APPENDIX II

DRAFT AND REVISED DRAFT MAXIMUM RESIDUE LIMITS FOR PESTICIDES
(Advanced to Step 8 of the Codex Procedure)

				MRL (mg/kg)		Step	Note

008 CARBARYL

CM	1207	Rice hulls¹	50		8
AF	1053	Sorghum forage (dry)¹	5		8
AB	0541	Soya bean hulls¹	0.3		8
AV	0702	Sunflower forage¹	5		8
AB	0447	Sweet corn cannery waste¹	7.4		8
VW	0448	Tomate paste¹	10		8
AM	0660	Almond hulls	50		8
VS	0621	Asparagus	15		8
VR	574	Beetroot	0.1		8
VR	577	Carrot	0.5		8
VO	0440	Egg plant	1		8
MO	0098	Kidney of cattle, goats, pigs and sheep	3		8
MO	0099	Liver of cattle, goats, pigs and sheep	1		8
GC	0645	Maize	0.02	(*)	8
AF	0645	Maize forage,	400	dry	8
AS	0645	Maize fodder	250		8
OC	0645	Maize oil, crude	0.1		8
MM	0095	Meat (from mammals other than marine mammals)	0.05		8
ML	0106	Milks	0.05		8
FT	0305	Olives	30		8
OC	0305	Olive oil, virgin	25		8
VO	0445	Peppers, sweet	5		8
CM	1206	Rice bran, unprocessed	170		8
AS	0649	Rice straw and fodder. Dry	120		8
CM	1205	Rice, polished	1		8
AF	0651	Sorghum forage, green	20		8
OC	0541	Soya bean oil, crude	0.2		8
VD	541	Soya bean (dry)	0.2		8
AL	0541	Soya bean fodder	15		8
AL	1265	Soyabean forage (green)	30	Dry wt	8
OC	0802	Sunflower seed oil, crude	0.05		8
VO	0448	Sweet corn, corn on the cob	0.1		8
VR	0508	Sweet potato	0.02	(*)	8
SO	0802	Sunflower seed	0.2		8
VO	0448	Tomato	5		8
JF	0448	Tomato juice	3		8
TN	0085	Tree nuts	1		8
VR	0506	Turnip, Garden	1		8
GC	0654	Wheat	2		8
CF	1211	Wheat flour	0.2		8
CF	1210	Wheat germ	1		8
CM	0654	Wheat bran, unprocessed	2		8
AS	0654	Wheat straw and fodder, dry	30		8

20 2,4-D

0001

Citrus fruits

22 DIAZINON

MM	814	Goat meat	2	(fat)	8
MO	98	Kidney of cattle, goats, pigs and sheep	0.03		8
MO	99	Liver of cattle, goats, pigs and sheep	0.03		8
MM	98	Meat of cattle, pigs and sheep	2	(fat)	8
FP	9	Pome fruits	0.3		8

30 DIPHENYLAMINE

ML	812	Cattle milk	0.0004	(*) F	8
FP	230	Pear	5	Po	8

49 MALATHION

VS	621	Asparagus	1	8
VP	61	Beans, except broad bean and soy bean	1	8
FB	20	Blueberries	10	8
VC	424	Cucumber	0.2	8
VL	485	Mustard greens	2	8
VA	385	Onion, Bulb	1	8
VA	0389	Spring onion	5	8
VO	447	Sweet corn (corn-on-the-cub)	0.02	8
JF	448	Tomato juice	0.01	8
VL	506	Turnip greens	5	8

59 PARATHION-METHYL

FP	226	Apple	0.2	8
VB	41	Cabbages, Head	0.05	8
DF	269	Dried grapes (=currants, raisins and sultanas	1	8
FB	269	Grapes	0.5	8
FS	247	Peach	0.3	8
VD	72	Peas (dry)	0.3	8

62 PIPERONYL BUTOXIDE

MO	1280	Cattle kidney	0.3		8
MO	1281	Cattle liver	1		8
MM	812	Cattle meat	5	(fat)	8
ML	812	Cattle milk	0.2	F	8
GC	80	Cereal Grains	30	Po	8
FC	1	Citrus fruits	5		8
JF	1	Citrus juice	0.05		8
DF	167	Dried fruits	0.2	Po	8
PE	112	Eggs	1		8
VC	45	Fruiting vegetables, Cucurbits	1		8
MO	0098	Kidney of cattle, goats, pigs & sheep	0.2		8	Excluding cattle kidney
VL	483	Lettuce, Leaf	50		8
MO	0099	Liver of cattle, goats, pigs & sheep	1		8
OC	645	Maize oil, Crude	80	PoP	8
MM	0095	Meat (from mammals other than marine mammals)	2		8	Excluding cattle meat
ML	0106	Milks	0.05	F	8	Excluding cattle milk
VL	485	Mustard greens	50		8
AL	72	Pea hay or pea fodder (dry)	200	(dry)	8
AL	528	Pea vines (green)	400	(dry)	8
SO	703	Peanut, Whole	1		8
VO	51	Peppers	2		8
PM	110	Poultry meat	7	(fat)	8
PO	111	Poultry, Edible offal of	10		8
VD	70	Pulses	0.2	Po	8
VL	494	Radish leaves (including radish tops)	50		8
VR	75	Root and tuber vegetables	0.5		8	Except carrot
VL	502	Spinach	50		8
VO	448	Tomato	2		8
JF	448	Tomato juice	0.3		8
CM	654	Wheat bran, Unprocessed	80	PoP	8
CF	1211	Wheat flour	10	PoP	8
CF	1210	Wheat germ	90	PoP	8
CF	1212	Wheat wholemeal	30	PoP	8

79 AMITROLE

FB	0269	Grapes	0.05		8
FP	0009	Pome fruits	0.05	(*)	8
FS	0012	Stone fruits	0.05	(*)	8

85 FENAMIPHOS

FP	226	Apple	0.05	(*)	8
FI	327	Banana	0.05		8
VB	402	Brussels sprouts	0.05		8
VB	41	Cabbages, Head	0.05		8
OC	691	Cotton seed oil, Crude	0.05	(*)	8
MO	105	Edible offal (mammalian)	0.01	(*)	8
PE	112	Eggs	0.01	(*)	8
MM	95	Meat (from mammals other than marine mammals)	0.01	(*)	8
ML	106	Milks	0.005	(*)	8
OC	697	Peanut oil, Crude	0.05	(*)	8
PO	110	Poultry meat	0.01	(*)	8
PO	111	Poultry, Edible offal of	0.01	(*)	8

94 METHOMYL

AB	0691	Cotton seed, hulls¹	0.2		8
AB	1203	Cotton seed, meal¹	0.05		8
AV	0495	Rape seed forage¹	0.2		8
AB	0541	Soya bean hulls¹	1		8
AB	1265	Soy bean meal¹	0.2		8
VD	0071	Beans (dry)	0.05		8
VP	0526	Common bean (pods and/or immature seeds)	1		8

SO	0691	Cotton seed	0.2		8
OR	691	Cotton seed oil, Edible	0.04		8
MO	105	Edible offal (mammalian)	0.02	(*)	8
PE	112	Eggs	0.02	(*)	8
GC	0645	Maize	0.02	(*)	8
AF	0645	Maize forage	50		8
OR	645	Maize oil, Edible	0.02	(*)	8
MM	0095	Meat (from mammals other than marine mammals)	0.02	(*)	8
ML	0106	Milks	0.02	(*)	8
FS	0245	Nectarine	0.2		8
GC	0647	Oats	0.02	(*)	8
FS	0247	Peach	0.2		8
FS	14	Plums (including prunes)	1		8
VR	0589	Potato	0.02	(*)	8
PM	110	Poultry meat	0.02	(*)	8
PO	111	Poultry, Edible offal of	0.02	(*)	8
SO	495	Rape seed	0.05		8
AL	541	Soya bean fodder	0.2		8
OC	541	Soya bean oil, Crude	0.2		8
OR	541	Soya bean oil, Refined	0.2		8
AS	161	Straw, fodder (dry) and hay of cereal grains and other grass-like plants	10		8

96 CARBOFURAN


SO	0691	Cotton seed	0.1		8
SO	0495	Rape seed	0.05	(*)	8
AS	0649	Rice straw and fodder (dry)	1		8
CM	0649	Rice, husked	0.1		8

103 PHOSMET

0085

Tree nuts

0.2

113 PROPARGITE

AM	0838	Almond hulls	50		8
TN	0660	Almonds	0.1	(*)	8
FP	0226	Apple	3		8
JF	0226	Apple juice	0.2		8
FC	0001	Citrus fruits	3		8
AB	0001	Citrus pulp, dry	10		8
SO	0691	Cotton seed	0.1		8
OR	0691	Cotton seed oil, Edible	0.2		8
DF	0269	Dried grapes (=currants, raisins and sultanas)	12		8
MO	0105	Edible Offal (Mammalians)	0.1	(*)	8
PE	0112	Eggs	0.1	(*)	8
JF	0269	Grape juice	1		8
FB	0269	Grapes	7		8
DH	1100	Hops, dry	100		8
CF	1255	Maize flour	0.2		8
OC	0645	Maize oil, crude	0.7		8
OR	0645	Maize oil, edible	0.5		8
MM	0095	Meat (from mammals other than marine mammals)	0.1	(*) (fat)	8
ML	0106	Milks	0.1	(*) F	8
JF	0004	Orange juice	0.3		8
OC	0698	Peanut oil, crude	0.3		8
OR	0698	Peanut oil, edible	0.3		8
PM	0110	Poultry meat	0.1	(*) (fat)	8
PO	0111	Poultry, edible offal of	0.1	(*)	8
FS	0012	Stone fruit	4		8
DT	1114	Tea, Green, Black	5		8

126 OXAMYL

VR	0577	Carrot	0.1		8
MO	0096	Edible offal of cattle, goats, horses, pigs & sheep	0.02	(*)	8	Animal commodity, no residues are expected from consumption of feed commodities with oxamyl as evaluated by JMPR
PE	0112	Eggs	0.02	(*)	8	Animal commodity, no residues are expected from consumption of feed commodities with oxamyl as evaluated by JMPR
MM	0095	Meat (from mammals other than marine mammals)	0.02	(*)	8	Animal commodity, no residues are expected from consumption of feed commodities with oxamyl as evaluated by JMPR
ML	0106	Milks	0.02	(*)	8
SO	0697	Peanut	0.05		8
AL	0697	Peanut fodder	0.2		8
VR	0589	Potato	0.1		8
PM	0110	Poultry meat	0.02	(*)	8
PO	0111	Poultry, Edible offal of	0.02	(*)	8	Animal commodity, no residues are expected from consumption of feed commodities with oxamyl as evaluated by JMPR

