A Meta‐Analysis of Maize and Wheat Yields in Low‐Input vs. Conventional and Organic Systems

Abstract

Organic and low‐input systems are proposed as ways to reduce the environmental impacts of agriculture. Previous studies have shown that yields of organic systems can be ∼19 to 25% lower than conventional systems. An intermediary, low‐input system could be less damaging for the environment than conventional systems, while reducing yield losses in comparison with organic systems. In this study, we performed a meta‐analysis to compare low‐input systems to conventional and organic systems. Our analysis is based on data of cropping system experiments conducted in Europe and North America, and focuses on two important crops, maize (Zea mays L.) and soft winter wheat (Triticum aestivum L.). Pesticide use was greatly reduced for low‐input systems as compared with conventional for the two crops (50% for maize, 70% for wheat on average). Mean mineral N use was also reduced by 36% for maize and 28% for wheat in low‐input relative to conventional. Maize yields in low‐input systems were not different from those in conventional systems, and were higher than yields in organic systems (yield ratio of low‐input vs. organic = 1.24). Wheat yields in low‐input systems were lower than yields in conventional systems (yield ratio of low‐input vs. conventional = 0.88), but were substantially higher than yields in organic systems (yield ratio of low input vs. organic = 1.43). This is one of the first meta‐analyses to assess performance in terms of pesticide use intensity, and yields, with clear evidence emerging that low‐input systems can markedly reduce pesticide application, without strongly reducing crop yields, relative to conventional systems.Core Ideas Maize yields are equivalent for tested low‐input and conventional systems. Maize yields are on average 24% higher for tested low‐input relative to organic. Wheat yield average is 12% lower in tested low‐input than in conventional systems. Wheat yields are on average 43% higher for tested low‐input relative to organic. Mean pesticide use is more than halved in low‐input compared to conventional systems.

A new analytical framework of farming system and agriculture model diversities. A review

“…It seems that there is still much room to improve efficiency of (i) nitrogen and phosphorus fertiliser use (Goulding et al 2008;Cordell et al 2011), including use of "enhanced-efficiency fertilisers" such as controlled-release fertilisers and nitrification/urease inhibitors (Timilsena et al 2015), (ii) water use (Ali and Talukder 2008;Playan and Mateos 2006) and (iii) pesticide use (e.g. Gaba et al 2016;Hossard et al 2016;Lechenet et al 2017). Research is still needed to estimate the room for improving these efficiencies, to assess potential impacts on agricultural and environmental performances from field to landscape/catchment levels in different production situations and to develop the knowledge required to implement best management practices.…”

Meta‐Analysis of QTL Studies for Resistance to Fungi and Viruses in Maize

“…Moreover, primary studies may report heterogeneous results because they use different genotypes and environments (Hao et al, 2010). Several meta-analysis approaches have been used to compare agriculture systems, mainly for environmental condition effects on production (Rotundo and Westgate, 2009;Pittelkow et al, 2015;Hossard et al, 2016), but few meta-analyses focused on phenotype-genome associations (Zeggini and Ioannidis, 2009;Teissier et al, 2018). Data extracted from several and even heterogeneous studies could be subjected to metaanalysis (Akobeng, 2005), which is a research design that combines results of primary studies, thereby increasing the power and precision of estimates of global effects and thus increasing the validity of conclusions (Ferreira González et al, 2011).…”

“…Data extracted from several and even heterogeneous studies could be subjected to metaanalysis (Akobeng, 2005), which is a research design that combines results of primary studies, thereby increasing the power and precision of estimates of global effects and thus increasing the validity of conclusions (Ferreira González et al, 2011). Several meta-analysis approaches have been used to compare agriculture systems, mainly for environmental condition effects on production (Rotundo and Westgate, 2009;Pittelkow et al, 2015;Hossard et al, 2016), but few meta-analyses focused on phenotype-genome associations (Zeggini and Ioannidis, 2009;Teissier et al, 2018).…”

Agricultural Science and Organic Farming: Time to Change Our Trajectory

“…Where science has compared systems that combine organic amendments, crop rotations, and judicious use of fertilizers and pesticides (low‐input systems as compared to conventional practices), it has found the organic system lacking. A meta‐analysis of comparisons of organic, low‐input, and conventional systems for wheat and corn (Hossard et al, 2016) found that low‐input systems had better yields than organic systems and used 70% less pesticide for wheat (50% less for corn) and 28% less nitrogen fertilizer (36% less for corn) than the conventional systems. This is a beneficial compromise between intensive, high‐input, high‐yield agriculture and organic agriculture, but it has little marketing power in the general population.…”