PocketNNI, an app for reducing the environmental impact of arable farming

Optimizing the use of inputs is suitable for both the wallet and the environment. Besides improving the economic performance of crops, precision agriculture is increasingly proving to be an effective way to mitigate the environmental impact of agricultural production, in this case, rice farming

A field in which research (and industry) have made great strides concerns the support of fertilization and crop defense through smart applications, i.e., systems based on the integration of different digital technologies. As for fertilization, a promising approach to formulate quantitative and spatially distributed variable rate diagnoses of nitrogen supply is based on the combined use of remote sensing information and some satellite-guided ground measurements to derive maps of the index of the nutritional status of a crop, i.e., the NNI (Nitrogen Nutritional Index). If the values obtained are less than one, there is crop stress; if, on the other hand, the NNI is higher than unity, there is the so-called "luxury consumption".

The PocketNNI app

The app is a software for smartphones that, starting from remote sensing data, supports nitrogen fertilization, applied in this case on rice.

The app is based on processing the latest satellite maps available through Sentinel 2, the NDVI (Normalized Difference Vegetation Index) and the NDRE (Normalized Difference Red Edge). These maps are used to identify a few points (smart scouting) that can satisfactorily highlight the variability within the plot in order to estimate the nitrogen content (PNC, Plant Nitrogen Concentration) and LAI (Leaf Area Index) of the crop of the points identified in the passage. Next, the connections between PNC measurements and NDRE values in the pixels corresponding to the measurement points are defined and similar connections between LAI and NDVI. With further steps, the NNI is finally defined as the ratio between PNC and Ncrit (Critical Plant Nitrogen Concentration).

The PocketNNI app is particularly useful for diagnostic purposes, to directly provide the NNI as output, integrating ground measurements and satellite images in a fully automated way, without the need for dedicated tools and without having to export and analyze data in external environments. In this way, creating maps of nutritional status is not required, with significant advantages in terms of cost-effectiveness and timeliness of the analysis. The information provided is easily interpreted in order to effectively overcome most of the barriers limiting the adoption of precision farming techniques in purely operational contexts.

 

Field experiments

One of the experimental trials for the validation of the app was carried out in a plot of 2 ha cultivated with rice in the province of Milan, according to the practice of submergence, commonly adopted in the district.

Two different nitrogen fertilization strategies with urea were applied, each on half of the plot: the first (called " Baseline Scenario", BS) of the traditional type, implemented without spatial differentiation and according to the cultivation needs perceived by the farmer; the second ("Alternative Scenario", AS), using the PocketNNI app.  Satellite data were grouped into 5 classes, namely severe stress (NNI < 0.7); light stress (0.7 ≤ NNI < 0.9); neutral (0.9 ≤ NNI ≤ 1.1); light luxury consumption (1.1 < NNI ≤ 1.3): (v)severe luxury consumption (NNI > 1.3) in order to derive a prescription map, to suggest the most correct dose of nitrogen to be distributed in different points of the plot.

In detail, the real-time diagnosis of nitrogen nutritional status with the combined use of PocketNNI and satellite data allowed to capture the spatial variability of NNI, resulting in a variable rate distribution. With very similar applied average doses of urea, yields were significantly different, with increases in paddy rice of as much as 12.8% in the alternative scenario. This protected both from nitrogen stress (with potential yield decrease) and luxury consumption (leading to greater vulnerability to lodging and a tendency to fungal infections).

 

Environmental benefits

The environmental performance of the two fertilization strategies was assessed using the Life Cycle Assessment, which estimates the potential environmental impacts of a product throughout its life cycle, considering the many effects on the environment, namely: Carbon footprint or Climate change (CC), ozone layer depletion (OD), human toxicity - non-carcinogenic effects (HT-noc), human toxicity - carcinogenic effects (HT-c), particulate matter (PM) formation, photochemical smog formation (POF), acidification (TA), terrestrial eutrophication (TE), freshwater eutrophication (FE), marine eutrophication (ME), freshwater ecotoxicity (FEx), and mineral and fossil resource depletion (MFRD).

The presented data concern 1 ton of paddy rice at commercial humidity (14%), considering all the phases of the production cycle, from the working of the soil to the drying of paddy rice.

This excludes the rice processing and packaging (steps that are not directly influenced by fertilization).

Information on the consumption of production factors (seeds, plant protection products, fertilizers, diesel and energy) and the use of tractors and equipment were collected through field inspections. Methane and fertilizer-related emissions (e.g., nitrate leaching, ammonia volatilization) were estimated according to models proposed by the Intergovernmental Panel on Climate Change (IPCC).

Conventionally, for each environmental effect evaluated, the worst-case scenario is set equal to 100%, while the other is proportionally scaled.

In the trial carried out, the alternative scenario of fertilization performed with the support of the PocketNNI app invariably shows a lower impact, with reductions ranging from about 10% (for ozone depletion) to 13-14% for acidification, eutrophication and consumption of mineral and fossil resources.

The improved environmental sustainability can be ascribed to both the higher yield and the greater efficiency of nitrogen fertilization: Indeed, the PocketNNI app has optimized the amount of N distributed per kilogram of paddy rice produced while simultaneously reducing the amount lost through leaching and/or volatilization.

On a more general level, the decreased consumption of mineral fertilizers has a double environmental benefit, as it reduces their production (which is highly energy-intensive) and at the same time it cuts down on the emission of pollutants such as ammonia, nitrates and, although to a lesser extent, nitrous oxide. Hence, from the environmental point of view, the benefits mainly concern lower acidification and eutrophication.

As for economic sustainability, the solution presented has both direct benefits (higher productivity per unit of nitrogen distributed) and indirect benefits (lower risk of losses due to diseases and training), against a negligible increase in expenditure (5 euros/ha per year).

Although the trial was carried out for a single cultivation campaign, the results achieved are promising and confirm what was obtained in similar surveys. In these cases, the same reference (the NNI) was calculated using instrumentation to estimate PNC and LAI, with manual integration in an external environment of data collected on the ground and employing satellite images.

A further aspect of submerged rice cultivation that affects global warming is the methane emission due to the degradation of organic matter in anaerobic conditions. On this subject, several research projects are underway (including "BESTsomRICE"), aimed at evaluating alternative water management for reducing the phenomenon, intending to create profitable synergies with variable rate fertilization based on PocketNNI.