Introduction:

Assessment of product quality is of special significance in organic farming and includes the supervision of crop quality in different growing systems (e.g., Fleck et al. 1998) and the characterisation of different cultivars. Several methods have been developed and applied for this purpose, e.g., the physico-chemical analysis of crops, picture forming methods (PFMs) and plant observation. So far only limited information is available on the comparability of these methods. This contribution aims to compare the results of the analysis of physico-chemical parameters of summer and autumn carrots with features determined by PFMs by means of correlation analysis.



Conclusions:

High and significant correlation coefficients were found between quality parameters of summer and autumn carrots from a biodynamical breeding project determined by physico-chemical analysis and PFMs. This indicates close relationships between the two quality approaches which should be investigated further in future work

Bauer, D.

Hagel, I.

Haneklaus, S.

Schnug, E.

English

Organic Eprints

  1HAGEL, I., D. BAUER, S. HANEKLAUS and E. SCHNUG (2000): Quality Assessment of Summer and Autumn Carrots from a Bio-dynamic Breeding Project and Correlations of Physico-Chemical Parameters and Features Determined by Picture Forming Methods. Proceedings of the 13th IFOAM Scientific Conference, Basel, Switzerland, 284-287.  Quality Assessment of Summer and Autumn Carrots from a  Biodynamic Breeding Project and Correlations of Physico-Chemical Parameters  and Features Determined by Picture Forming Methods   Ingo Hagel 1, Dietrich Bauer 2, Silvia Haneklaus 3, Ewald Schnug 3  1 Institut für Biologisch-Dynamische Forschung, Brandschneise 5, D-64295 Darmstadt   2 Dottenfelderhof, D-61118 Bad Vilbel 3 Bundesforschungsanstalt für Landwirtschaft, Bundesallee 50, D-38116 Braunschweig  eMail of the corresponding author: Ingo.Hagel@IBDF.de  Keywords: Breeding, Carrot, Picture Forming Methods, Quality   Introduction Assessment of product quality is of special significance in organic farming and includes the supervision of crop quality in different growing systems (e.g., Fleck et al. 1998) and the characterisation of different cultivars. Sev-eral methods have been developed and applied for this purpose, e.g., the physico-chemical analysis of crops, picture forming methods (PFMs) and plant observation. So far only limited information is available on the com-parability of these methods. This contribution aims to compare the results of the analysis of physico-chemical parameters of summer and autumn carrots with features determined by PFMs by means of correlation analysis.  Material and Methods Six summer and eight autumn carrot varieties from biodynamic breeders (D. Bauer, and Th. Heinze) and conven-tional breeders (Sperli, Quedlinburg) including open pollinating cultivars, F1-Hybrids and special selections were tested in a biodynamic breeding project established in 1998. These field experiments were carried out with-out replicates. The following parameters were determined in the plant samples collected at harvest time: dry matter, single carrot weight of autumn varieties, essential plant nutrients (N, NO3, P, K, Mg, S, Ca) and different carbohydrates. Also a decomposition test according to Reinhold (1943) was carried out in order to assess storage quality (Samaras, 1978). Because of a misunderstanding between project partners single carrot weight was only determined for autumn carrots. Quality assessments applying PFMs such as copper chloride cristallisation and chromatography were carried out and quantified from Dr. U. Balzer-Graf (Balzer-Graf, 1999 a and b) according to Balzer-Graf (2000).   Results and Discussion This contribution aims to compare the two methods rather than discussing the individual results obtained. This information is provided by Hagel et al. (2000 a and b) and Balzer-Graf (1999 a and b). The physico-chemical parameters of summer and autumn carrots (table 1 and 2) differed widely as did the results obtained by PFMs (table 3 and 4).  