130 DIFLUBENZURON

FC	0001	Citrus fruits	0.5		8
MO	0105	Edible offal (mammalian)	0.1	(*)
MM	0095	Meat (from mammals other than marine mammals)	0.1	(fat)	8
ML	0106	Milks	0.02	(*) F	8
VO	0450	Mushrooms	0.3		8
FP	0009	Pome fruit	5		8
PM	0110	Poultry meat	0.05	(*) (fat)	8
GC	0649	Rice	0.01	(*)	8
AS	0649	Rice straw and fodder, dry	0.7		8

135 DELTAMETRIN

FP	0226	Apple	0.2		8
VR	0577	Carrot	0.02		8
GC	0080	Cereal grains	2	Po	8
FC	0001	Citrus fruits	0.02		8
PE	0112	Eggs	0.02	(*)	8
VB	0042	Flowerhead brassicas	0.1		8
FB	0269	Grapes	0.2		8
TN	0666	Hazelnuts	0.02	(*)	8
Mo	0098	Kidney of cattle, goats, pigs and sheep	0.03	(*)	8
VA	0384	Leek	0.2		8
VP	0060	Legume vegetables	0.2		8
MO	0099	Liver of cattle, goats, pigs and sheep	0.03	(*)	8
MO	0098	Kidney of cattle, goats, pigs and sheep	0.03	(*)	8
ML	0106	Milks	0.05		8
VO	0450	Mushrooms	0.05		8
FS	0245	Nectarine	0.05		8
FT	0305	Olives	1		8
VA	0385	Onion, Bulb	0.05		8
FS	0247	Peach	0.05		8
FS	0014	Plums (including Prunes)	0.05		8
VR	0589	Potato	0.01	(*)	8
PM	0110	Poultry meat	0.1	(fat)	8
PO	0111	Poultry, edible offal of	0.02	(*)	8
VD	0070	Pulses	1 Po		8
VR	0494	Radish	0.01	(*)	8
FB	0275	Strawberry	0.2		8
SO	0802	Sunflower seed	0.05	(*)	8
VO	0447	Sweet corn (corn-on-the-cob)	0.02	(*)	8
DT	1114	Tea, Green, Black	5		8
VO	0448	Tomatoes	0.3		8
TN	0688	Walnuts	0.02	(*)	8
CF	1211	Wheat flour	0.3	PoP	8
CF	1212	Wheat wholemeal	2	PoP	8

162 TOLYLFUANID

FB	0264	Blackberries	5	8
VC	0424	Cucumber	1	8
FB	0021	Currants, Black, Red, White	0.5	8
FB	0269	Grapes	3	8
DH	1100	Hops, dry	50	8
VA	0384	Leek	2	8
VO	0445	Peppers, sweet	2	8
FB	0272	Raspberries, Red, Black	5	8
FB	0275	Strawberry	5	8
VO	0448	Tomato	3	8

196 TEBUFENOZIDE

AM	660	Almond hulls	30		8
TN	660	Almonds	0.05		8
FI	326	Avocado	1		8
FB	20	Blueberries	3		8
VB	400	Broccoli	0.5		8
VB	41	Cabbages, Head	5		8
FC	1	Citrus fruits	2		8
FB	265	Cranberry	0.5		8
FB	0269	Grapes	2		8
DF	269	Dried grapes (=currants, raisins and sultanas)	2		8
PE	112	Eggs	0.02	(*)	8
FB	0269	Grapes			8
VL	53	Leafy vegetables	10		8
HH	738	Mints	20		8
FS	245	Nectarine	0.5		8
FS	247	Peach	0.5		8
TN	672	Pecan	0.01	(*)	8
VO	0051	Peppers	1		8
PM	0110	Poultry meat	0.02	(*)	8
SO	0495	Rape seed	2		8
FB	0272	Raspberries, red, black	2		8
GS	0654	Sugar cane	1		8
VO	0448	Tomato	1		8

203 SPINOSAD

FP	0226	Brassica vegetables	2		8
VL	0053	Leafy vegetables	10		8

204 ESFENVALERATE

PE	0112	Eggs	0.01	(*)	8
PM	0110	Poultry meat	0.01	(*) (fat)	8
PO	0111	Poultry, Edible offal of	0.01	(*)	8
SO	0495	Rapeseed	0.01	(*)	8
AS	0654	Wheat straw and fodder, dry	2		8

205 FLUTOLANIL

PE	0112	Eggs	0.05	(*)	8
MO	0098	Kidney of cattle, goats, pigs and sheep	0.1		8
MO	0099	Liver of cattle, goats, pigs and sheep	0.2		8
MM	0095	Meat (from mammals other than marine mammals)	0.05	(*)	8
ML	0106	Milks	0.05	(*)	8
PO	0111	Poultry edible offal	0.05	(*)	8
PM	0110	Poultry meat	0.05	(*)	8
CM	1206	Rice bran, unprocessed	10		8
AS	0649	Rice straw and fodder, dry	10		8
CM	0649	Rice, husked	2		8
CM	1205	Rice, polished	1		8

206 IMIDACLOPRID

FP	0226	Apple	0.5		8
AB	0226	Apple pomace, dry	5		8
FS	0240	Apricot	0.5		8
FI	0327	Banana	0.05		8
AS	0640	Barley straw and fodder (dry)	1	dry	8
VP	0061	Beans, except broad bean and soya bean	2		8
VB	0400	Broccoli	0.5		8
VB	0402	Brussels sprouts	0.5		8
VB	0041	Cabbages, head	0.5		8
VB	0404	Cauliflower	0.5		8
GC	0080	Cereals grains	0.05		8
FC	0001	Citrus fruits	1		8
AB	0001	Citrus pulp, dry	10		8
VC	0424	Cucumber	1		8
MO	0105	Edible offal (Mammalian)	0.05		8
VO	0440	Egg plant	0.2		8
PE	0112	Eggs	0.02	(*)	8
FB	0269	Grapes	1		8
DH	1100	Hops, dry	10		8
VA	0384	Leek	0.05	(*)	8
VL	0482	Lettuce, Head	2		8
AS	0645	Maize fodder	0.2	dry	8
AF	0645	Maize forage	0.5	dry	8
FI	0345	Mango	0.2		8
MM	0095	Meat (from mammals other than marine mammals)	0.02	(*)	8
VC	0046	Melons, except Watermelon	0.2		8
ML	0106	Milks	0.02	(*)	8
FS	0245	Nectarine	0.5		8
AF	0647	Oat forage (green)	5	dry	8
AS	0647	Oat straw and fodder, dry	1	dry	8
VA	0385	Onion, Bulb	0.1		8
FS	0247	Peach	0.5		8
FP	0230	Pear	1		8
TN	0672	Pecan	0.05		8
VO	0051	Peppers	1		8
FS	0014	Plums (including prunes)	0.2		8
PM	0110	Poultry meat	0.02	(*)	8
PO	0111	Poultry, Edible offal of	0.02	(*)	8
VR	0589	Potato	0.5		8
SO	0495	Rape seed	0.05	(*)	8
AF	0650	Rye forage (green)	5	dry wt	8
AS	0650	Rye straw and fodder, dry	1	dry wt	8
VC	0431	Squash, Summer	1		8
VO	0447	Sweet corn (corn-on-the-cob)	0.02	(*)	8
VR	0596	Sugar beet	0.05	(*)	8
AV	0596	Sugar beet leaves or tops	5	dry wt	8
VO	0448	Tomato	0.5		8
VC	0432	Watermelon	0.2		8
CM	0654	Wheat bran, unprocessed	0.3		8
CF	1211	Wheat flour	0.03		8
AS	0654	Wheat straw and fodder, dry^a	1		8

¹ These letters and codes are preliminary and might change in future.

APPENDIX III

DRAFT AND REVISED DRAFT MAXIMUM RESIDUE LIMITS FOR PESTICIDES
(Advanced at Step5/8 of the Codex Procedure)

				MRL (mg/kg)		Step	Note

48 LINDANE

GC	0640	Barley	0.01	(*)	5/8
MO	0105	Edible offal (mammalian)	0.01	(*)	5/8
PE	0112	Eggs	0.01	(*)	5/8
GC	0645	Maize	0.01	(*)	5/8
MM	0095	Meat (from mammals other than marine mammals)	0.1	(fat)	5/8
ML	0106	Milks	0.01	(*)	5/8
GC	0647	Oats	0.01	(*)	5/8
PO	0111	Poultry edible offals	0.01	(*)	5/8
PM	0110	Poultry meat	0.05	(fat)	5/8
GC	0650	Rye	0.01	(*)	5/8
GC	0651	Sorghum	0.01	(*)	5/8
AS	0081	Straw and fodder (dry) of cereal grains	0.01	(*)	5/8
VO	1275	Sweet corn (kernels)	0.01	(*)	5/8
GC	0654	Wheat	0.01	(*)	5/8

59 PARATHION-METHYL

0245

Nectarine

0.3

5/8

63 PYRETHRINS

0080

Cereal grains

0.3

5/8

83 DICHLORAN

FB	0269	Grapes	7		5/8
FS	0245	Nectarine	7	Po	5/8
FS	0247	Peach	7	Po	5/8

196 TEBUFENOZIDE

MO	0105	Edible offal (mammalian)	0.02	(*)	5/8
MM	0095	Meat (from mammals other than marine mammals)	0.05	(fat)	5/8
ML	0106	Milks	0.01	(*)	5/8

APPENDIX IV

DRAFT AND REVISED DRAFT MAXIMUM RESIDUE LIMITS FOR PESTICIDES
(Advanced at Step5 of the Codex Procedure)

				MRL (mg/kg)		Step	Note

27 DIMETHOATE

VS	0620	Artichoke, Globe	0.05		5
VB	0402	Brussels sprouts	0.2		5
VB	0041	Cabbage, Head	2		5
VB	0404	Cauliflower	0.2		5
VS	0624	Celery	0.5		5
FC	0001	Citrus fruits	5		5
VL	0482	Lettuce, Head	5		5
FI	0545	Mango	1	Po	5
FT	0305	Olives	0.5		5
VO	0445	Peppers, sweet	5	Po	5
GC	0654	Wheat	0.05		5
AS	0654	Wheat straw and fodder, dry	1		5

37 FENITROTIHION

GC	0080	Cereal grains	10	Po	5
CM	0654	Wheat bran (unprocessed)	30	PoP	5

72 CARBENDAZIM

VS	0621	Asparagus	0.2		5
FS	0013	Cherries	10	Th	5
VP	0526	Common bean (pods and/or immature seeds)	0.5	Th	5
FI	0345	Mango	5		5
SO	0697	Peanut	0.1	(*) Th	5
AL	0697	Peanut fodder	3	Th	5
VO	0444	Peppers, Chili	2		5
VD	0541	Soya bean (dry)	0.5	Th	5
VC	0431	Squash, Summer	0.5	Th	5
VR	0596	Sugar beet	0.1	(*) Th	5
AV	0596	Sugar beet leaves or tops	10	Th	5

