Creating the data basis to adapt agricultural decision support tools to new environments, land management and climate change—A case study of the RiceAdvice App

Abstract

Increasing demand for land to ensure human food security in the future has already impelled agricultural production into marginal areas. The environmental conditions found there have a more pronounced impact on agricultural productivity than in the systems used so far under favourable conditions. In addition to this challenge, climate change is expected to increase the unreliability of weather conditions (through increased variability and occurrence of extremes) for farmers considerably. This unreliability is even more serious in developing countries’ farming system where food security is vulnerable. Current efforts in digitalization offer great possibilities to improve farmers` decision‐making processes. A wide range of online tools and smartphone applications is available to support both agricultural extension services and smallholder farmers alike. These apps are often parameterized and validated to certain environments and are troubled when applied to new geographical locations and different environmental conditions. We have conducted field trials to demonstrate potential methods to close knowledge gaps in the data background for one of these apps, RiceAdvice, concerning three key aspects: shifting of cropping calendar, adjustment of fertilizer management and genotype selection. Sites in Ethiopia, Madagascar and Rwanda were selected to represent altitudinal gradients, with overlapping elevations reflecting differences in temperature to enable cross‐country comparisons. Planting dates were distributed throughout three calendar years, with continuous iterative planting dates taking place in Madagascar, in‐ and off‐season planting dates in Rwanda with different fertilizer applications, and one planting date during each rainy season in Ethiopia with different management options. With these trials, we have been able to identify key data sets needed for the adaptation of agricultural decision support tools to new environments. These include the assessment of climatic constraints on innovations to cropping calendars (e.g. double cropping), informed selection of alternative varieties able to complete crucial parts of their phenological development to avoid temperature‐related stress inducing, for example spikelet sterility in rice in late development stages and the effectivity of potential innovations in fertilizer management strategies.

Transplanting as an option to cope with abiotic stress in high‐altitude lowland rice production systems in East Africa

“…The disadvantage is clearly labour intensity if it is not mechanized (Haefele et al., 2016). In rainfed systems, direct seeding, on the contrary, is prone to poor stand count and losses from early droughts due to unpredictable rainfall patterns that increase the weed pressure in the ongoing season (Cotter et al., 2020; Ohno et al., 2018). Although initially debated (Sharma, 1995), it has been shown that transplanting has the potential to increase yields, nutrient efficiency, and water productivity in irrigated systems (Chen et al., 2017; Tadesse et al., 2013; Ullah et al., 2020; Zhang et al., 2018).…”

Season‐specific varietal management as an option to increase rainfed lowland rice production in East African high altitude cropping systems

“…To avoid the risk of cold sterility two rules should be followed, the selected variety should arrive at booting stage latest at the end of October, but to make use of the higher radiation levels in September, it should have the longest cycle length possible without compromising the first rule. Therefore, precise knowledge of the duration of the potentially suitable varieties is required and a crop model that is well‐calibrated for the varieties as well as for the environment in combination with a smartphone application such as RiceAdvice (Cotter et al, 2020) would be of great help to support farmers’ decision‐making.…”

Impact of Climate Change on Dryland Agricultural Systems: A Review of Current Status, Potentials, and Further Work Need

“…rice, wheat and maize, in the northern part of China due to HT and D stress. The combined detrimental effect of HT and D on cereal, i.e., rice, sorghum, wheat, barley, and maize, was more severe as compared to individual HT or D impact (Cotter et al, 2020). Cohen et al, (2020) conducted meta-analysis of HT and D stress on crop yield and yield components.…”