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�� Costing of breeding Programs: Crop Network based Approach��Lennin Musundire��7th October 2025��APBA Conference, Victoria Falls, Zimbabwe��

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Current and Future Status

Common gap for Crop breeding networks

1. Plant breeding is a business

2. Align resource allocation relative to market share/size

3. Compare the cost of the alternative breeding pipeline and strategies

4. Estimate the cost of running current breeding pipelines

Costing is now part of ENABLE (B4T –AoW and EiB phase 3PO).

The focus is on crop regional networks, with an emphasis on “breakthrough products” to align with the Gates Foundation's investments.

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Potential solution

https://cgiar-service-portal-prd.azurewebsites.net/register

Service portal request

Further improvement through the use of an “Excel-based” new approach – analysis and modelling.

https://excellenceinbreeding.org/toolbox/tools/breeding-costing-tool

Clunky interface

Requires knowledge of breeding programs to operate – discourages non-breeders

Detail heavy - gets into the weeds (e.g., cost of envelopes/pens)

University of Queensland Costing Tool is open access/free and developed by practical plant breeders –

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Primary Outcomes of Costing

Develop

Develop Realistic Budgets

Charge

Costing for Services realistically

Identify

Identify High-Cost Items

Optimize

Optimize resource allocation through basic simulation – not QG, breeding metrics at various stages

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Case Study: WCA Sorghum Network

Market Segments, Country Prioritization, and Costing Summary of Breeding Programs

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Market Segments, Actual Area Harvested (Ha) and Partner Roles �

ID MS internal	MS ID from Breeding Portal	MS Long Name	Burkina Faso	Ghana	Mali	Nigeria	Senegal	Togo	Niger	Chad	Cameroon	Total Area (ha)/MS
	Tier		3A	4A	2A	3B	3A	3B	3B	4B	4B
MS1	MS00673	Sorghum \| Non-Hybrid \| WAF \| Food; Fodder \| White; Cream \| Sahelian Zone \| Rainfed \| Early	475,000		549,548	1,401,250	39,123		2,111,451	282,391	107,418	4,966,180
MS2	MS00400	Sorghum \| Non-Hybrid \| WAF \| Food; Fodder \| White; Cream \| Sudan; Guinea zone \| Rainfed \| Mid	570,000		1,099,095	2,802,500	117,368	15,802	703,817	338,869	143,224	5,790,675
MS3	MS00681	Sorghum \| Non-Hybrid \| WAF \| Food; Fodder; Local Malting \| Red \| Sudan; Guinea zone \| Rainfed \| Mid	570,000	121,867		280,250		180,139		338,869	250,643	1,741,767
MS4	MS00674	Sorghum \| Hybrid \| WAF \| Food; Fodder \| White; Cream \| Sahelian Zone \| Rainfed \| Early	190,000		18,318	112,100	13,041		211,145			544,604
MS5	MS00675	Sorghum \| Hybrid \| WAF \| Food; Fodder \| White; Cream \| Guinea zone; Sudan \| Rainfed \| Mid	95,000		91,591	112,100	13,041					311,732
MS6	MS00678	Sorghum \| Non-Hybrid \| WAF \| Food; Food Processing; Poultry \| White \| Sudan; Guinea zone \| Rainfed \| Mid		15,233	73,273	280,250				56,478		425,235
MS7	MS00677	Sorghum \| Non-Hybrid \| WAF \| Malting; Feed \| White; Cream \| Sudan; Guinea zone \| Rainfed \| Mid	106,633		560,500							667,133
MS8	MS00676	Sorghum \| Non-Hybrid \| WAF \| Food; Food Processing \| Red \| Sahelian Zone \| Rainfed \| Early	60,933				72,688	70,382	112,956			316,959
MS9	MS00915	Sorghum \| Non-Hybrid \| WAF \| Food; Food Processing; Poultry \| White \| Sahelian Zone \| Rainfed \| Early				26,082	47,405	351,909				425,396
MS10	MS00680	Sorghum \| Non-Hybrid \| WAF \| Ethanol production \| White; Cream \| Sudan; Guinea zone \| Rainfed \| Mid			56,050							56,050
MS11	MS00914	Sorghum \| Non-Hybrid \| WAF \| Food; Fodder \| White; Cream \| Sahelian Zone; Post rainy season \| Rainfed \| Extra-early				39,123						39,123
MS12	MS00679	Sorghum \| Hybrid \| WAF \| Food; Food Processing \| White \| Sudan; Guinea zone \| Rainfed \| Early				13,041						13,041
MS13	MS01119	Sorghum \| Non-Hybrid \| WAF \| Fodder \| White; Cream; red \| Sudan; Guinea zone \| Rainfed \| Mid						70,382				70,382
Total Area (Ha) per Country			2,067,566	137,100	2,448,375	5,066,696	302,665	688,613	3,139,369	1,016,608	501,285	15,368,277

Program receiving resources for population development		Program receiving resources for trialing		Not a regional priority, country effort only		Dormant program

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Breeding scheme for OPV sorghum pipelines �(MS1, MS2 and MS3)

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There is also the Regional and National breeding pipelines for:

Hybrids female parents (seed parents) or B lines sorghum pipelines (MS4 and MS5)

Hybrids male parents (pollen parents) or R lines sorghum pipelines (MS4 and MS5)

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Market Segments, Partner Roles and Total Cost (US$)

	MS ID	CIMMYT Senegal	Burkina Faso	Mali	Nigeria	Senegal	Togo	Total Cost (US$) per MS
Tiers			3A	2A	3B	3A	3B
MS1	MS00673	341,557	269,996	102,509	61,854	244,382		1,020,297
MS2	MS00400	349,088	323,996	205,017	50,841	255,383	10,901	1,195,225
MS3	MS00681	349,110	323,996		56,348	46,752	124,272	900,477
MS4	MS00674		107,999	169,822	79,623	108,756		466,200
MS5	MS00675		53,999	17,085	62,167	97,900		231,151
Total Cost (US$) per Country		1,039,754	1,079,985	494,432	310,833	753,173	135,173	3,813,350

The partner is only interested in the market segment as a test and release.		The partner is interested in the Market Segment but not network/ABI interest.		The network funds the partner to scale up breeding.

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High Level Summary

1. At least 58% of operational costs are currently spent on germplasm development and 42% on product evaluation.

2. The three most expensive components of the breeding pipeline are:

F₁ crossing for $17.22 per 3m row.
Breeder and foundation seeds production for $15.88 and $ 16.52 per 3m row, respectively.
Stage 2 AYT trials at $4.26 per 3m row.

3. The three most expensive cost item activities in nurseries are:

Cost of pollination bags
Cost of labour for pollination.
Cost of labour for day and night guarding

4. The three most expensive items in trials are:

Cost of labour for pollen bagging and self-pollination.
Cost of field visits for breeders, research assistants and respective drivers
Cost of labour for data collection, counting the number of plants, the number of ears, and plant lodging.

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Recommendations

Prioritize high-impact traits and crops aligned with market demand.
Use Market segments to guide investment. Allocate resources proportionally to potential market share and size, as well as farmer adoption.
Benchmark alternative breeding strategies (e.g., conventional vs. genomic selection).
Use costing data to inform decisions on breeding pipeline design and optimization.
Identify cost drivers in each program and areas for efficiency gains.

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Research Outcomes