84 DODINE

FS	0013	Cherries	3	5
FS	0245	Nectarines	5	5
FS	0247	Peach	5	5
FP	0009	Pome fruits	5	5

86 PIRIMIPHOS-METHYL

GC	0080	Cereal grains	7	Po	5
ML	0106	Milks	0.01		5
CM	0654	Wheat bran, Unprocessed	15	PoP	5

94 METHOMYL

AL	1020	Alfalfa fodder	20		5
AL	1021	Alfalfa forage (green)	25		5
GC	0640	Barley	2		5
AL	61	Bean fodder	10		5
VP	61	Beans, except broad bean and soya bean	1		5
VB	0040	Brassica vegetables	7		5
VS	0624	Celery	3		5
AB	0001	Citrus pulp, Dry	3		5
VC	0045	Fruiting vegetables, Cucurbits	0.1		5
FB	0269	Grapes	7		5
VL	0053	Leafy vegetables	30		5
AL	0528	Pea vines (green)	40		5
VR	0589	Potato	0.02	(*)	8
AL	1265	Soya bean forage (green)	40		5
GC	0654	Wheat	2		5
CM	654	Wheat bran, Unprocessed	3		5
CF	1211	Wheat flour	0.03		5
CF	1210	Wheat germ	2		5

95 ACEPHATE

VS	0620	Artichoke, Globe	0.3		5
VP	0061	Beans, except broad bean and soya bean	5		5
MO	0105	Edible offal (Mammalian)	0.05		5
PE	0112	Eggs	0.01	(*)	5
VB	0042	Flowerhead brassicas	2		5
FC	0003	Mandarins (incl Mandarin-like hybrids)	7		5
MM	0095	Meat (from mammals other than marine mammals)	0.05		5
ML	0106	Milks	0.02		5
FS	0245	Nectarine	2		5
FS	0247	Peach	2		5
VO	0051	Peppers	5		5
FP	0009	Pome fruit	7		5
PM	0110	Poultry meat	0.01	(*)	5
PO	0111	Poultry, Edible offal of	0.01	(*)	5
VD	0541	Soya bean (dry)	0.3		5

96 CARBOFURAN

GC	0645	Maize	0.05	(*)	5
AF	0645	Maize forage	0.2		5
VR	0589	Potato	0.2		5
VR	0596	Sugar beet	0.2		5
AV	0596	Sugar beet leaves or tops	0.7		5

100 METHAMIDOPHOS

VS	0620	Artichoke, Globe	0.2	(Ac)	5
VP	0061	Beans, except broad bean and soya bean	1	(Ac)	5
VB	0041	Cabbage, head	1		5
SO	0691	Cottonseed	0.2		5
MO	0105	Edible offal (Mammalian)	0.01	(*)	5
PE	0112	Eggs	0.01	(*)	5
VB	0042	Flowerhead brassicas	0.5	(Ac)	5
AV	1051	Fodder beet	30		5
AM	1051	Fodder beet leaves or tops	0.02		5
FC	0003	Mandarins	0.5	(Ac)	5
MM	0095	Meat (from mammals other than marine mammals)	0.01	(*)	5
ML	0106	Milks	0.02		5
FS	0245	Nectarine	0.5	(Ac)	5
FS	0247	Peach	0.5	(Ac)	5
VO	0051	Peppers	2	(Ac)	5
FP	0009	Pome fruit	0.5	(Ac)	5
VR	0587	Potato	0.05		5
PM	0110	Poultry meat	0.01	(*)	5
PO	0111	Poultry, Edible Offal of	0.01	(*)	5
VD	0541	Soya bean (dry)	0.1	(Ac)	5
VR	0596	Sugar beet	0.02		5
AV	0596	Sugar beet leaves or tops	30		5
VO	0448	Tomato	2		5

145 CARBOSULFAN

SO	0691	Cotton seed	0.05		5
MO	0105	Edible offal (Mammalian)	0.05	(*)	5
PE	0112	Eggs	0.05	(*)	5
GC	0645	Maize	0.05	(*)	5
AF	0645	Maize forage	0.05	(*)	5
MM	0095	Meat (from mammals other than marine mammals)	0.05	(*)	5
ML	0106	Milks	0.03	(*)	5
VR	0589	Potato	0.05	(*)	5
PM	0110	Poultry meat	0.05	(*)	5
PO	0111	Poultry, Edible offal of	0.05	(*)	5
AS	0649	Rice	0.05	(*)	5
VR	0596	Sugar beet	0.3		5
AV	0596	Sugar beet leaves or tops	0.05	(*)	5

162 TOLYLFUANID

0482

Lettuce, Head

207 CYPRODINIL

AM	0660	Almond hulls	0.05	(*)	5
TN	0660	Almonds	0.02	(*)	5
FP	0226	Apple	0.05		5
GC	0640	Barley	3		5
VP	0061	Beans, except broad bean and soya bean	0.5		5
VC	0424	Cucumber	0.2		5
DF	0269	Dried grapes (= Currants, Raisins and Sultanas)	5		5
MO	0095	Edible offal (Mammalian)	0.01	(*)	5
VO	0440	Egg plant	0.2		5
PE	0112	Eggs^1/	0.01	(*)	5
FB	0269	Grapes	3		5
VL	0482	Lettuce, Head	10		5
VL	0483	Lettuce, Leaf	10		5
MM	0095	Meat (from mammals other than marine mammals)	0.01	(*) (fat)	5
ML	0106	Milks	0.0004	(*)	5
VA	0385	Onion, Bulb	0.3		5
FP	0230	Pear	1		5
VO	0445	Peppers, Sweet	0.5		5
PM	0110	Poultry meat	0.01	(*) (fat)	5
PO	0111	Poultry, Edible offal of	0.01	(*)	5
DF	0014	Prunes	5		5
FB	0272	Raspberries, Red, Black	0.5		5
FS	0012	Stone fruits	2		5
AS	0081	Straw and fodder (dry) of cereal grains	10		5
FB	0275	Strawberry	2		5
VC	0431	Squash, Summer	0.2		5
VO	0448	Tomatoes	0.5		5
GC	0654	Wheat	0.5		5
CM	0654	Wheat bran, unprocessed	2		5

208 FAMOXADONE

GC	0640	Barley	0.2		5
AS	0640	Barley straw and fodder (dry)	5		5
VC	0424	Cucumber	0.2		5
FB	0269	Grape	2		5
AB	0269	Grape pomace dry	7		5
DF	0269	Dried grapes (raisin)	5		5
MO	0105	Edible offal (mammalian)	0.5		5
PE	0112	Eggs	0.01	(*)	5
MM	0095	Meat (from mammals other than marine mammals)	0.5	Fat	5
ML	0106	Milk	0.03	(F)
VR	0589	Potato	0.02	(*)
PM	0110	Poultry meat	0.01	(*)
PM	0111	Poultry, edible offal	0.01	(*)
VC	431	Summer squash	0.2
VO	0448	Tomato	2
GC	0654	Wheat	0.1
CM	0654	Wheat bran, unprocessed	0.2
AS	0654	Wheat straw	7

209 METHOXYFENOZIDE

AM	0660	Almond hulls	50		5
AB	0226	Apple pomace, dry	7		5
VB	0400	Broccoli	3		5
VB	0041	Cabbages, head	7		5
VS	0624	Celery	15		5
SO	0691	Cotton seed	7		5
DF	0269	Dried grapes (raisins)	3		5
MO	0105	Edible Offal (mammalian)	0.02		5
PE	0112	Eggs	0.01		5
FB	0269	Grapes	1		5
VL	0482	Lettuce, head	15		5
VL	0483	Lettuce, leaf	30		5
GC	0645	Maize	0.02	(*)	5
AS	0645	Maize fodder	60		5
AF	0645	Maize forage	50		5
MM	0095	Meat (for mammals other than marine mammals)	0.05	(fat)	5
ML	0106	Milks	0.01		5
VL	0485	Mustard greens	30		5
FP	0009	Pome fruit	2		5
VO	0051	Peppers	2		5
FP	0009	Pome fruits	2		5
PM	0110	Poultry meat	0.01	(*)	5
PO	0111	Poultry, edible offal of	0.01	(*)	5
DF	0014	Prunes (dried plums)	2		5
VL	0502	Spinach	50		5
FS		Stone fruit	2		5
VO	0447	Sweet corn (corn-on-the-cob)	0.02	(*)	5
VL	0448	Tomato	2		5
TN	0085	Tree nuts	0.1		5