Correlation coefficients of parameters determined by physico-chemical analysis and PFMs are presented in ta-bles 5 and 6. Due to low number of variants per regression (summer carrots: n = 6; autumn carrots: n = 8) some-times even high correlation coefficients failed to turn out significant (e.g., P/Vitality for summer carrots: r = 0.81; fructosis/embryo-like: r = -0.79 (Table 5)). In order to illustrate the potential of relations for future projects using more variants these correlation coefficients were also mentioned in tables 5 and 6.  For summer carrots in general all nutritional elements indicated close relationships to features obtained by PFMs. E.g., for “Ripeness” determined by PFMs and the contents of K, Mg, S and Ca very high correlation coefficients from 0.93** to 0.97** were found (table 5). The closest significant correlation was found for Mg/Differentiation and Mg/Regeneration with r = 0.98 *** (table 5). Of course the strong relationship for Dry Matter/Ripeness (r = 0.87*) appears reasonable. Also the positive relation for % N/Ripeness (r = 0.90*) is con-sistent with findings from Wistinghausen (1979), who carried out time series analyses of carrots. But interest-ingly not for summer carrots (but for autumn carrots!) any significant correlations between parameters from PFMs and “Nitrate” were found (table 5 and 6).  Also the individual carbohydrates were more often correlated with features determined by PFMs in autumn than summer carrots (table 5 and 6). The reason could be related to an increased translocation rate of carbohydrates to the roots (as measured by content of dry matter) in autumn carrots due to the longer vegetation period (table 1 and 2). On the other hand a less pronounced relationship between mineral elements and PFMs in autumn carrots compared to summer carrots was found. With increasing single carrot weight the autumn carrots were judged more “Fruit-like” (r = 0.95***) and less “Vegetative” (r = -0.94***) by PFMs (table 6).    2Table 1.: Mean content of dry matter (DM), loss of DM (%) in the decomposition test (DCT), N in % FM1 (N), nitrate in ppm FM (NO3), nutrient elements (ppm in FM), carbohydrates in FM (%): glucosis (GLU), fructosis (FRU), monosaccharides in (MS), saccharosis in (SAC), total sugar (TS), monosaccharides:disaccharides (Mo:Di) of summer carrots in a biodynamic breeding project.   Summer Carrots  DM DCT N  NO3 P  K  Mg S    Ca  GLU FRU MS  SAC TS  Mo:DiMICHEL (Bauer2)  12.1  56  0.16 115 359  2333 131  226  469 1.67 1.30 2.97 2.83 5.79  1.05 MICHEL  (Sperli)  10.5  53  0.12 155 273  1976 125  189  419 2.15 1.70 3.85 2.02 5.87  1.91 FRÜHBUND  (Bauer)  12.1  51  0.14 156 259  2271 125  228  422 2.06 1.66 3.72 2.94 6.67  1.27 FRÜHBUND  (Sperli)  10.8  46  0.12 186 258  1941 117  179  385 2.15 1.76 3.92 2.28 6.19  1.72 Mean of OP3 Cultivars  11.4 52  0.14 153 287 2130 124 206  424  2.01 1.61 3.62 2.52 6.13 1.49                      ANGLIA  F1  9.8  49  0.11 137 229  1632  98  155  359 2.35 1.73 4.08 2.02 6.10  2.03 NANDA  F1  11.0  48  0.12 128 249  1695 104  158  393 2.24 1.62 3.86 2.85 6.72  1.35 Mean of Hybrids  10,4 49  0,12 133 239 1663 101 157  376  2,30 1,68 3,98 2,44 6,41 1,69   Table 2.: Mean content of dry matter (DM), single carrot weight (SCW), % loss of DM in decomposition test (DCT), % N in FM1 (N), ppm nitrate in FM (NO3), nutrient elements (ppm in FM), carbohydrates in FM (%): glucosis (GLU), fructosis (FRU), monosaccharides (MS), saccharosis (SAC), total sugar (TS), monosaccha-rides:disaccharides (Mo:Di) of autumn carrots from a biodynamic breeding project.   Autumn Carrots  DM SCW DCT N  NO3 Ca  K  P  S  Mg GLU FRU MS  SAC TS  Mo:DiRODELIKA 97 (Bauer2)  14.6  143 41   0.15 80 441  2295 329 191  131  0.60 0.51 1.11 7.47 8.58  0.15 RODELIKA  97  NUSSIG  (Bauer)  12.7  165 37   0.15 91 381  2492 284 158  119  1.30 1.08 2.39 4.62 7.00  0.52 ROBILA  (Heinze)  13.1  122 51   0.18 280 464  2590 315 219  154  0.65 0.66 1.31 5.45 6.76  0.42 LANGE ROTE STUMPFE (Quedlinburg2) 12.2  118 52   0.17 235 442  2578 357 212  129  0.92 0.79 1.71 4.24 5.95  0.40 LANGE ROTE STUMPFE (Bauer)  11.8 108 55  0.15 369 467 2589  297 194 118 1.14 0.86 2.00 4.05 6.06 0.49 DUWICKA   11.1 53 64  0.14 223 310 3158  