Optimising the harvesting time of grass in primary growth is difficult under Finnish climatic conditions, because the digestibility of grass decreases on average by 0.5 percentage units daily. We constructed a model based on cumulative temperature and geographical location which estimates the digestibility of grass. This model is used to produce estimates utilising real time weather information. The estimates are presented as a map, which is revised daily. Farmers have free access to the maps via Internet

Huhtanen, P.

Mattila, I.

Nikander, H.

Nousiainen, J.

Rinne, Marketta

English

University of Kentucky

University of Kentucky UKnowledge International Grassland Congress Proceedings XIX International Grassland Congress Digestibility Estimates Based on a Grass Growth Model Are Distributed via Internet to Finnish Farmers Marketta Rinne Agricultural Research Centre, Finland J. Nousiainen Valio Ltd., Finland I. Mattila Agricultural Research Centre, Finland H. Nikander Agricultural Research Centre, Finland P. Huhtanen Agricultural Research Centre, Finland Follow this and additional works at: https://uknowledge.uky.edu/igc  Part of the Plant Sciences Commons, and the Soil Science Commons This document is available at https://uknowledge.uky.edu/igc/19/33/4 The XIX International Grassland Congress took place in São Pedro, São Paulo, Brazil from February 11 through February 21, 2001. Proceedings published by Fundacao de Estudos Agrarios Luiz de Queiroz This Event is brought to you for free and open access by the Plant and Soil Sciences at UKnowledge. It has been accepted for inclusion in International Grassland Congress Proceedings by an authorized administrator of UKnowledge. For more information, please contact UKnowledge@lsv.uky.edu. ID # 33 - 04DIGESTIBILITY ESTIMATES BASED ON A GRASS GROWTH MODEL AREDISTRIBUTED VIA INTERNET TO FINNISH FARMERSM. Rinne1*, J. Nousiainen2, I. Mattila1, H. Nikander1 and P. Huhtanen11Agricultural Research Centre, FIN-31600 Jokioinen, Finland2Valio Ltd., Farm Services, P.O. Box 20, FIN-00039 Valio, Finland* marketta.rinne@mtt.fiAbstractOptimising the harvesting time of grass in primary growth is difficult under Finnish climaticconditions, because the digestibility of grass decreases on average by 0.5 percentage units daily.We constructed a model based on cumulative temperature and geographical location whichestimates the digestibility of grass. This model is used to produce estimates utilising real timeweather information. The estimates are presented as a map, which is revised daily. Farmers havefree access to the maps via Internet.Keywords: Advisory service, cumulative temperature, D-value, forecast, grass, growth stage,Internet, modelIntroductionUnder the climatic conditions of Finland, the primary growth of grass after winter is veryintensive. Dry matter (DM) yield increases rapidly, but simultaneously the concentration ofdigestible organic matter in DM (D-value) of grasses decrease. The daily D-value decline ingrasses such as timothy and meadow fescue has on average been 0.5 percentage units, but therange is large (0.1 to 1 unit per day). Cutting the grass very early means unnecessary sacrifices inharvested DM while a late harvest decreases the nutritional value of the forage. Cows consuminggrass silage ad libitum decreased their daily milk production by 0.5 kg per each percentage unitdecline in silage D-value (Rinne et al. 1999a). In silage-based dairy cow diets, a D-value around69-70 % is generally recommended in Finland.The development of D-value may not be linear in terms of time, because grass growth isgreatly influenced by weather conditions. Several approaches have been taken to model thechanges of quality in the growing crop (Fick et al. 1994). Cumulative temperature (CT) has provento be an accurate predictor of grass D-value under Finnish conditions (Rinne et al. 1999b, 2000).This paper describes the development of a grass growth model based on field data collected duringfour years. An Advisory Service is based on the model utilising real time weather data. Theestimates are distributed via Internet to assists the farmers in choosing the optimal harvesting dateof grass in primary growth.Material and methodsMixed timothy (Phleum pratense) and meadow fescue (Festuca pratensis) leys weresampled from experimental plots of Agricultural Research Centre and from practical dairy farmsby Valio Ltd. The leys were scattered around Finland and at least 3 data points per each ley wereobtained at no more than one week intervals around the actual harvesting time. The data setcomprised of all together 62 data sets over 4 years (1996-1999) and totalled 258 individualobservations. The D-value of the samples was determined with a cellulase based in vitro incubation(Friedel 1990). CT was obtained from the Finnish Meteorological Institute. CT was accumulatedsince the onset of the growing season, which starts when the mean daily temperature is over 5 °Cfor five consecutive days. CT was calculated as Σ(mean daily temperature - 5) °C. For thegeographical coordinates X and Y (km), the values of the municipality centre were used. Aregression equation for D-value was calculated using SAS MIXED procedure using CT, X andY as fixed factors while the year and each ley within the year were random factors. The followingregression equation was produced:D-value (%) = 86.3 - 0.052 CT - 0.0059 X - 0.0018 Y    (R2 = 0.95 and root MSE = 0.99)Finnish Meteorological Institute provides information of CT real time during the growingseason. Map images presenting regional D-values are produced based on the previous equationand CT using GIS software to cover whole Finland. CT is estimated by interpolation using ARCVIEW SPLINE procedure for a 5 × 