APPENDIX V

CODEX MAXIMUM RESIDUE LIMITS FOR PESTICIDES RECOMMENDED FOR REVOCATION

				MRL (mg/kg)		Step	Note

008 CARBARYL

AL	1021	Alfalfa forrage green	100	T	CXL-D
VS	621	Aspergus	10	T	CXL-D	To be revoked once the related MRL(s) reach Step 8
FI	0327	Banana	5	T	CXL-D
GC	0640	Barley	5	T	CXL-D
AL	1030	Bean forrage green	100		CXL-D
VR	0574	Beetroot	2		CXL-D	To be revoked once the related MRL(s) reach Step 8
FB	0264	Blacberries	10	T	CXL-D
FB	0020	Blueberries	7	T	CXL-D
VB	0041	Cabbages, Head	5	T	CXL-D
VR	0577	Carrot	2	T	CXL-D	To be revoked once the related MRL(s) reach Step 8
MM	0812	Cattle meat	0.2	T	CXL-D
AL	1023	Clover	100	T	CXL-D
VP	0526	Common bean (pods and/or immature seeds)	5	T	CXL-D
SO	0691	Cotton seed	1	T	CXL-D
VD	0527	Cowpea (dry)	1	T	CXL-D
FB	0265	Cranberry	7	T	CXL-D
VC	0424	Cucumber	3	T	CXL-D
FB	0266	Dewberries (including boysenberry and loganberry)	10	T	CXL-D
PE	0112	Eggs	0.5	T	CXL-D
VO	0440	Egg plant	5		CXL-D	To be revoked once the related MRL(s) reach Step 8
MM	0814	Goat meat	0.2	T	CXL-D
AS	0162	Hay or fodder (dry) of grasses	100	T	CXL-D
FI	0341	Kiwuifruit	10	T	CXL-D
VL	0053	Leafy vegetables	10	T	CXL-D
AF	0645	Maize forage,	100	T	CXL-D	To be revoked once the related MRL(s) reach Step 8
VC	0046	Mellons, except water mellons	3	T	CXL-D
AO3	0001	Milk products	0.1	T	CXL-D
ML	0106	Milks	0.1	T	CXL-D	To be revoked once the related MRL(s) reach Step 8
AO5	1900	Nuts (whole in shell)	10	T	CXL-D
GC	0647	Oats	5	T	CXL-D
VO	0442	Okra	10	T	CXL-D
FT	0305	Olives	10	T	CXL-D	To be revoked once the related MRL(s) reach Step 8
DM	0305	Olives, processed	1	T	CXL-D
VR	0588	Parsnip	2	T	CXL-D
AL	0528	Pea vines (green)	100	T	CXL-D
AL	0697	Peanut fodder	100	T	CXL-D
SO	0703	Peanut, Whole	2	T	CXL-D
VP	0063	Peas (pods and/or immature seeds)	5	T	CXL-D
FS	0014	Plums (including prunes)	10	T	CXL-D
VR	0589	Potato	0.2	T	CXL-D
PM	0110	Poultry meat	0.5	T	CXL-D
PO	0113	Poultry skin	5	T	CXL-D
VC	0429	Pumpkins	3	T	CXL-D
VR	0494	Radish	2	T	CXL-D
FB	0272	Raspberries, Red, Black	10	T	CXL-D
GC	0649	Rice	5	T	CXL-D
GC	0649	Rice	50		St. 7D
CM	0649	Rice, Husked	5	T	CXL-D
GC	0650	Rye	5	T	CXL-D
MM	0822	Sheep meat	0.2	T	CXL-D
GC	0651	Sorghum	10	T	CXL-D
AF	0651	Sorghum forage, green	20		CXL-D	To be revoked once the related MRL(s) reach Step 8
VD	541	Soya bean (dry)	1		CXL-D	To be revoked once the related MRL(s) reach Step 8
AL	1265	Soyabean forage (green)	100		CXL-D	To be revoked once the related MRL(s) reach Step 8
VC	0431	Squash, Summer	3	T	CXL-D
FB	0275	Strawberry	7	T	CXL-D
VR	0596	Suggar beat	0.2	T	CXL-D
AV	0596	Suggar beat leaves or tops	100	T	CXL-D
VR	0497	Swede	2	T	CXL-D
VO	1225	Sweet corn (kernels)	1	T	CXL-D
VO	0448	Tomato	5	T	CXL-D	To be revoked once the related MRL(s) reach Step 8
TN	0085	Tree nuts	1	T	CXL-D	To be revoked once the related MRL(s) reach Step 8
GC	0654	Wheat	5	T	CXL-D
CM	0654	Wheat bran, unprocessed	20	T	CXL-D	To be revoked once the related MRL(s) reach Step 8
CF	1211	Wheat flour	0.2	T	CXL-D
CF	1212	Wheat wholemeal	2	T	CXL-D
VC	0433	Winter squash	3	T	CXL-D

20 2,4-D

0001

Citrus fruits

CXL-D

22 DIAZINON

MM	97	Meat of cattle, pigs and sheep	0.7		CXL-D	To be revoked once the related MRL(s) reach Step 8
FP	9	Pome fruits	2		CXL-D	To be revoked once the related MRL(s) reach Step 8

34 ETHION

0081

Citrus fruits

CXL-D

37 FENITROTIHION

1211

White bread

0.2

CXL-D

48 LINDANE

VR	0577	Carrot	0.2	CXL-D
PE	0112	Eggs	0.01	CXL-D	To be revoked once the related MRL(s) reach Step 8
PM	0110	Poultry meat	0.05	CXL-D	To be revoked once the related MRL(s) reach Step 8
SO	0495	Rape seed	0.05	CXL-D
VR	0596	Sugar beet	0.1	CXL-D
AV	0596	Sugar beet leaves or tops	0.1	CXL-D

49 MALATHION

FB	20	Blueberries	0.5	CXL-D	To be revoked once the related MRL(s) reach Step 8
CM	0654	Wheat bran,Unprocessed	20	CXL-D
CF	1212	Wheat wholemeal	2	CXL-D

55 OMETHOATE

Delete all proposed MRLs

60 PARATHION-METHYL

VB	41	Cabbages, Head	0.2		CXL-D	To be revoked once the related MRL(s) reach Step 8
VD	82	Peas (dry)	0.2		CXL-D	To be revoked once the related MRL(s) reach Step 8

64 PYRETHRINS

0080

Cereal grains

CXL-D

To be revoked once the related MRL(s) reach Step 8

74 DISULFOTON

VR	0589	Potato	0.5		CXL-D
VR	0591	Radish Japanese	0.2		CXL-D

83 DICHLORAN

FB	0269	Grapes	10	CXL-D	To be revoked once the related MRL(s) reach Step 8
VL	0428	Lettuce, Head	10	CXL-D
FS	0247	Peach	15	CXL-D	To be revoked once the related MRL(s) reach Step 8
FS	0014	Plums (including prunes)	10	CXL-D
FB	0275	Strawberry	10	CXL-D
VO	0448	Tomato	0.5	CXL-D

85 PENAMIPHOS


FI	327	Banana	0.1	CXL-D	To be revoked once the related MRL(s) reach Step 8
VB	402	Brussels sprouts	0.05	CXL-D	To be revoked once the related MRL(s) reach Step 8
VB	41	Cabbages, Head	0.05	CXL-D	To be revoked once the related MRL(s) reach Step 8

94 METHOMYL

AS	0640	Barley straw and fodder, dry	5	CXL-D
VP	0526	Common bean (pods and/or immature seeds)	2	CXL-D	To be revoked once the related MRL(s) reach Step 8
SO	0691	Cotton seed	0.5	CXL-D	To be revoked once the related MRL(s) reach Step 8
VL	0480	Kale	5	CXL-D
GC	0645	Maize	0.05	CXL-D	To be revoked once the related MRL(s) reach Step 8
AS	0645	Maize fodder	50	CXL-D
AF	0645	Maize forage	50	CXL-D	To be revoked once the related MRL(s) reach Step 8
MM	0095	Meat (from mammals other than marine mammals)	0.02	CXL-D	To be revoked once the related MRL(s) reach Step 8
ML	0106	Milks	0.02	CXL-D	To be revoked once the related MRL(s) reach Step 8
FS	0245	Nectarine	5	CXL-D	To be revoked once the related MRL(s) reach Step 8
GC	0647	Oats	0.5	CXL-D	To be revoked once the related MRL(s) reach Step 8
FS	0247	Peach	5	CXL-D	To be revoked once the related MRL(s) reach Step 8
VR	0589	Potato	0.1	CXL-D	To be revoked once the related MRL(s) reach Step 8
VL	0502	Spinach	5	CXL-D

96 CARBOFURAN

AS	0645	Maize fodder	5	CXL-D
SO	0088	Oilseed	0.1*	CXL-D
CM	0649	Rice, husked	0.2	CXL-D	To be revoked once the related MRL(s) reach Step 8

100 METHAMIDOPHOS

FS	0247	Peach	1	CXL-D
FP	0009	Pome fruits	0.5	7
VO	0448	Tomato	1	7

103 PHOSMET

0085

Tree nuts

0.1

CXL-D

To be revoked once the related MRL(s) reach Step 8

113 PROPARGITE

AL	1020	Alfalfa fodder	75	CXL-D
AL	1021	Alfalfa forage (green)	30	CXL-D
TN	0660	Almonds	0.1	CXL-D	To be revoked once the related MRL(s) reach Step 8
FP	0226	Apple	5	CXL-D	To be revoked once the related MRL(s) reach Step 8
JF	0226	Apple pomace, Dry	80	CXL-D
FS	0240	Apricot	7	CXL-D	To be replaced by MRL for stone fruits
FC	0001	Citrus fruits	5	CXL-D	To be revoked once the related MRL(s) reach Step 8
AB	0001	Citrus pulp, Dry	40	CXL-D	To be revoked once the related MRL(s) reach Step 8
VP	0526	Common bean (pods and/or immature seeds)	20	CXL-D
SO	0691	Cotton seed	0.1 (*)	CXL-D	To be revoked once the related MRL(s) reach Step 8
FB	0265	Cranberry	10	CXL-D
VC	0424	Cucumber	0.5	CXL-D
DF	0269	Dried grapes (=currants, raisins and sultanas)	10	CXL-D	To be revoked once the related MRL(s) reach Step 8
PE	0112	Eggs	0.1	CXL-D	To be revoked once the related MRL(s) reach Step 8
FT	0297	Fig	2	CXL-D
FB	0269	Grapes	10	CXL-D	To be revoked once the related MRL(s) reach Step 8
DH	1100	Hops, dry	30	CXL-D	To be revoked once the related MRL(s) reach Step 8
AS	0645	Maize fodder	10	CXL-D
AF	0645	Maize forage	10	CXL-D
MM	0095	Meat (from mammals other than marine mammals)	0.1	CXL-D
ML	0106	Milks	0.1	CXL-D	To be revoked once the related MRL(s) reach Step 8
AM	0738	Mint hay	50	CXL-D
FS	0245	Nectarine	7	CXL-D	To be replaced by MRL for stone fruits
FS	0247	Peach	7	CXL-D	To be replaced by MRL for stone fruits
AL	0697	Peanut fodder	10	CXL-D
AL	1270	Peanut forageo (green)	10	CXL-D
GC	0651	Sorghum	5	CXL-D
AF	0651	Sorghum forage (green)	10	CXL-D
AS	0651	Sorghum straw and fodder, Dry	10	CXL-D
DT	1114	Tea, Green, Black	10	CXL-D	To be revoked once the related MRL(s) reach Step 8

126 OXAMYL

FI	0327	Banana	0.2	CXL-D
VP	0061	Beans, except broad bean and soya bean	0.2	CXL-D
VS	0624	Celery	5	CXL-D
SB	0716	Coffee beans	0.1	CXL-D
GC	0645	Maize	0.05	CXL-D
VA	0385	Onion, Bulb	0.05	CXL-D
SO	0697	Peanut	0.1	CXL-D	To be revoked once the related MRL(s) reach Step 8
AL	0697	Peanut fodder	2	CXL-D	To be revoked once the related MRL(s) reach Step 8
FI	0353	Pineapple	1	CXL-D
VR	0075	Root and tuber vegetables	0.1	CXL-D	To be revoked once the related MRL(s) reach Step 8
VD	0541	Soya Bean (dry)	0.1	CXL-D
VC	0431	Squash, Summer	2	CXL-D
GS	0659	Sugar cane	0.05	CXL-D
VC	0432	Watermelon	2	CXL-D