334 138 120 1.70 1.71 3.41 2.81 6.22 1.21 Mean of OP3 Cultivars  12,6 118 50  0,16 213 418 261  319 185 129 1,05 0,94 1,99 4,77 6,76 0,53                      TINO  F1  10.1  74 45   0.12 211 430  1421 202 164  130  1.37 1.07 2.44 3.22 5.67  0.76 NEVIS  F1  10.1  87 38   0.11 349 385  1901 241 145  94  1.40 1.11 2.50 2.93 5.43  0.85 Mean of Hybrids  10,1 67 42  0,12 280 408 1661  222 155 112 1,39 1,09 2,47 3,08 5,55 0,81  1 FM fresh matter; 2 breeder, 3 OP = open pollinating    3Table 3.: Quality parameters according to picture forming methods of summer carrots from a biodynamic breed-ing project. Index ranging from 0 (very low) to 100 (very high). (from Balzer-Graf, 1999)    Carrot  Differen-   Ripe- Regene- Embryo- Vege-    Leaf-Summer Carrots  typical  tiation  Vitality ness ration  like  tative  Dying  like MICHEL (Bauer1) 60 50 70  80  60 40  0 10  0 MICHEL (Sperli1) 60 45 55  60  40  0  0 20  0 FRÜHBUND (Bauer) 50  45  60  70  40  30  0  0  20 FRÜHBUND (Sperli) 50  40  45  50  30  0  10  0  10 ANGLIA F1  30  20  20  20  0  0  40  50  0 NANDA F1  40  20  40  40  0  0  40  40  0 1 breeder                 Table 4.: Quality parameters according to Picture Forming Methods of autumn carrots from a biodynamic breeding project. Index ranging from 0 (very low) to 100 (very high). (from Balzer-Graf, 1999)   Carrot Differen-   Fruit- Root- Stabi-  Vege-   Autumn Carrots  typical tiation  Vitality like  like  Lity  Tative  Ageing RODELIKA 97 (Bauer1) 80  80  70  90  80  60  0  0 RODELIKA 97 NUSSIG (Bauer)  80  70  70  80  80  60  0  20 ROBILA (Heinze1) 70  60  70  60  60  50  0  20 LRSt2 (Quedlinburg1)  50 50 60  50  60  50  20 20 LRSt2  (Bauer)  40 40 50  40  40  40  30 30 DUWICKA    40 80 60  0  60  50  60 20 TINO  F1  20 10 30  20  20  20  60 60 NEVIS  F1  30 20 40  20  20  30  60 60 1 breeder; 2 LRSt = LANGE ROTE STUMPFE                   Table 5.: Correlation coefficients for the relationships between parameters of physico-chemical analysis and picture forming methods of summer carrots in a biodynamic breeding project.  Number of variants per regression: n = 6. Statistical significances: p < 0.05 (*); p < 0.01 (**); p<0.001 (***)     Carrot-  Differen-    Ripe-   Regene- Embryo- Vege-      Leaf-    typical  tiation  Vitality  ness  ration  like  tative  Dying  like DM      0.65    0.86 *    0.87 *    0.70    0.88 *   -0.61   -0.69    DCT    0.63    0.63    0.71    0.71    0.73    0.75   -0.69       N    0.69    0.76    0.88 *    0.90 *    0.86 *    0.96 **      -0.60    NO3                         P    0.74 *    0.70    0.81    0.80    0.82 *    0.76   -0.60       K    0.79    0.92 *    0.93 **    0.96 **    0.94 **    0.88 *   -0.89 *   -0.82 *    Mg    0.95 **    0.98 ***    0.96 **    0.97 **    0.98 ***   0.68   -0.97 **   -0.82 *    S    0.72    0.88 *    0.90 *    0.93 **    0.90 *    0.90 *   -0.86 *   -0.77    Ca    0.84 *    0.80    0.95 **    0.94 **    0.88 *    0.82 *   -0.74       Glucosis   -0.75   -0.77   -0.88 *   -0.88 *   -0.87 *   -0.87 *    0.68       Fructosis        -0.64   -0.62      -0.79          Saccharosis                 0.70          Total Sugar                         Mo:Di         -0.71   -0.70      -0.81           Only correlation coefficients > ±0.50 are listed   Different characteristics between the two sets of carrot variants were also noticed with regard to relations be-tween the decomposition test (DCT) and PFM parameters. Only summer carrots showed reasonably high (though not significant) correlation coefficients from 0.63 to 0.75 (table 5). In contrast for autumn carrots all correlation coefficients were below 0.50 (therefore not shown in table 6).     4The very often high and significant correlations between physico-chemical parameters and features determined by PFMs are striking and underline the technical accuracy of both methods. The results clearly confirm PFMs as a suitable tool for quality assessment which provide reliable results. This is also corroborated by the investiga-tions of Balzer-Graf (2000) who showed that it is possible to distinguish crops from different growing systems by PFMs.   