5 km grid from data gathered from the network ofmeteorological observatories scattered around Finland. The same accuracy is used to produce themap images. Numerical values for each municipality centre are also provided. D-values arepresented in the map at 1 %-unit intervals ranging from 75 to 65 % (Figure 1). The estimate ofD-value is revised daily. Also forecasts of D-value after 5 days are presented based on threeoptions: the CT development follows a mean rate based on 30 year records, or represents 12.5 %lower or higher percentile of the rate of CT accumulation.Internet provides a media to distribute the information real time to the farmers. The homepage of the Advisory Service (named "Artturi") was placed in the "Agronet" portal which is a non-commercial portal within the agricultural sector in Finland. The Service is freely available at theweb site "http://www.agronet.fi/artturi" starting in June 2000. The language of the site is Finnish.Results and discussionAccording to the equation, D-value decreases by 0.05 % units per each increment of 1 °Cof CT. In June, the average mean daily temperature in Southern Finland is 15 °C meaning that CTincreases by 10 °C daily. Consequently, D-value declines 0.52 percentage unit daily, whichcorresponds well to earlier observations in Finland (Rinne et al. 1999a, 2000). The coefficients forX and Y mean that at the same CT, the D-value decreases by 0.59 percentage unit per 100 kmshift to east and by 0.18 per 100 km shift to north. A theoretical basis for these effects can befound in the systematic changes of the climate. The onset of growing season is postponednorthbound, but the intensity of growth increases at least partly due to longer day light periods.The effect of Y can be interpreted as the effect of shifting from coastal climate in the west towardsmore continental climate in the east, where for example the snow cover is deeper and melts laterin the spring than in the west.The D-value estimate of the current Service is only based on the general CT accumulationand geographical location. Soil type, grass species (especially if forage legumes are included), leymanagement, differences in microclimate and many other factors are likely to cause significantmodifications in grass development. At present, we do not have sufficient data to modify themodel based on these factors. We continue to collect data on grass development to be able tocover certain specific situations. The models including specific site factors could potentially beutilised in the Service by two-way information transfer. Farmers could send information relevantto their grassland management to the Service, and this information could be used in producingindividualized results. In the future, farmers may for example measure CT themselves to controlthe microclimate of their fields. In addition, the onset of growing season could possibly bedetermined by measuring soil temperatures on individual field basis.In conclusion, the Advisory Service described in this paper will improve the ability offarmers to produce forage fitting optimally to the feeding strategy chosen on their farms. Internetprovides a powerful tool to distribute the information to farmers as approximately half of Finnishdairy farmers have access to Internet through their PC's. Time lag and cost are greatly reduced inthe new Service compared to earlier systems based on chemical analyses of field samples andpublishing results in a newspaper. The possible errors in sampling and analysing are also avoided.However, there still remains several important aspects to be studied in the future. Refining themodel based on information from individual fields through two-way information transfer viaInternet is within reach. A great challenge lies in extending the Service to cover the regrowth(s)of grass, which would allow the farmers to optimize their harvesting systems across the wholegrowing period and concerning both quality and quantity of grass. This requires more experimentaldata on grass growth under different harvesting strategies.Finally, we wish to emphasize that the actual decision of harvest remains a responsibilityof the farmer. The decision should be made based on regular observations of the leys and reliesultimately on the professional skills of the farmer.ReferencesFick, G.W., Wilkens, P.W. & Cherney, J.H. (1994). Modeling forage quality changes in thegrowing crop. In: Forage quality, evaluation and utilization. ASS, CSSA & SSSA, Madison,Wisconsin. pp. 757-795.Friedel, K. (1990). Die Schätzung des energetischen Futterwertes von Grobfutter mit Hilfe einerCellulase-methode. Wissenschaftliche Zeitung Universitet Rostock, Nreihe 39: 78-86.Rinne, M., Jaakkola, S., Kaustell, K., Heikkilä, T. and Huhtanen, P. (1999a). Silagesharvested at different stages of grass growth v. concentrate foods as energy and protein sourcesin milk production. Anim. Sci. 69: 251-263.Rinne, M., Hellämäki, M., Nousiainen J., Aura E. and Huhtanen, P. (1999b). Developmentof timothy during progressing growth and subsequent nutritional implications. The XIIthInternational Silage Conference, Uppsala, Sweden, 5-7 July 1999. pp. 166-167.Rinne, M. and Nykänen, A. (2000). Timing of primary growth harvest affects the yield andnutritive value of timothy-red clover mixtures. Agric. Food Sci. Finl. 9: 121-134.Figure 1 - D-value of timothy in Finland on 16 June 1999 estimated with the model described inthe text.

Digestibility Estimates Based on a Grass Growth Model Are Distributed via Internet to Finnish Farmers

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Digestibility Estimates Based on a Grass Growth Model Are Distributed via Internet to Finnish Farmers

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