Precisionsodling av vall
Cultivated grassland is an important crop, both considering crop sequence and live- stock keeping. It is cultivated on 45 % of the Swedish arable land, but it is a crop that differs from grains regarding time of harvest, number of harvests and composi- tion of species. In other crops e.g. wheat an...
| Autor principal: | |
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| Formato: | First cycle, G2E |
| Lenguaje: | sueco sueco |
| Publicado: |
2017
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| Materias: | |
| Acceso en línea: | https://stud.epsilon.slu.se/12831/ |
| _version_ | 1855572139767234560 |
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| author | Hellstedt, Emma |
| author_browse | Hellstedt, Emma |
| author_facet | Hellstedt, Emma |
| author_sort | Hellstedt, Emma |
| collection | Epsilon Archive for Student Projects |
| description | Cultivated grassland is an important crop, both considering crop sequence and live-
stock keeping. It is cultivated on 45 % of the Swedish arable land, but it is a crop that differs from grains regarding time of harvest, number of harvests and composi-
tion of species. In other crops e.g. wheat and barley, it is possible to estimate bio-
mass and nitrogen demand since the early 00’s using remote sensing technology. But due to the unique properties of ley, the technology cannot be applied with ease.
There are a few ongoing Swedish projects where the correlation between remote sensing and ley properties is studied. One is at the experimental station in Rådde,
which is where the data analysed in this report come from. In this particular field experiment, four different ley compositions are considered: three strict, different grasslands and one containing clover and grass. Five different amounts of nitrogen fertilizer have been applied to one of the grasses and to the mixed ley field. In con-
nection to all three harvests, an N-sensor has been used to measure hyper spectral reflectance data. In this work the correlation between reflection and biomass, TS, raw protein content and protein amount have been examined by using two methods.
The first one looks into single linear regression between the measured data and four
vegetation indices (VI), and the second method uses Partial Least Squares regres-
sion (PLS) with hyperspectral data, 400-900nm. The multivariate PLS models were validated by cross validation.
The results show that there are relationships between remote sensing and meas-
ured data – where the strongest correlations can be found between hyperspectral
data and protein amount in grasses. Among the studied VI’s, the ones based on green wavelength bands yielded the highest correlations. Also, it can be noted that
the ley containing clover had low correlations regarding all examined properties.
When forming models with PLS, the highest correlations could be seen with the
protein amount and raw protein content. Besides, it gets clear that the sensor used in
this study makes a good estimation of the share of clover.
Despite the facts that hyperspectral data yields higher correlations than using VI’s, but also that the correlations were high in cultivated grass, more research has
to be done in order to make further general conclusions. |
| format | First cycle, G2E |
| id | RepoSLU12831 |
| institution | Swedish University of Agricultural Sciences |
| language | Swedish swe |
| publishDate | 2017 |
| publishDateSort | 2017 |
| record_format | eprints |
| spelling | RepoSLU128312017-11-01T08:37:22Z https://stud.epsilon.slu.se/12831/ Precisionsodling av vall Hellstedt, Emma Fertilizing Plant physiology - Nutrition Agricultural machinery and equipment Cultivated grassland is an important crop, both considering crop sequence and live- stock keeping. It is cultivated on 45 % of the Swedish arable land, but it is a crop that differs from grains regarding time of harvest, number of harvests and composi- tion of species. In other crops e.g. wheat and barley, it is possible to estimate bio- mass and nitrogen demand since the early 00’s using remote sensing technology. But due to the unique properties of ley, the technology cannot be applied with ease. There are a few ongoing Swedish projects where the correlation between remote sensing and ley properties is studied. One is at the experimental station in Rådde, which is where the data analysed in this report come from. In this particular field experiment, four different ley compositions are considered: three strict, different grasslands and one containing clover and grass. Five different