Table 6.: Correlation for the relationship between parameters of physico-chemical analysis and picture forming methods of autumn carrots in a biodynamic breeding project.  Number of variants per regression: n = 8. Statistical significances: p < 0.05 (*); p < 0.01 (**); p<0.001 (***)     Carrot  Differen-    Fruit- Root-  Stabi-  Vege-      typical  tiation  Vitality like  like  lity  tative  Ageing SCW    0.87 **       0.68    0.95 ***    0.67    0.66   -0.94 ***   -0.55 DM    0.92 **    0.75 *    0.86 **    0.88 **    0.86 **    0.84 *  -0.91 **   -0.90** DCT                     N      0.55    0.53       0.63    0.65     -0.71 * NO3   -0.78 **   -0.61   -0.68   -0.71 *   -0.74 *   -0.63    0.68    0.60 P    0.54    0.78 *    0.78 *       0.73 *    0.80 *    -0.86 ** K      0.67    0.73 *       0.54    0.61     -0.62 Mg                     S           0.55        -0.60    Ca                       Glucosis   -0.59        -0.79 *         0.74*    0.55 Fructosis          -0.68         0.58    Saccharosis    0.80 *    0.54    0.65    0.87 **    0.69    0.65   -0.81 *   -0.73 * Total Sugar    0.86 **    0.74 *    0.75 *    0.79 *    0.80 *    0.76 *  -0.76 *   -0.81 * Mono:Di   -0.65         -0.89 **          0.84 **     Only correlation coefficients > ±0.50 are listed  Conclusions High and significant correlation coefficients were found between quality parameters of summer and autumn carrots from a biodynamical breeding project determined by physico-chemical analysis and PFMs. This indicates close relationships between the two quality approaches which should be investigated further in future work.   References Balzer-Graf, U. (1987): Vitalaktivität von Nahrungsmitteln im Spiegel bildschaffender Methoden. Elemente der Naturwissenschaft, Nr.46, 69-92. Balzer-Graf, U. (1999 a): Vitalqualität von Populations- und Hybridsorten bei Frühmöhren. Bericht zu Untersu-chungen im Auftrag von Dietrich Bauer.  Balzer-Graf, U. (1999 b): Vitalqualität von Populations- und Hybridsorten bei Lagermöhren. Bericht zu Unter-suchungen im Auftrag von Dietrich Bauer.  Balzer-Graf, U. (2000): Vitalquality. Quality Research with Picture Forming Methods. In: Lockeretz, W. and Geier, B. (Eds.), Quality and Communications for the organic Market, IFOAM, 179-188.  Fleck, M., I. Hagel und A. Meier-Ploeger (1998): Lagerfähigkeit und Inhaltsstoffe von Möhren aus der biolo-gisch-dynamischen und konventionellen Praxis. Deutsche Gesellschaft für Qualitätsforschung (Pflanzliche Nah-rungsmittel) e.V., XXXIII. Vortragstagung, 23./24. März 1998, Dresden, 217-222. Hagel, I., D. Bauer,  S. Haneklaus und E. Schnug (2000): Zur Qualität von Frühmöhren aus einem biologisch-dynamischen Züchtungsprojekt. Deutsche Gesellschaft für Qualitätsforschung e.V., XXXV. Vortragstagung, 20./21. März 2000, Karlsruhe (im Druck). Hagel, I., D. Bauer,  S. Haneklaus und E. Schnug (2000): Zur Qualität von Herbstmöhren aus einem biologisch-dynamischen Züchtungsprojekt. Deutsche Gesellschaft für Qualitätsforschung e.V., XXXV. Vortragstagung, 20./21. März 2000, Karlsruhe (im Druck). Reinhold, J. (1943): Die Haltbarkeit von Gemüse, ein wichtiger Qualitätsfaktor. Z. Pflanzenkrankh. PflSchutz 53, 175-199.  Samaras, I. (1978): Nachernteverhalten unterschiedlich gedüngter Gemüsearten mit besonderer Berück-sichtigung physiologischer und mikrobiologischer Parameter. Diss., Gießen. WISTINGHAUSEN, E. v. (1979): Was ist Qualität? Wie entsteht sie und wie ist sie nachzuweisen? Verlag "Le-bendige Erde", Darmstadt. Bibliographische Angaben zu diesem Dokument:   Hagel, I. und Bauer, D. und Haneklaus, S. und Schnug, E. (2000) Quality Assessment of Summer and Autumn Carrots from a Biodynamic Breeding Project and Correlations of Physico-Chemical Parameters and Features Determined by Picture Forming Methods. Beitrag präsentiert bei der Konferenz: 13th IFOAM Scientific Conference, Basel, 28.08.2000 - 31.08.2000; Veröffentlicht in Alföldi, Thomas und Lockeretz, William und Niggli, Urs, (Hrsg.) Proceedings 13th International IFOAM Scientific Conference, Seite(n) 284-287. IFOAM.  Das Dokument ist in der Datenbank „Organic Eprints“ archiviert und kann im Internet unter http://orgprints.org/00002191 abgerufen werden. 

