Yield variability across spatial scales in high input farming: Data and farmers’ perceptions for potato crops in the Netherlands

• Published in: European journal of agronomy 2023-10, Vol.150, p.126925, Article 126925
• Main Authors: Ravensbergen, Arie Pieter Paulus, van Ittersum, Martin K., Silva, João Vasco, Maestrini, Bernardo, Kempenaar, Corné, Reidsma, Pytrik
• Format: Article
• Language: English
• Subjects: Climate variability; Linear mixed effects models; Long-term yield data; Solanum tuberosum; Weather extremes; Yield gap
• ISSN: 1161-0301; 1873-7331
• DOI: 10.1016/j.eja.2023.126925

Crop yields are determined by the biophysical environment and by farm management decisions, which in turn depend on socio-economic conditions of the farm(er). The interaction of these factors results in spatial and temporal yield variability. We assessed ware potato yield variability in the Netherlands across four agronomically relevant scales (among provinces, farms and fields and within fields) using five datasets with data on potato yield across space and time. Furthermore, we disseminated an online questionnaire among farmers to identify the perceived yield gap and the key yield gap explaining factors at farm level. Spatial yield variability was largest among fields, with a standard deviation of 8.5–11.1 t ha−1, and within fields, with a standard deviation of 7.7–8.7 t ha−1. Spatial yield variability decreased at higher aggregation levels, i.e., the standard deviation of among-farm yield variability was 4.0–6.1 t ha−1 and that of among-provinces 1.6–3.5 t ha−1. Mean yields of the datasets ranged from 46 to 52 t ha−1. Temporal yield variability explained 10–55 % of the total observed variation in crop yield and its magnitude was equal or larger than the spatial yield variability for almost all datasets. Farmers estimated the ware potato yield gap at 13–18 t ha−1, corresponding to 20–24 % of estimated yield potential, depending on the soil type and variety. Water deficit and water excess were considered the most important yield gap explaining biophysical factors. In addition, soil structure was an important biophysical factor on clay soils and diseases on sandy soils. Irrigation and fertilization were identified as the most important yield gap explaining management factors, whereas legislation and potato prices were identified as the key socio-economic factors influencing potato yields. However, the perceived yield gap explaining factors varied with soil type, variety and year. We conclude that reducing potato yield variability in the Netherlands can be achieved best at the field and within-field level, rather than at farm or regional level. When reducing yield variability is not feasible and/or desirable, inputs should be adapted to actual yield levels to achieve optimal environmental and economic sustainability. [Display omitted] •We assessed potato yield variability at regional, farm, field and within-field scale.•We asked farmers to indicate the most important yield gap explaining factors at farm level.•Yield variability was largest at field and with