amounts of nitrogen fertilizer have been applied to one of the grasses and to the mixed ley field. In con- nection to all three harvests, an N-sensor has been used to measure hyper spectral reflectance data. In this work the correlation between reflection and biomass, TS, raw protein content and protein amount have been examined by using two methods. The first one looks into single linear regression between the measured data and four vegetation indices (VI), and the second method uses Partial Least Squares regres- sion (PLS) with hyperspectral data, 400-900nm. The multivariate PLS models were validated by cross validation. The results show that there are relationships between remote sensing and meas- ured data – where the strongest correlations can be found between hyperspectral data and protein amount in grasses. Among the studied VI’s, the ones based on green wavelength bands yielded the highest correlations. Also, it can be noted that the ley containing clover had low correlations regarding all examined properties. When forming models with PLS, the highest correlations could be seen with the protein amount and raw protein content. Besides, it gets clear that the sensor used in this study makes a good estimation of the share of clover. Despite the facts that hyperspectral data yields higher correlations than using VI’s, but also that the correlations were high in cultivated grass, more research has to be done in order to make further general conclusions. Vall odlas på 45 % av Sveriges åkerareal och vallen är en viktig gröda både ur växt- följdssynpunkt och för djurhållning. Det är också en gröda som skiljer sig från spannmålen genom skördetidpunkt, antal skördar och artsammansättning. I andra grödor som vete och korn finns sen 00-talet optiska sensorer som kan läsa av bio- massa och kvävebehov i grödan, men på grund av vallens unika egenskaper kan inte tekniken med lätthet överföras till vall. Det finns några försök i Sverige med syfte att kartlägga sambanden mellan sensormätning och egenskaper i vallen. I det här arbetet presenteras data från ett pågående fältförsök i vall på Rådde försöksstation. Försöket består av tre gräsvallar och en blandvall varav en av gräsvallarna och blandvallen har fått fem olika N-givor. I samband med tre olika skördar har vi med en hyperspektral N-sensor mätt reflektansen från varje försök och i det här arbetet undersöks sambandet mellan reflektansen och biomassa, ts, råproteinhalt och prote- inmängd genom två metoder. Dels genom en enkel linjär korrelation mellan fyra olika vegetationsindex (VI) och dels genom en multivariat linjär korrelation, Partial Least Squares regression (PLS), med hyperspektral data mellan 400-900 nm. Sam- banden mellan hyperspektral data och analysvärdena användes i modeller som tes- tades genom korsvalidering. Resultaten från sammanställningen visar att det fanns samband mellan sensor- mätning och analysdata där de starkaste sambanden fanns mellan hyperspektral data och proteinmängd i gräsvallar. Bland VI var de innehållande gröna våglängder som gav starkast korrelation med samtliga analysvärden men generellt var korrelationen i blandvallarna svag. Vid skapandet av modeller utifrån sambanden var det prote- inmängd och proteinhalt som gav högst r2-värde vid en validering och även sam- bandet mellan sensormätning och klöverandelen visade att en sensor i den här stu- dien kunde läsa av mängden klöver med god korrelation. Trots att hyperspektral data gav starkare korrelation än VI och trots att korrelat- ionerna överlag var starka i gräsvallarna behövs ytterligare försök för att kunna dra några generella slutsatser. 2017-10-31 First cycle, G2E NonPeerReviewed application/pdf sv https://stud.epsilon.slu.se/12831/1/hellstedt_e_171031.pdf Hellstedt, Emma, 2017. Precisionsodling av vall : sensormätning som analysredskap för proteininnehåll och skörd. First cycle, G2E. Uppsala: (NL, NJ) > Dept. of Soil and Environment <https://stud.epsilon.slu.se/view/divisions/OID-435.html> urn:nbn:se:slu:epsilon-s-8482 swe |
| spellingShingle | Fertilizing Plant physiology - Nutrition Agricultural machinery and equipment Hellstedt, Emma Precisionsodling av vall |
| title | Precisionsodling av vall |
| title_full | Precisionsodling av vall |
| title_fullStr | Precisionsodling av vall |
| title_full_unstemmed | Precisionsodling av vall |
| title_short | Precisionsodling av vall |
| title_sort | precisionsodling av vall |
| topic | Fertilizing Plant physiology - Nutrition Agricultural machinery and equipment |
| url | https://stud.epsilon.slu.se/12831/ https://stud.epsilon.slu.se/12831/ |