130 DIFLUBENZURON

FP	0226	Apple	1	CXL-D	To be replaced by MRL for pome fruits
VB	0402	Brussels sprouts	1	CXL-D
VB	0041	Cabbages, Head	1	CXL-D
FC	0001	Citrus fruits	1	CXL-D	To be revoked once the related MRL(s) reach Step 8
SO	0691	Cotton seed	0.2	CXL-D
MO	0105	Edible offal (mammalian)	0.05	CXL-D	To be revoked once the related MRL(s) reach Step 8
MM	0095	Meat (from mammals other than marine mammals)	0.05	CXL-D	To be revoked once the related MRL(s) reach Step 8
ML	0106	Milks	0.05	CXL-D	To be revoked once the related MRL(s) reach Step 8
VO	0450	Mushrooms	0.1	CXL-D	To be revoked once the related MRL(s) reach Step 8
FP	0230	Pear	1	CXL-D	To be replaced by MRL for pome fruits
FS	0014	Plums (including prunes)	1	CXL-D
PM	0110	Poultry meat	0.05	CXL-D	To be revoked once the related MRL(s) reach Step 8
VD	0541	Soya bean (dry)	0.1	CXL-D
VO	0448	Tomato	1	CXL-D

135 DELTAMETRIN

VS	0620	Artichoke, Globe	0.05	CXL-D
FI	0327	Banana	0.05	CXL-D
VD	0071	Beans (dry)	1	CXL-D	To be replaced by MRL for pulses
VB	0040	Brassica vegetables	0.2	CXL-D	To be replaced by MRL for flowerhead brassicas
VA	0036	Bulb vegetables, except fennel, bulb	0.1	CXL-D	To be replaced by the MRLs for leek and onion bulb
SB	0715	Cacao beans	0.05	CXL-D
GC	0080	Cereal grains	1	CXL-D	To be revoked once the related MRL(s) reach Step 8
SB	0716	Coffee beans	2	CXL-D
MO	0105	Edible offal (mammalian)	0.05	CXL-D
PE	0112	Eggs	0.01	CXL-D	To be revoked once the related MRL(s) reach Step 8
VD	0561	Field pea (dry)	1	CXL-D	To be replaced by the MRL for pulses
FT	0297	Fig	0.01	CXL-D
VO	0050	Fruiting vegetables other than cucurbis	0.2	CXL-D
FB	0269	Grapes	0.05	CXL-D	To be revoked once the related MRL(s) reach Step 8
DH	1100	Hops, Dry	5	CXL-D
FI	0341	Kiwifruit	0.05	CXL-D
AL	0157	Legume animal feeds	0.5	CXL-D
VP	0060	Legume vegetables	0.1	CXL-D
VD	0533	Lentil (dry)	1	CXL-D	To be replaced by the MRL for pulses
FC	0003	Mandarins	0.05	CXL-D
VC	0046	Melons, except watermelon	0.01	CXL-D
ML	0106	Milks	0.02	CXL-D	To be revoked once the related MRL(s) reach Step 8
VO	0450	Mushrooms	0.01	CXL-D	To be revoked once the related MRL(s) reach Step 8
SO	0088	Oilseed	0.1	CXL-D	To be revoked once the related MRL(s) reach Step 8
SO	0088	Oilseed, except peanut	0.1	CXL-D
FT	0305	Olives	0.1	CXL-D	To be revoked once the related MRL(s) reach Step 8
FC	0004	Oranges, Sweet, Sour	0.05	CXL-D	To be replaced by the MRL for citrus fruits
SO	0697	Peanut	0.01	CXL-D
FI	0353	Pineapple	0.01	CXL-D
FP	0009	Pome fruits	0.1	CXL-D	To be revoked once the related MRL(s) reach Step 8
PM	0110	Poultry meat	0.01	CXL-D	To be revoked once the related MRL(s) reach Step 8
PO	0111	Poultry, edible offal of	0.01	CXL-D	To be revoked once the related MRL(s) reach Step 8
VR	0075	Root and tuber vegetables	0.01	CXL-D	To be replaced by the MRLs for individual commodities
FS	0012	Stone fruits	0.05	CXL-D	To be replaced by the MRL for nectarine and peach
AS	0081	Straw and fodder (dry) of cereal grains	0.5	CXL-D
FB	0275	Strawberry	0.05	CXL-D	To be revoked once the related MRL(s) reach Step 8
DT	1114	Tea, Green, Black	10	CXL-D	To be revoked once the related MRL(s) reach Step 8
FT	0312	Tree tomato	0.02	CXL-D
CF	1211	Wheat flour	0.2	CXL-D	To be revoked once the related MRL(s) reach Step 8
CF	1212	Wheat wholemeal	1	CXL-D	To be revoked once the related MRL(s) reach Step 8

137 BENDIOCARB

VR	0574	Beetroot	0.05	CXL-D
MF	0812	Cattle fat	0.05	CXL-D
MO	1280	Cattle kidney	0.2	CXL-D
MM	0812	Cattle meat	0.05	CXL-D
MO	0812	Cattle, Edible offal of	0.05	CXL-D
PE	0112	Eggs	0.05	CXL-D
GC	0645	Maize	0.05	CXL-D
AS	0645	Maize fodder	0.05	CXL-D
AF	0645	Maize forage	0.05	CXL-D
ML	0106	Milks	0.05	CXL-D
VR	0589	Potato	0.05	CXL-D
PF	0111	Poultry fats	0.05	CXL-D
PM	0110	Poultry meat	0.05	CXL-D
PO	0111	Poultry, Edible offal of	0.05	CXL-D
VR	0596	Sugar beet	0.05	CXL-D
AV	0596	Sugar beet leaves or tops	0.05	CXL-D

162 TOLYLFUANID

FB	0021	Currants, Black, Red, White	5	CXL-D	To be revoked once the related MRL(s) reach Step 8
VC	0425	Gherkin	2	CXL-D
FB	0275	Strawberry	3	CXL-D	To be revoked once the related MRL(s) reach Step 8
VO	0448	Tomato	2	CXL-D

170 HEXACONAZOLE

FP	0226	Apple	CXL-D
FI	0327	Banana	CXL-D
SB	0716	Coffee beans	CXL-D
FB	0269	Grapes	CXL-D
GC	0654	Wheat	CXL-D
AS	0654	Wheat straw and fodder, Dry	CXL-D

196 TEBUFENOZIDE

MO	1280	Cattle kidney	0.02	CXL-D	Replaced by Eddible offal (mammalian)
MO	1281	Cattle liver	0.02	CXL-D	Replaced by Eddible offal (mammalian)
MM	812	Cattle meat	0.05	CXL-D
ML	812	Cattle milk	0.01	CXL-D

APPENDIX VI

DRAFT AND REVISED DRAFT MAXIMUM RESIDUE LIMITS FOR PESTICIDES
(Returned to Step 6 and 3 of the Codex Procedure)

				MRL (mg/kg)		Step	Note

007 CAPTAN

FP	226	Apple	20	6
FS	13	Cherries	25	6
VC	424	Cucumber	3	6
DF	269	Dried grapes (=currants, raisins and sultanas)	50	6
FB	269	Grapes	25	6
VC	046	Melons, except watermelon	10
FS	245	Nectarine	3	6
FSO	247	Peach	20
FS	14	Plums (including prunes)	10	6
FP	9	Pome fruits	15	6
FB	272	Raspberries, Red, Black	20	6
FB	275	Strawberry	15
VO	448	Tomato	5	6

008 CARBARYL

FS	0013	Cherries	20	6
FC	0001	Citrus fruits	15	6
JF	0001	Citrus juice	0.5	6
AB	0001	Citrus pulp, dry	4	6
DF	0269	Dried grapes (=currants, raisins and sultanas)	50	6
FB	0269	Grapes	40	6
JF	0269	Grape juice	30	6
AB	0269	Grape pomace, dry	80	6
FS	0012	Stone fruits	10	6

22 DIAZINON

Cabbages, Head

0.5

27 DIMETHOATE

GC	640	Barley	2	6
FB	0269	Grapes	2	6
VP	63	Peas (pods and succulent=immature seeds)	1	6
FS	14	Plums (including prunes)	1	6
FP	9	Pome fruits	0.5	6
AV	596	Sugar beet leaves or tops	0.1	6
VO	448	Tomato	2	6
VL	506	Turnip, Greens	1	6
VR	506	Turnip, Garden	0.1	6

41 FOLPET

FP	226	Apple	10	6
DF	269	Dried grapes (=currants, raisins and sultanas)	40	6
FB	269	Grapes	10	6
VL	482	Lettuce, Head	50	6
FB	275	Strawberry	5	6
VO	448	Tomato	3	6

49 MALATHION

AL	1020	Alfalfa fodder	200		6
AL	1021	Alfalfa forage (green)	500	(dry)	6
AL	1023	Clover	500	(dry)	6
AL	1031	Clover hay or fodder	150		6
SO	691	Cotton seed	20		6
OC	691	Cotton seed oil, Crude	13		6
OR	691	Cotton seed oil, Edible	13		6
AF	162	Grass forage	200		6
AS	162	Hay or fodder *dry) of grasses	300		6
GC	645	Maize	0.05		6
AS	645	Maize fodder	50		6
AF	645	Maize forage	10	(dry)	6
GC	651	Sorghum	3		6
GC	654	Wheat	0.5		6
CF	1211	Wheat flour	0.2		6
AF	654	Wheat forage (whole plant)	20	dry wt	6
AS	654	Wheat straw and fodder, Dry	50		6

61 PARATHION-METHYL

AL	1020	Alfalfa fodder	70		6
AL	1021	Alfalfa forage (green)	70		6

AL	1030	Bean forage (green)	1	Fresh wt	6
SO	691	Cotton seed	25		6
OC	691	Cotton seed oil, Crude	10		6
OR	691	Cotton seed oil, Edible	10		6
AS	162	Hay or fodder (dry) of grasses	5		6
GC	645	Maize	0.1		6
CF	1255	Maize flour	0.05		6
OC	645	Maize oil, Crude	0.2		6
OR	645	Maize oil, Edible	0.1		6
AL	82	Pea hay or pea fodder (dry)	80		6
AL	528	Pea vines (green)	40		6
SO	495	Rape seed	0.05		6
OC	495	Rape seed oil, Crude	0.2		6
OR	495	Rapeseed oil, Edible	0.2		6
AV	0596	Sugar beat leaves or tops	0.05	(*) fresh wt	6
GC	654	Wheat	5		6
CM	654	Wheat bran, Unprocessed	10		6
CF	1211	Wheat flour	2		6
AS	0654	Wheat and straw fodder, dry	10		6