Quality Assessment of Summer and Autumn Carrots from a Biodynamic Breeding Project and Correlations of Physico-Chemical Parameters and Features Determined by Picture Forming Methods

Assessment of product quality is of special significance in organic farming and includes the supervision of crop quality in different growing systems and the characterisation of different cultivars. Several methods have been developed and applied for this purpose, e.g., the physico-chemical analysis of crops, picture forming methods (PFMs) and plant observation. So far only limited information is available on the com-parability of these methods. This contribution aims to compare the results of the analysis of physico-chemical parameters of summer and autumn carrots with features determined by PFMs by means of correlation analysis. High and significant correlation coefficients were found between quality parameters of summer and autumn carrots from a biodynamical breeding project determined by physico-chemical analysis and PFMs. This indicates close relationships between the two quality approaches which should be investigated further in future work

Hagel, Ingo

Bauer, Dieter

Haneklaus, Silvia

Schnug, Ewald

Proceedings of the 13th IFOAM Scientific Conference, Basel, Switzerland, 284-287.  Quality Assessment of Summer and Autumn Carrots from a  Biodynamic Breeding Project and Correlations of Physico-Chemical Parameters  and Features Determined by Picture Forming Methods   Ingo Hagel 1, Dietrich Bauer 2, Silvia Haneklaus 3, Ewald Schnug 3  1 Institut für Biologisch-Dynamische Forschung, Brandschneise 5, D-64295 Darmstadt   2 Dottenfelderhof, D-61118 Bad Vilbel 3 Bundesforschungsanstalt für Landwirtschaft, Bundesallee 50, D-38116 Braunschweig   Keywords: Breeding, Carrot, Picture Forming Methods, Quality   Introduction Assessment of product quality is of special significance in organic farming and includes the supervision of crop quality in different growing systems (e.g., Fleck et al. 1998) and the characterisation of different cultivars. Sev-eral methods have been developed and applied for this purpose, e.g., the physico-chemical analysis of crops, picture forming methods (PFMs) and plant observation. So far only limited information is available on the com-parability of these methods. This contribution aims to compare the results of the analysis of physico-chemical parameters of summer and autumn carrots with features determined by PFMs by means of correlation analysis.  Material and Methods Six summer and eight autumn carrot varieties from biodynamic breeders (D. Bauer, and Th. Heinze) and conven-tional breeders (Sperli, Quedlinburg) including open pollinating cultivars, F1-Hybrids and special selections were tested in a biodynamic breeding project established in 1998. These field experiments were carried out with-out replicates. The following parameters were determined in the plant samples collected at harvest time: dry matter, single carrot weight of autumn varieties, essential plant nutrients (N, NO3, P, K, Mg, S, Ca) and different carbohydrates. Also a decomposition test according to Reinhold (1943) was carried out in order to assess storage quality (Samaras, 1978). Because of a misunderstanding between project partners single carrot weight was only determined for autumn carrots. Quality assessments applying PFMs such as copper chloride cristallisation and chromatography were carried out and quantified from Dr. U. Balzer-Graf (Balzer-Graf, 1999 a and b) according to Balzer-Graf (2000).   