Local/national/regional agricultural statistics |
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| Reporting results for this indicator: number of people for which the change happened * Reporting Purpose: þBaseline þProgress þ Evaluation * Number of households experiencing increased production * Number of additional tons of food produced per hectare |
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| Questions for guiding the analysis and interpretation of data (explaining the how and why the change happened, and how CARE contributed to the change) * This indicator provides the total output per unit area and indicative information on the productive systems efficiency |
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| Other Considerations * FGDs can provide qualitative verification, especially regarding to external factors (climate, pests and diseases, insecurity, input markets, prices, etc.) which could have affected productivity. * Should be collecting data at the same time of year, ideally post-harvest, every year |