65 THIABENDAZOLE

VO	450	Mushrooms	60		6
FC	001	Citrus fruits	3	Po	6

73 CARBENDAZIM

FI	0327	Banana	0.2		6
GC	0640	Barley	0.5		6
AS	0640	Barley straw and fodder	2		6
VD	0071	Beans (dry)	0.5		6
FB	0018	Berries and other small fruits	1		6	Except grapes
VR	0577	Carrot	0.2		6
MM	0812	Cattle meat	0.05	(*)	6
PF	0840	Chicken fat	0.05	(*)	6
VC	0424	Cucumber	0.05	(*)	6
MO	0105	Eddible offal (mammalian)	0.05	(*)	6
PE	0112	Eggs	0.05	(*)	6
VP	0529	Garden pea, Shelled	0.02		6
VC	0425	Gherkin	0.05	(*)	6
FB	0269	Grapes	3		6
VL	0482	Lettuce, Head	5		6
ML	0106	Milks	0.05	(*)	6
FC	0004	Oranges, Sweet, Sour	1		6
VO	0051	Peppers	0.1	Th	6
PM	0110	Poultry meat	0.05	(*)	6
SO	0495	Rape seed	0.05	(*)	6
AS	0649	Rice straw and fodder, Dry	15		6
CM	0649	Rice, Husked	2		6
GC	0649	Rye	0.05		6
GC	0654	Wheat	0.05	(*)	6
AS	0654	Wheat and straw fodder, Dry	1		6

74 DISULFOTON

VB	0400	Broccoli	0.1	6
VB	0041	Cabbages, Head	0.2	6
VB	0404	Cauliflower	0.05	6
VL	0482	Lettuce, Head	1	6
VL	0483	Lettuce, Leaf	1	6

85 PENAMIPHOS

VO	51	Peppers	0.5		6
VO	448	Tomato	0.5		6
VC	432	Watermelon	0.05	(*)	6

90 CHLORPYRIFOS-METHYL

GC	0640	Barley	10		6
GC	0647	Oats	10		6
GC	0649	Rice	10	Po	6

94 METHOMYL

FP	0226	Apple	2		6
FP	0230	Pear	0.3		6

96 CARBOFURAN

VC	4199	Cantaloupe	0.2	6
VC	0424	Cucumber	0.3	6
FC	0206	Mandarin	0.5	6	Originate from the use of carbosulfan
FC	0004	Oranges, Sweet, Sour	0.5	6	Originate from the use of carbosulfan
VC	0431	Squash, Summer	0.3	6
VO	0447	Sweet corn (corn-on-the-cob)	0.1	6

103 PHOSMET

FS	0240	Apricot	10	6
FB	0020	Blueberries	15	6
FC	0001	Citrus fruits	3	6
FS	0245	Nectarine	10	6
FP	0230	Pome fruit	10	6

117 ALDICARB

FI	327	Banana	0.2		6
VR	0589	Potato	0.5		6

126 OXAMYL

FC	0001	Citrus fruits	3	6
VC	0424	Cucumber	1	6
VC	0046	Melons, except watermelon	1	6
VO	0051	Peppers	5	6

135 DELTAMETRIN

0053

Leafy vegetables

145 CARBOSULFAN

AB	0001	Citrus pulp, Dry	0.1	6
FC	206	Mandarin	0.1	6
FC	0004	Oranges, Sweet, Sour	0.1	6

166 OXYDEMETON-METHYL

FP	0226	Apple	0.05		6
GC	0640	Barley	0.05	(*)	6
AS	640	Barley straw and fodder, Dry	2		6
VB	0041	Cabbages, Head	0.05	(*)	6
MF	0812	Cattle fat	0.05	(*)	6
VD	526	Common bean (dry)	0.1		6
SO	0691	Cotton seed	0.05		6
PE	0112	Eggs	0.05	(*)	6
FB	0269	Grapes	0.1		6
VL	0480	Kale	0.01	(*)	6
VB	0405	Kohlrabi	0.05		6
FC	0204	Lemon	0.2		6
MM	0097	Meat of cattle, pigs & sheep	0.05	(*)	6
ML	0106	Milks	0.01	(*)	6
FC	0004	Oranges, Sweet, Sour	0.2		6
FP	0230	Pear	0.05		6
MF	0818	Pig fat	0.05	(*)	6
VR	0589	Potato	0.05	(*)	6
PF	0111	Poultry fats	0.05	(*)	6
PM	0110	Poultry meat	0.05	(*)	6
GC	650	Rye	0.05		6
AS	650	Rye straw and fodder, Dry	2		6
MF	0822	Sheep fat	0.05	(*)	6
VR	0596	Sugar beet	0.05	(*)	6
AV	0596	Sugar beet leaves or tops	0.05	(*)	6
GC	0654	Wheat	0.05	(*)	6
AS	654	Wheat straw and fodder, Dry	2		6

193 FENPYROXIMATE

FP	226	Apple	0.3	6
FB	269	Grapes	1	6
FC	4	Oranges, Sweet, Sour	0.2	6

203 SPINOSAD

0812

Cattle milk

204 ESFENVALERATE

SO	0691	Cotton seed	0.05	6
VO	0448	Tomato	0.1	6
GC	0654	Wheat	0.05	6

APPENDIX VII

PROPOSED DRAFT GUIDELINES ON THE USE OF MASS SPECTROMETRY (MS) FOR IDENTIFICATION, CONFIRMATION AND QUANTITATIVE DETERMINATION OF RESIDUES - At Step 3 of the Codex Procedure

Confirmatory Tests

Whenever chromatographic techniques are used in screening or confirmation proper settings of the retention time windows is pivotal. Care should be taken that the instrument is adjusted correctly before starting the analysis, a system suitability test should be performed prior to each batch of analysis¹. Retention times data base should be adjusted for the current conditions². In phase 1 tolerance intervals of 1.5 to 3% of the absolute retention time may be applied for capillary GC depending on the peak shape. For confirmation of the retention time the absolute tolerance intervals will increase at higher retention time. The tolerance interval should be less than 1 sec for an RT less than 500 sec. For retention times between 500 and 5000 sec. an interval of 0.2% RRT is recommended. For higher retention times 6 sec. is an suitable interval.
Confirmatory tests may be quantitative and/or qualitative but, in most cases, both types of information will be required. Particular problems occur when residues must be confirmed at or about the limit of determination but, although it is difficult to quantify residues at this level, it is essential to provide adequate confirmation of both level and identity.
The need for confirmatory tests may depend upon the type of sample or its known history. In some crops or commodities, certain residues are frequently found. For a series of samples of similar origin, which contain residues of the same pesticide, it may be sufficient to confirm the identity of residues in a small proportion of the samples selected randomly. Similarly, when it is known that a particular pesticide has been applied to the sample material there may be little need for confirmation of identity, although a number of randomly selected results should be confirmed. Where “blank” samples are available, these should be used to check the occurrence of possible interfering substances.
The necessary steps to positive identification are a matter of judgement on the analyst’s part and particular attention should be paid to the choice of a method that would minimise the effect of interfering compounds. The technique(s) chosen depend(s) upon the availability of suitable apparatus and expertise within the testing laboratory.

Gas Chromatography/Mass spectrometry (GC/MS)

Residue data obtained using mass spectrometry can represent the most definitive evidence and, where suitable equipment is available, it is the confirmatory technique of choice. The technique is also used commonly for residue screening purposes (phase 1). Mass spectrometric determination of residues is usually carried out in conjunction with a chromatographic separation technique to provide retention time ion mass/charge ratio and abundance data simultaneously. Quantitative transmission of labile analytes through the chromatographic system is subject to problems similar to those experienced with other detectors. For quantification, the ions monitored should be those that are the most specific to the analyte, are subject to least interference and provide good signal-to-noise ratio.
When using selected ion monitoring (SIM), tolerance intervals of ion ratios and retention times based on injection of pesticide standard in pure solvent at the concentration close to critical level should have been established at this point. The tolerance intervals for the ion ratios should be within the limits of ± 30 % of absolute ion abundances ratios. When 2 (or 3) selected ion ratios are within the established tolerance intervals the residue is confirmed³. For a small number of pesticides the mass spectrum may only exhibit one specific ion. In this case alternative confirmation should be sought.

When the ions detected still indicate the possible presence of a residue the result may be reported as tentatively identified. However, when the result would lead to regulatory action, further confirmation of analyte identity shall be sought. This can be achieved with the same GC-MS equipment, by injecting matrix-matched standards of the suspected analyte, in order to compensate for matrix influence on ion ratios. In this case subsequent injections of matrix matched standard and suspected sample has to be made. The deviation of RRT of analyte in standard and suspected peak in sample should typically be less than 0.1 %. Two ion ratios measured in a sample should be within the tolerance interval calculated based on the ion ratios in matrix-matched standard. The residue is considered to be confirmed if it complies with the general rule stated above. If the ion rations are not within the tolerance intervals, additional confirmation of identity may be obtained by the use of alternative analytical techniques, examples are listed in Table 6.

Further confirmation by mass spectrometry can be accomplished by acquisition of the “complete electron-impact mass spectrum (in practice generally from m/z50 to beyond the molecular ion region. The absence of interfering ions is an important consideration in confirming identity. Additional confirmation of identity may be obtained by (i) the use of an alternative chromatographic column; (ii) by the use of an alternative ionisation technique (eg chemical ionization); (iii) by monitoring further reaction products of selected ions by tandem mass spectrometry (MS/MS or MSⁿ); or (iv) by monitoring selected ions at increased mass resolution.

Mass spectrometric determinations should satisfy similar analytical quality control criteria to those applied to other systems.

HPLC and HPLC-MS

Confirmation of residues detected following separation by HPLC is generally more problematic than where gas chromatography is used. If detection is by UV absorption, production of a complete spectrum can provide good evidence of identity. However, UV spectra of some pesticides are poorly diagnostic, being similar to those produced by many other compounds possessing similar functional groups or structures, and co-elution of interfering compounds can create additional problems. UV absorption data produced at multiple wavelengths may support or refute identification but, in general, they are not sufficiently characteristic on their own. Fluorescence data may be used to support those obtained by UV absorption. LC-MS can provide good supporting evidence but, because the spectra generated are generally very simple, showing little characteristic fragmentation, results produced from LC-MS are unlikely to be definitive. LC-MS/MS is a more powerful technique, combining selectivity with specificity, and often provides good evidence of identity. LC-MS techniques tend to be subject to matrix effects, especially suppression, and therefore confirmation of quantity may require the use of standard addition or isotopically-labelled standards. Derivatisation may also be used for confirmation of residues detected by HPLC (Table 6).