Results and Discussion This contribution aims to compare the two methods rather than discussing the individual results obtained. This information is provided by Hagel et al. (2000 a and b) and Balzer-Graf (1999 a and b). The physico-chemical parameters of summer and autumn carrots (table 1 and 2) differed widely as did the results obtained by PFMs (table 3 and 4).   Correlation coefficients of parameters determined by physico-chemical analysis and PFMs are presented in ta-bles 5 and 6. Due to low number of variants per regression (summer carrots: n = 6; autumn carrots: n = 8) some-times even high correlation coefficients failed to turn out significant (e.g., P/Vitality for summer carrots:            r = 0.81; fructosis/embryo-like: r = -0.79 (Table 5)). In order to illustrate the potential of relations for future projects using more variants these correlation coefficients were also mentioned in tables 5 and 6.   For summer carrots in general all nutritional elements indicated close relationships to features obtained by PFMs. E.g., for “Ripeness” determined by PFMs and the contents of K, Mg, S and Ca very high correlation coefficients from 0.93** to 0.97** were found (table 5). The closest significant correlation was found for Mg/Differentiation and Mg/Regeneration with r = 0.98 *** (table 5). Of course the strong relationship for Dry Matter/Ripeness (r = 0.87*) appears reasonable. Also the positive relation for % N/Ripeness (r = 0.90*) is con-sistent with findings from Wistinghausen (1979), who carried out time series analyses of carrots. But interest-ingly not for summer carrots (but for autumn carrots!) any significant correlations between parameters from PFMs and “Nitrate” were found (table 5 and 6).   Also the individual carbohydrates were more often correlated with features determined by PFMs in autumn than summer carrots (table 5 and 6). The reason could be related to an increased translocation rate of carbohydrates to the roots (as measured by content of dry matter) in autumn carrots due to the longer vegetation period (table 1 and 2). On the other hand a less pronounced relationship between mineral elements and PFMs in autumn carrots compared to summer carrots was found. With increasing single carrot weight the autumn carrots were judged more “Fruit-like” (r = 0.95***) and less “Vegetative” (r = -0.94***) by PFMs (table 6).  Table 1.: Mean content of dry matter (DM), loss of DM (%) in the decomposition test (DCT), N in % FM1 (N), nitrate in ppm FM (NO3), nutrient elements (ppm in FM), carbohydrates in FM (%): glucosis (GLU), fructosis (FRU), monosaccharides in (MS), saccharosis in (SAC), total sugar (TS), monosaccharides:disaccharides (Mo:Di) of summer carrots in a biodynamic breeding project.   Summer Carrots  DM DCT N  NO3 P  K  Mg S    Ca  GLU FRU MS  SAC TS  Mo:DiMICHEL (Bauer2)  12.1  56  0.16 115 359  2333 131  226  469 1.67 1.30 2.97 2.83 5.79  1.05 MICHEL  (Sperli)  10.5  53  0.12 155 273  1976 125  189  419 2.15 1.70 3.85 2.02 5.87  1.91 FRÜHBUND  (Bauer)  12.1  51  0.14 156 259  2271 125  228  422 2.06 1.66 3.72 2.94 6.67  1.27 FRÜHBUND  (Sperli)  10.8  46  0.12 186 258  1941 117  179  385 2.15 1.76 3.92 2.28 6.19  1.72 Mean of OP3 Cultivars  11.4 52  0.14 153 287 2130 124 206  424  2.01 1.61 3.62 2.52 6.13 1.49                      ANGLIA  F1  9.8  49  0.11 137 229  1632  98  155  359 2.35 1.73 4.08 2.02 6.10  2.03 NANDA  F1  11.0  48  0.12 128 249  1695 104  158  393 2.24 1.62 3.86 2.85 6.72  1.35 Mean of Hybrids  10,4 49  0,12 133 239 1663 101 157  376  2,30 1,68 3,98 2,44 6,41 1,69   Table 2.: Mean content of dry matter (DM), single carrot weight (SCW), % loss of DM in decomposition test (DCT), % N in FM1 (N), ppm nitrate in FM (NO3), nutrient elements (ppm in FM), carbohydrates in FM (%): glucosis (GLU), fructosis (FRU), monosaccharides (MS), saccharosis (SAC), total sugar (TS), monosaccha-rides:disaccharides (Mo:Di) of autumn carrots from a biodynamic breeding project.   