Vall-Optimal: New technology and operations management for optimal harvest time and forage quality on cattle farms

Background

Analysing the nutrient composition in ley crops and other roughages became common in Sweden during the 1970s. The main aim in that period was to increase the crude protein concentration in hay and silage. In an effort to predict the nutritional quality of the forage before harvest, samples were taken and the results were linked to the accumulation of temperature, which is presented in a model to predict the optimal day for harvest of the first cut in ley systems. This model, Vallprognos (Vallprognos.se) provides robust and useful results and is currently in use in Sweden. However, we need information for predicting optimal harvest dates for the subsequent cuts. Farmers and advisors need near real time information on the nutritional quality status of the crop.

An alternative to the current methods is to use spectral devices that measure the amount of light reflected by plants. These measurements combine with data from multiple analysed plant samples in laboratories using conventional chemistry for nutritive values, and these results are used for calibrations of the instruments. Used with appropriate mathematical tools, these devices provide information about the standing or harvested crop. These devices can further be divided into two types, the passive spectrometers, and active light spectrometers (Figure 1).

Figure 1. Passive (a) vs active (b) light sensors. The passive sensor measures the sunlight reflected by the plant, whereas the active sensor emits its own light using a bulb and measures it back after being reflected by the plant.

Project description

The project started in 2021 and was until December 2023, covering three growing seasons. Field campaigns were being performed in several farms over Sweden and the tasks are organised according to three main activities, as follow:

Activity 1. Prediction of harvest time for ley using field spectrometers

In Activity 1, we used the Yara-N sensor field spectrometer to collect spectral data in swards all over Sweden. The Yara-N sensor is a commercial field spectrometer that is already used by farmers for wheat nitrogen management purposes. The spectral data was used to calibrate models to estimate the forage parameters, including yield, protein, and digestibility, which gives the fraction of the feed that is utilised by the animal.

Activity 2. Field test the pre-harvest field spectrometer system with farmers

In activity 2, we tested how farmers can use field spectrometer data to improve harvest decisions and give advisors the opportunity to use field spectrometers as a complementary tool to the Vallprognos.se system. To do this, we developed a simple prototype of a decision support system where farmers and advisors could upload and view the spectral data collected from the Yara-N sensor and get estimates of forage parameters from the models developed in Activity 1.

Figure 2. Prototype of the web system with the information that could be accessed by farmers.

Activity 3. Evaluate the potential for using active light sensors for prediction of nutrient content in grass/clover silage.

In Activity 3, we used active light spectrometers (ALS) to measure dry matter content and forage quality in stored silage. For this purpose, we used two handheld devices to scan silage samples collected over several regions in Sweden. The resulting spectral data was used to develop models to predict feed quality.

Collaboration

This project was a collaboration between the Swedish University of Agricultural Sciences (SLU) and Växa Sverige.

Contacts

Anders H Gustafsson, Expert fodder Knowledge & Development
Växa Sverige
anders.h.gustafsson@vxa.se, +46 10-471 06 32, +46 70-375 99 41

Johanna Karlsson, Expert fodder Knowledge & Development
Växa Sverige
johanna.karlsson@vxa.se, +46 10-471 01 35, +46 76-125 03 79

Hans Lindberg, Production Consultant
Växa Sverige
hans.lindberg@vxa.se, +46 10-471 01 15, +46 70-370 29 86

David Parsons, Professor
Department of Crop Production Ecology, Crop production science
Swedish University of Agricultural Sciences
david.parsons@slu.se, +46 90-786 87 14, +46 73-089 34 45

Julianne Oliveira, Researcher
Department of Crop Production Ecology, Crop production science
Swedish University of Agricultural Sciences
julianne.oliveira@slu.se, +46 90-786 87 24, +46 76-763 71 29

Sanna Bergqvist, Doctoral student
Department of Crop Production Ecology, Crop production science
Swedish University of Agricultural Sciences
sanna.bergqvist@slu.se, +46 90-786 87 26, +46 73-067 50 37

Bengt-Ove Rustas, Researcher
Department of Animal Nutrition and Management; Feed science
Swedish University of Agricultural Sciences
bengt-ove.rustas@slu.se, +46 18-67 16 63, +46 72-244 69 55