Thin Layer Chromatography (TLC)
In some instances, confirmation of gas chromatographic findings is most conveniently achieved by TLC. Identification is based on two criteria, Rf value and visualisation reaction. Detection methods based on bioassays (e.g. enzyme -, fungal growth or chloroplast inhibition) are especially suitable for qualitative confirmation as they are specific to certain type of compounds, sensitive and normally very little affected by the co-extracts^4,5. The scientific literature contains numerous references to the technique⁶. The quantitative aspects of thin-layer chromatography are, however, limited. A further extension of this technique involves the removal of the area on the plate corresponding to the Rf of the compound of interest followed by elution from the layer material and further chemical or physical confirmatory analysis. A solution of the standard pesticide should always be spotted on the plate alongside the sample extract to obviate any problems of non-repeatability of Rf. Over-spotting of extract with standard pesticide can also give useful information. The advantages of thin layer chromatography are speed, low cost and applicability to heat sensitive materials; disadvantages include (usually) lower sensitivity and separation power than instrumental chromatographic detection techniques and need for more efficient cleanup in case of detections based on chemicals colour reactions.
Derivatisation
When selecting ions for GC/MS confirmation based on a derivative, the selected ions must be structurally significant for the residue and not only represent fragments of the derivatizing agent. Whereas derivatisation might be a valuable way to confirm the identity of a residue, it should be taken into account that it will also add an extra element to the uncertainty of a quantitative confirmation .
This area of confirmation may be considered under three broad headings.
(a) Chemical reactions
Small-scale chemical reactions resulting in degradation, addition or condensation products of pesticides, followed by re-examination of the products by chromatographic techniques, have frequently been used. The reactions result in products possessing different retention times and/or detector response from those of the parent compound. A sample of standard pesticide should be treated alongside the suspected residue so that the results from each maybe directly compared. A fortified extract should also be included to prove that the reaction has proceeded in the presence of sample material. Interference may occur where derivatives are detected by means of properties of the derivatising reagent. A review of chemical reactions which have been used for confirmatory purposes has been published by Cochrane, W.P. (Chemical derivatisation in pesticide analysis, Plenum Press, NY (1981)). Chemical reactions have the advantages of being fast and easy to carry out, but specialised reagents may need to be purchased and/or purified.
(b) Physical reactions
A useful technique is the photochemical alteration of a pesticide residue to give one or more products with a reproducible chromatographic pattern. A sample of standard pesticide and fortified extract should always be treated in a similar manner. Samples containing more than one pesticide residue may give problems in the interpretation of results. In such cases pre-separation of specific residues may be carried out using TLC, HPLC or column fractionation prior to reaction.
(c) Other methods
Many pesticides are susceptible to degradation/transformation by enzymes. In contrast to normal chemical reactions, these processes are very specific and generally consist of oxidation, hydrolysis or de-alkylation. The conversion products possess different chromatographic characteristics from the parent pesticide and may be used for confirmatory purposes if compared with reaction products using standard pesticides.

Table 6. Detection methods suitable for screening (Phase 1) and confirmation (Phase 2) of residues.

		Phase 1 - Screening
		GC with capillary column – ECD, NPD, FPD, PFPD	GC-MS	LC-MS	LC-DAD or scanning UV	LC-UV/VIS (single wavelength)	LC-fluorescence	GC with packed column – ECD, NPD, FPD	TLC – enzyme -, fungal growth or chloroplast inhibition
Phase 2, confirmation	GC – capillary column – ECD, NPD, FPD, PFPD	x¹	x¹	x	x	x	x	x	x
	GC-MS	x	X¹²	x	x	x	x	x	x
	LC-MS	x	x		x	x	x	x	x
	Full scan techniques	x	x	x	x	x	x	x	x
	(MS)ⁿ, HRMS, alternative ionisation techniques	x	x	x	x	x	x	x	x
	LC-DAD or scanning UV	x	x	x		x	x	x	x
	LC-UV/VIS (single wavelength)	x	x				x	x	x
	LC-fluorescence	x	x		x	x		x	x
	TLC – enzyme, fungal growth or chloroplast inhibition	x	x	x	x	x	x	x	X²³
	Derivatisation	x	x	x	x	x	x	x	x
	Specific isomers profile	x	x	x	x	x	x	x

1 – Either the column of different polarity, which results in different elution order of the residues and contaminants eluting in the vicinity to the peak of interest, or another specific detector shell be used.
2- The same GC-MS technique can be used for the phase 2 (confirmation) if different ions are selected or tolerance intervals are established based on matrix matched solutions.
3 – Mobile or stationary phase of different polarity shall be used.

Undisplayed Graphic

Figure 2. Schematic Representation of Screening and Confirmation (Phase 1 and Phase 2) for Pesticide Residues
1 - Unusual values including banned substances, MRL violation or study requirements as in e.g. exposure assessment
2 – Refer to table 6 for other means of confirmation
3 - For a small number of pesticides the mass spectrum may only exhibit one specific ion. In this case alternative confirmation should be sought.

APPENDIX VIII

PROPOSED DRAFT GUIDELINES ON ESTIMATION OF UNCERTAINTY OF RESULTS
- At Step 3 of the Codex Procedure

1. INTRODUCTION

According to the CCMAS guidelines on measurement uncertainty at step 5 of the Codex procedure, it is a requirement under ISO/IEC 17025 that laboratories determine and make available the uncertainty associated with each analytical method and result. To this end, food laboratories operating under Codex guidelines should have available considerable data derived from method validation /verification, inter-laboratory studies and in-house quality control activities, which can be applied to estimate the uncertainties particularly for the routine methods undertaken in the laboratory.

1.1 CONCEPT AND COMPONENTS OF UNCERTAINTY

Measurement uncertainty refers to the ‘uncertainty’ associated with data generated by a measurement process. In analytical chemistry, it generally defines the uncertainty associated with the laboratory process but may also include an uncertainty component associated with sampling and qualitative confirmation.
The uncertainty ‘estimate’ therefore describes the range around a reported or experimental result within which the true value can be expected to lie within a defined level of probability. This is a different concept to measurement error which can be defined as the difference between an individual result and the true value. The reporting of uncertainty is intended to provide a higher level of confidence in the validity of the reported result.
Contributions to data uncertainty are manifold and described in detail in Tables 1and 2. The evaluation of uncertainty ideally requires an understanding and estimation of the contributions to the uncertainty of each of the activities involved in the measurement process.

2. IDENTIFICATION OF UNCERTAINTY SOURCES

In general, the uncertainty of measurements is comprised of many components, arising from activities involved with the sample. The uncertainty of an analytical result is influenced by three major phases of the determination:

Ø External operations: sampling (S_S), packing, shipping and storage of samples⁷;
Ø Preparation of test portion: sample preparation and sample processing (S_Sp);
Ø Analysis (S_A): extraction, cleanup, evaporation, derivatisation, instrumental determination
The combined standard (S_Res) and relative (CV_L) uncertainty may be calculated according to the error propagation law:
; (1)
If the whole sample is analysed the mean residue remains the same and the equation can be written as:
and CV_{L =} (2)

2.1 ERRORS IN ANALYTICAL MEASUREMENTS

In most measurements we can distinguish between three types of errors: gross, random and systematic errors.
Gross errors refer to unintentional/unpredictable errors while generating the analytical result. Errors of this type invalidate the measurement. Laboratory quality assurance procedures should minimize gross errors. It is not possible or desirable to statistically evaluate and include the gross errors in the estimation of uncertainty. They need no further discussion in this document.
Random errors are present in all measurements, and cause replicate results to fall on either side of the mean value. The random error of a measurement cannot be compensated for, but increasing the number of observations and training of the analyst may reduce the effects.

Systematic errors occur in most experiments, but their effects are quite different. The sum of all the systematic errors in an experiment is referred to as the bias. Since they do not sum to zero over a large number of measurements, individual systematic errors cannot be detected directly by replicate analyses. The problem with systematic errors is that they may go undetected unless appropriate precautions are taken. In practice, systematic errors in an analysis can only be identified if the analytical technique is applied to a reference material, the sample is analysed by another analyst or preferably in another laboratory, or by re-analysing the sample by another analytical method. However, only if the reference material matches identically in terms of analyte, matrix, and concentration does it meet the ideal conditions for determining the bias of the method. The bias of a method may also be investigated by recovery studies. However, recovery studies assess only the effects of analysis (S_A) and do not necessarily apply to naturally incurred samples, or components of the bias that may be introduced prior to the analytical step. In pesticide analysis, results are not normally corrected for the recovery, but should be corrected if the average recovery is significantly different from 100%. If the result has been corrected for recovery, the uncertainty associated with recovery should be incorporated in the uncertainty estimation of the measurement.
Some examples of sources of errors are illustrated in Tables 1 and 2 It should be noted that not all sources mentioned have to be evaluated in the uncertainty estimation. Some sources are already incorporated in the overall uncertainty, while others are negligible and may be disregarded. However, it is important to recognise and assess all sources before elimination. Further information may be obtained from published documents⁸,⁹.

Table 1: Sources of error in preparation of the test portion

	Sources of systematic error	Sources of random error
Sample preparation	The portion of sample to be analysed (analytical sample) may be incorrectly selected	The analytical sample is in contact and contaminated by other portions of the sample
		Rinsing, brushing is performed to various extent, stalks and stones may be differentially removed
Sample processing (S_Sp)	Decomposition of analyte during sample processing, cross contamination of the samples	Non homogeneity of the analyte in single units of the analytical sample
		Non homogeneity of the analyte in the ground/chopped analytical sample
		Variation of temperature during the homogenisation process
		Texture (maturity) of plant materials affecting the efficiency of homogenisation process

Table 2: Sources of error in analysis (S_A):

	Sources of systematic error	Sources of random error
Extraction/Cleanup	Incomplete recovery of analyte	Variation in the composition (e.g. water, fat, and sugar content) of sample materials taken from a commodity
Extraction/Cleanup	Interference of co-extracted materials (load of the adsorbent)	Temperature and composition of sample/solvent matrix
Quantitative determination	Interference of co-extracted compounds	Variation of nominal volume of devices within the permitted tolerance intervals
	incorrect purity of analytical standard	Precision and linearity of balances
	Biased weight/volume measurements	Incomplete and variable derivatisation reactions
	Operator bias in reading analogue instruments, equipment	Changing of laboratory-environmental conditions during analysis
	Determination of substance which do not originate from the sample (e.g. contamination from the packing material)	Varying injection, chromatographic and detection conditions (matrix effect, system inertness, detector response, signal to noise variation etc.)
	Determination of substance differing from the residue definition	Operator effects (lack of attention)
	Biased calibration	Calibration

3. PROCEDURES FOR ESTIMATING MEASUREMENT UNCERTAINTY

Whilst there are a number of options available to laboratories for the estimation of measurement uncertainty, there are two preferred procedures described commonly as the ‘bottom up’ approach and the ‘top down’ approach¹,¹⁰

The bottom-up method:

The bottom up or component-by-component approach incorporates an activity-based process whereby the analyst breaks down all the analytical operations into primary activities. These are then combined or grouped into common activities and an estimate made of the contribution of these activities to the combined uncertainty value of the measurement process. The bottom up approach can be very laborious and requires a detailed knowledge of the whole analytical process. The benefit to the analyst is that this approach provides a clear understanding of the analytical activities which contribute significantly to the measurement uncertainty and which therefore may be assigned as critical control points to reduce or manage measurement uncertainty in future applications of the method.

