estimating yields and yield gaps: experiences from east...

International Institute of Tropical Agriculture – Institut international d’agriculture tropicale – www.iita.org

ESTIMATING YIELDS AND YIELD GAPS:

Experiences from East Africa

Godfrey Taulya, Lydia Wairegi, Piet van Asten


PRESENTATION OUTLINE

1. General approach

2. Yield estimation in banana/plantain systems

3. On-farm monitoring study vs. one-time farm visit survey

4. Non-destructive bunch weight estimation

5. Yield-determining factors and yield gaps


GENERAL APPROACH

1. What is happening in

farmer fields ?

2. Study single factors in

controlled environments

3. Field validation and testing

for interactions

4. Modeling to understand

interactions and extrapolate

5. Proposing technologies for

on-farm testing


Understanding existing spatial variability

at regional scale

0 125 250 km

L. Kivu

L. Edward

L. Tanganyika

L. Victoria

Rwanda

Uganda

TanzaniaBurundi

DRCongo

Kenya

30°E 35°E

0°

5°S


Understanding existing spatial variability

diagnostics at farm scale

Michael Okumu, Severine Delstanche


YIELDS IN BANANA/PLANTAIN SYSTEMS

Integrative index for

impacts of:

• constraints

• cultural practices

Yield bunch weight

• Harvests are year-round

• Temporal variations in

fresh bunch weight


YIELD DATA COLLECTION BY FARMERS

One-time farm visits during surveys patchy data

o Mature bunches may be weighed

o Immature bunches: visual ‘guestimates’ + extrapolation

Farm monitoring studies comprehensive data

o Challenge: Synchronizing farm visit with harvest operations

Yield data collection by farmers in monitoring studies

o Extra demands on the farmer (time and labour)

o Literacy/numeracy skills; accuracy and consistency in data

o Restricting studies to literate farmers can bias datasets

• Greater resource endowment, higher standard of management

are correlated with higher literacy levels


ESTIMATION OF FRESH BUNCH WEIGHT

General allometric function for estimation of fresh bunch weight (FBW, kg)

at harvest was established through linear regression:

Where:

H is number of hands per bunch

F is number of fingers on second-last hand

V is the pseudostem volume at 1-m above ground (cm3)

k is linear regression intercept while a, b and c are coefficients

Where:

G0 is girth at base of pseudostem (cm)

G1is girth at 100 cm above ground level (cm)


Across regions in Uganda

APPLICATION OF ALLOMETRIC FUNCTION

Across cultivars in Uganda


LIMITING FACTORS AND YIELD GAPS

Each farm was visited once in 4

to 6 weeks

Input data for the allometric

function were collected on

flowered plants

Agronomic management/crop

environment, pest damage data

were also collected

Boundary line analysis

identify the limiting factor/s

and to quantify the yield gap

due to each factor


LIMITING FACTORS AND YIELD GAPS


Evaluation of yield-determining factors during plant growth,

and

Non-destructive estimation of bunch weights based on

allometry permit:

Identification of limiting factors

Quantification of yield-gap

CONCLUSIONS

estimating yields and yield gaps: experiences from east...

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