Implications of intra-plot heterogeneity for yield estimation accuracy: Evidence from smallholder maize systems in Ethiopia

Abstract

Highlights We examine inter- and intra-plot heterogeneity of productivity in maize plots. We find high inter- and intra-plot variabilities in plant population and yield. Intra-plot heterogeneity overrides inter-plot heterogeneity in smallholder maize. The magnitude and distribution of yield estimation errors are method-dependent. More intensively managed plots show lower intra-plot heterogeneity and lower yield.

Revisiting the size–productivity relationship with imperfect measures of production and plot size

“…Thus, we first conduct an empirical characterization of measurement error associated with the different protocols, including some of those perceived as gold standards, and find that they suffer from systematic (nonclassical) measurement error. Interestingly, we find that all types of crop-cut sampling involving nonrandomly selected quadrats suffer from systematic measurement error, suggesting the prevalence of systematic differences in productivity within plots, as has also been shown in some recent studies (e.g., Bevis & Barrett, 2020;Kosmowski et al, 2021;Sida et al, 2021). We also find both negative and positive correlations between measurement error associated with the different protocols.…”

“…An imaginary "M" line starting at 1 meter from the northwestern vertices of the plot is identified and then a "W" line on the opposite long side of the plot is identified. The "feet" and the "vertices" of the "M" and "W" lines are used as sampling points (Sida et al, 2021) a At each sampling point, three maize cobs are randomly selected, the number of cob-bearing maize plants are counted, the cobs are weighed, and the field moisture content of the grain is recorded. The fresh grain yield is standardized at 12.5 percent moisture content (Sida et al, 2021).…”

“…The "feet" and the "vertices" of the "M" and "W" lines are used as sampling points (Sida et al, 2021) a At each sampling point, three maize cobs are randomly selected, the number of cob-bearing maize plants are counted, the cobs are weighed, and the field moisture content of the grain is recorded. The fresh grain yield is standardized at 12.5 percent moisture content (Sida et al, 2021). The fresh weight is then adjusted by the grain moisture content to compute dry weight using the formula: Dry Weight ¼ Fresh Weight à 100 -Moisture content of the shelled grain 100 (Sida et al, 2021).…”

“…First, the benchmark production and area measurement protocols used in previous studies are themselves not free from potential mismeasurement. For example, most studies use subplot crop cuts for approximating total production, whereas recent studies show that some types of subplot crop cuts can suffer from nonclassical measurement error (Kosmowski et al, 2021;Sida et al, 2021). 3 Similarly, although land area measurement using global positioning systems (GPS) brings significant improvements over self-reported data (Carletto et al, 2015(Carletto et al, , 2017Dillon et al, 2019;Kilic et al, 2017), the consumer grade GPS devices used in many of these studies are likely to suffer from some inaccuracies when applied to smaller plots (Dillon et al, 2019;Keita & Carfagna, 2009).…”

Mathematics of the Relationship between Plant Population and Individual Production of Maize (Zea mays L.)

“…Crop Environment Resource Synthesis (CERES) models simulate an average plant resulting in considerable uncertainties in understanding maize responses [17]. The different yield estimation protocols perform differently under different degrees of intra-field heterogeneity; how their accuracies vary was still reported unclear in 2021 [18].…”