Autumn Carrots  DM SCW DCT N  NO3 Ca  K  P  S  Mg GLU FRU MS  SAC TS  Mo:DiRODELIKA 97 (Bauer2)  14.6  143 41   0.15 80 441  2295 329 191  131  0.60 0.51 1.11 7.47 8.58  0.15 RODELIKA  97  NUSSIG  (Bauer)  12.7  165 37   0.15 91 381  2492 284 158  119  1.30 1.08 2.39 4.62 7.00  0.52 ROBILA  (Heinze)  13.1  122 51   0.18 280 464  2590 315 219  154  0.65 0.66 1.31 5.45 6.76  0.42 LANGE ROTE STUMPFE (Quedlinburg2) 12.2  118 52   0.17 235 442  2578 357 212  129  0.92 0.79 1.71 4.24 5.95  0.40 LANGE ROTE STUMPFE (Bauer)  11.8 108 55  0.15 369 467 2589  297 194 118 1.14 0.86 2.00 4.05 6.06 0.49 DUWICKA   11.1 53 64  0.14 223 310 3158  334 138 120 1.70 1.71 3.41 2.81 6.22 1.21 Mean of OP3 Cultivars  12,6 118 50  0,16 213 418 261  319 185 129 1,05 0,94 1,99 4,77 6,76 0,53                      TINO  F1  10.1  74 45   0.12 211 430  1421 202 164  130  1.37 1.07 2.44 3.22 5.67  0.76 NEVIS  F1  10.1  87 38   0.11 349 385  1901 241 145  94  1.40 1.11 2.50 2.93 5.43  0.85 Mean of Hybrids  10,1 67 42  0,12 280 408 1661  222 155 112 1,39 1,09 2,47 3,08 5,55 0,81  1 FM fresh matter; 2 breeder, 3 OP = open pollinating  Table 3.: Quality parameters according to picture forming methods of summer carrots from a biodynamic breed-ing project. Index ranging from 0 (very low) to 100 (very high). (from Balzer-Graf, 1999)    Carrot  Differen-   Ripe- Regene- Embryo- Vege-    Leaf-Summer Carrots  typical  tiation  Vitality ness ration  like  tative  Dying  like MICHEL (Bauer1) 60 50 70  80  60 40  0 10  0 MICHEL (Sperli1) 60 45 55  60  40  0  0 20  0 FRÜHBUND (Bauer) 50  45  60  70  40  30  0  0  20 FRÜHBUND (Sperli) 50  40  45  50  30  0  10  0  10 ANGLIA F1  30  20  20  20  0  0  40  50  0 NANDA F1  40  20  40  40  0  0  40  40  0 1 breeder                 Table 4.: Quality parameters according to Picture Forming Methods of autumn carrots from a biodynamic breeding project. Index ranging from 0 (very low) to 100 (very high). (from Balzer-Graf, 1999)   Carrot Differen-   Fruit- Root- Stabi-  Vege-   Autumn Carrots  typical tiation  Vitality like  like  Lity  Tative  Ageing RODELIKA 97 (Bauer1) 80  80  70  90  80  60  0  0 RODELIKA 97 NUSSIG (Bauer)  80  70  70  80  80  60  0  20 ROBILA (Heinze1) 70  60  70  60  60  50  0  20 LRSt2 (Quedlinburg1)  50 50 60  50  60  50  20 20 LRSt2  (Bauer)  40 40 50  40  40  40  30 30 DUWICKA    40 80 60  0  60  50  60 20 TINO  F1  20 10 30  20  20  20  60 60 NEVIS  F1  30 20 40  20  20  30  60 60 1 breeder; 2 LRSt = LANGE ROTE STUMPFE                   Table 5.: Correlation coefficients for the relationships between parameters of physico-chemical analysis and picture forming methods of summer carrots in a biodynamic breeding project.  Number of variants per regression: n = 6. Statistical significances: p < 0.05 (*); p < 0.01 (**); p<0.001 (***)     Carrot-  Differen-    Ripe-   Regene- Embryo- Vege-      Leaf-    typical  tiation  Vitality  ness  ration  like  tative  Dying  like DM      0.65    0.86 *    0.87 *    0.70    0.88 *   -0.61   -0.69    DCT    0.63    0.63    0.71    0.71    0.73    0.75   -0.69       N    0.69    0.76    0.88 *    0.90 *    0.86 *    0.96 **      -0.60    NO3                         P    0.74 *    0.70    0.81    0.80    0.82 *    0.76   -0.60       K    0.79    0.92 *    0.93 **    0.96 **    0.94 **    0.88 *   -0.89 *   -0.82 *    Mg    0.95 **    0.98 ***    0.96 **    0.97 **    0.98 ***   0.68   -0.97 **   -0.82 *    S    0.72    0.88 *    0.90 *    0.93 **    0.90 *    0.90 *   -0.86 *   -0.77    Ca    0.84 *    0.80    0.95 **    0.94 **    0.88 *    0.82 *   -0.74       Glucosis   -0.75   -0.77   -0.88 *   -0.88 *   -0.87 *   -0.87 *    0.68       Fructosis        -0.64   -0.62      -0.79          Saccharosis                 0.70          Total Sugar                         Mo:Di         -0.71   -0.70      -0.81           Only correlation coefficients > ±0.50 are listed   Different characteristics between the two sets of carrot variants were also noticed with regard to relations be-tween the decomposition test (DCT) and PFM parameters. Only summer carrots showed reasonably high (though not significant) correlation coefficients from 0.63 to 0.75 (table 5). In contrast for autumn carrots all correlation coefficients were below 0.50 (therefore not shown in table 6).   The very often high and significant correlations between physico-chemical parameters and features determined by PFMs are striking and underline the technical accuracy of both methods. The results clearly confirm PFMs as a suitable tool for quality assessment which provide reliable results. This is also corroborated by the investiga-tions of Balzer-Graf (2000) who showed that it is possible to distinguish crops from different growing systems by PFMs.   Table 6.: Correlation for the relationship between parameters of physico-chemical analysis and picture forming methods of autumn carrots in a biodynamic breeding project.  Number of variants per regression: n = 8. Statistical significances: p < 0.05 (*); p < 0.01 (**); p<0.001 (***)     Carrot  Differen-    Fruit- Root-  Stabi-  Vege-      typical  tiation  Vitality like  like  lity  tative  Ageing SCW    0.87 **       0.68    0.95 ***    0.67    0.66   -0.94 ***   -0.55 DM    0.92 **    0.75 *    0.86 **    0.88 **    0.86 **    0.84 *  -0.91 **   -0.90** DCT                     N      0.55    0.53       0.63    0.65     -0.71 * NO3   -0.78 **   -0.61   -0.68   -0.71 *   -0.74 *   -0.63    0.68    0.60 P    0.54    0.78 *    0.78 *       0.73 *    0.80 *    -0.86 ** K      0.67    0.73 *       0.54    0.61     -0.62 Mg                     S           0.55        -0.60    Ca                       Glucosis   -0.59        -0.79 *         0.74*    0.55 Fructosis          -0.68         0.58    Saccharosis    0.80 *    0.54    0.65    0.87 **    0.69    0.65   -0.81 *   -0.73 * Total Sugar    0.86 **    0.74 *    0.75 *    0.79 *    0.80 *    0.76 *  -0.76 *   -0.81 * Mono:Di   -0.65         -0.89 **          0.84 **     Only correlation coefficients > ±0.50 are listed  Conclusions High and significant correlation coefficients were found between quality parameters of summer and autumn carrots from a biodynamical breeding project determined by physico-chemical analysis and PFMs. This indicates close relationships between the two quality approaches which should be investigated further in future work.   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Quality Assessment of Summer and Autumn Carrots from a Biodynamic Breeding Project and Correlations of Physico-Chemical Parameters and Features determined by Picture Forming Methods

Quality Assessment of Summer and Autumn Carrots from a Biodynamic Breeding Project and Correlations of Physico-Chemical Parameters and Features Determined by Picture Forming Methods

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