The top-down method:

The top down approach is based on method validation and long-term precision data derived from laboratory control samples, proficiency testing results, published literature data and/or inter-laboratory collaborative trials. Uncertainty estimates based on inter-laboratory studies may also take into account the between-laboratory variability of the data and is likely to provide the most reliable estimate of the method performance and the uncertainty associated with its application. It is important to acknowledge however that collaborative studies are designed to evaluate the performance of a specific method and participating laboratories. They normally do not evaluate imprecision due to sample preparation or processing as the samples generally tend to be highly homogenized.

Pesticide residue analytical laboratories normally look for over 200 residues in numerous commodities that lead to practically infinite number of combinations. Therefore it is recommended that, for estimating the uncertainty associated with multi residue procedures, laboratories use a properly selected range of analytes and sample matrices which represents the residues and commodities to be analysed in terms of physical chemical properties and composition according to the relevant parts of the Revised Guidelines on Good Laboratory Practice instead of establishing the uncertainty for each method/analyte/matrix combination.
In summary, laboratories should use either their own long-term precision data or the activity-based procedure (component by component calculation) to establish and refine the uncertainty data.
In certain situations it may also be appropriate to estimate the uncertainty contribution due to sample variability. This will require an understanding of the analyte variability within the sample lot and is not readily available to the laboratory or the analyst The values obtained from the statistical analysis of over 8500 residue data (Table 4) provide currently the best estimate¹¹. These estimates can be incorporated into the combined uncertainty value.
Likewise it may be necessary to take into consideration the stability of analytes during sample storage and processing if these are likely to result in analyte variability between analysts and laboratories.

3.1 UNCERTAINTY ESTIMATES OF RESULTS INVOLVING ANALYSIS OF MULTI-COMPONENTS

The estimation of uncertainty of results for multi-component residues arising from the application of technical mixtures including structural and optical isomers, metabolites and other breakdown products may require a different approach particularly where the MRL has been established for the sum of all or some of the component residues. The assessment of the random and systematic errors of the results based on the measurements of multiple peaks is explained in detail in a recent publication¹² and should be consulted where necessary.

4. GUIDANCE VALUES FOR ACCEPTABLE UNCERTAINTIES

The establishment of the standard deviation of a series of tests ran by a single laboratory, as a measure of standard uncertainty, requires the results a large data-set that is not always available. However, for smaller amounts of data the true standard deviation can be estimated as follows:
Depending on the number of observations (n), the relation of the true (σ) standard deviations, calculated (S) standard deviations, and the expected range of the mean value () at 95% probability are illustrated in Table 3. The multiplying factor, f, provides the link between the estimated and true values as the function of the number of measurements.
Table 3 The values of f for calculation of expected ranges of standard deviation and mean values

n	S_min=f₁σ	S_max=f₂σ	= ±f₃S
	f₁	f₂	f₃
5	0.35	1.67	1.24
7	0.45	1.55	0.92
15	0.63	1.37	0.55
31	0.75	1.25	0.37
61	0.82	1.18	0.26
121	0.87	1.13	0.18

The guidance values for standard uncertainty, given in Table 4, are based on a large number of data and can be used to assess the reality of the estimated uncertainty in a laboratory in order to avoid an unreasonable high or low value.

Table 4. Typical expected uncertainties of major steps of pesticide residue analysis

Procedure	Relative uncertainty	Comments
Sampling of commodities of plant origin. Reflects the variation of mean residues being in composite samples taken randomly from a lot. It does not incorporate the errors of follow-up procedures.	Medium and small commodities. (Sample size ≥10)^a: 26-30%^b	For testing compliance with MRLs, the sampling uncertainty is 0, as the MRLs refer to the average residues in bulk samples.
	Large commodities. (Sample size ≥5)^a: 36-40%^b
Sampling of animal products	The relation between the number of samples (n) to be taken for detection of a specified percentage of violation (β_p) with a given probability (β_t), is described by^a: 1-β_t = (β_p)ⁿ	The primary samples should be selected randomly from the whole lot.
Sample processing Includes the physical operation performed for homogenizing the analytical sample and subsampling , but excludes decomposition and evaporation of analytes.	Largely varying depending on sample matrix and equipment. No typical value can be given. The analysts should try to keep it²below 8-10%.	It may be influenced by the equipment used for chopping / homogenising the sample and the sample matrix, but it is independent from the analyte.
Analysis It includes all procedures performed from the point of spiking of test portions.	Within laboratory reproducibility: 16-53% for concentrations of 1μg/kg to 1 mg/kg^c. Average between- laboratories reproducibility within 0.001-10 mg/kg: 25%^d	The typical CV_A can be conveniently determined from the recovery studies performed with various pesticide-commodity combinations on different days and during the use of the method.

Notes:
(a) Codex Secretariat. Recommended method of sampling for the determination of pesticide residues for compliance with MRLs, ftp://ftp.fao.org/codex/standard/en/cxg_033e.pdf .
(b) Ambrus A. Soboleva E. Contribution of sampling to the variability of residue data; www.iaea.org/trc
(c) Codex Secretariat, Revised Guidelines on Good Laboratory Practice in Residue Analysis ftp://ftp.fao.org/codex/alinorm03/al03_41e
(d) Alder L., Korth W., Patey A., van der Schee and Schoeneweis S., Estimation of Measurement Uncertainty in Pesticide Residue Analysis, J. AOAC International, 84, 1569-1578, 2001
In addition to the estimated uncertainties made by the individual laboratories, regulatory authorities and other risk managers may decide on a default expanded uncertainty of measurements which can be used in judging compliance with MRLs (See section 5) based on between-laboratories reproducibility values. For instance, a 50% expanded uncertainty for CV_L is considered to be a reasonable default value.

5. USE OF UNCERTAINTY INFORMATION

If required, the result should be reported together with the expanded uncertainty, U, as follows
Result = x ± U (units)
The expanded uncertainty, U, may be calculated from the standard combined uncertainty (S_Res) with a coverage factor of 2 as recommended by EURACHEM or with the Student t value for the level of confidence required (normally 95%) where the effective degree of freedom is less than 20. The respective calculations for the expanded uncertainty are as follows
U = 2S_Res or U = t_ν,0.95S_Res
The numerical value of the reported results should follow the general rule that the last digit can be uncertain. Rounding the results should be done only when the final result is quoted since rounding at the initial stages of calculation may introduce unnecessary bias in the calculated values.

APPENDIX IX

ANNEX 1: Proposals to Include of new Commodities in the Codex Classification

Proposed Code	Commodity	Scientific name	Synonyms	Remarks	Proposed by
FRUITS
FC Citrus fruits

FP Pome fruits

FS Stone fruits
	Davidson plum	Davidsonia pruriens F. Muell.		This is a tropical fruit with edible peel, not a stone fruit	Australia
FB Berries and other small fruits
	Azarole	Crataegus azarolus	Mediterranean medlar	This is a pome fruit?	EU
FT Assorted tropical and sub-tropical fruits – edible peel
	African plum	Vitex doniana	Black plum		USA
	aisen	Boscia senegalensis			USA
	almondette	Buchanania Lanzan Spreng.	chiraulinut		USA
FT/FI?	Banana bell	Musa spp.		flower of plant	Australia
	bignay	Antidesma bunius (l.) Spreng.	Chinese-laurel		USA
	Brazil cherry	Eugenia brasiliensis Lam.	Grumichama		USA
	Burmese grape	Baccaurea dombeyi.	baccaurea		USA
	cajou	Anacardium giganterum			USA
	Cattley guava	Psidium cattleianum	purple guava, strawberry guava		USA
	cherry of the Rio Grande	Eugenia aggregata DC.	cereja		USA
	Chinese white olive	Canarium album (Lour.) Raeusch.			USA
	chirauli nut	Buchanania latifolia Roxb.			USA
	coco plum	Chrysobalanus icaco L.	Icacier Coco palm		USA
	craboo	Byrsonima crassifolia (L.) Kunth	golden-spoon		USA
	Egyptian carissa	Carissa edulis Vahl	carissa plum		USA
	galonut	Anacolosa frutescens (Blume) Blume			USA
	governor's plum	Flacourtia indica (Burm.f.) Merr			USA
	guava berry	Myrciaria Fluor Linde			USA
	Herbert river cherry	Antidesma dallachyanum Baill.	Queenlang cherry		USA
	imbe	Garcinia livingstonei T. Anderson	African mangosteen		USA
	jamaica cherry	Garcinia livingstonei T. Anderson	calabur-tree, capulin		USA
	Java plum	Syzygium cumini (L.) Skeels	jambolan		USA
	jelly palm	Butia capitata (Mart.) Becc.			USA
	kapundung	Baccaurea racemosa (Reinw.) Müll. Arg.	menteng		USA
	karanda	Carissa carandas L.			USA
	kei apple	Dovyalis caffra (Hook. f. & Harv.) Warb.			USA
	maya breadfruit	Brosimum a Licaistum			USA
	miracle fruit	Synsepalum dulcificum (Schumach. & Thon.) Daniell			USA
FI/FT	Fruit salad tree (?) Mexican breadfruit	Monstera deliciosa Liebm.	monstera		Australia
	monos plum	Pseudanamomis umbellifera			USA (PR)
	palmyra palm fruit	Borassus flabellifer L.	doub palm, toddy palm, tala palm		USA
	Pejibaye-peach palm	Bactris gasipaes Kunth			USA
	pithecellobium dulce	Pithecellobium dulce (Roxb.) Benth.	blackbead, camachile		USA
	pitomba	Eugenia luschnatheanis			USA
	Purple mombin	Spondias purpurea L.	hog plum, jocote, imbu		USA
	salak	Salacca zalaceae			USA
	sataw	Parkia speciea			USA
	tallowood	Ximenia americana			USA
	toddy palm fruit	Borassus flabellifer L.			USA
	velvet tamarind	Dialium guineense Willd.	Sierra Leone tamarind		USA
	Waterberry	Syzygium guiveense			USA
	whampi	Clausena lansium			USA

FI Assorted tropical and sub-tropical fruits – inedible peel
	abiu	Pouteria caimito (Ruiz & Pav.) Radlk.	caimito, caimo, cauje		USA, Australia
	Abyssinian gooseberry	Dovyalis absyssinica	Inedible peel		USA
	atemoya	Annona hybrid			USA
	bael fruit	Aegle marmelos			USA
	binjai	Mangifera caesia Jack			USA
	biriba	Rollinia mucosa (Jacq.) Baill.			USA
	champadek	Artocarpus integrr			USA
	Ceylon gooseberry	Dovyalis hebecarpa (Gardner) Warb.	ketembilla		USA
	Florida gooseberry	Dovyalis absycinnica X D. hebecarpa			USA
	horse mango	Mangifera foetida			USA
	kaffir plum	Sclerocarpa birrea	Kaffir-date		USA
	langsat	Lansium domesticum Corrêa	langsep, langsium, lanzon		USA
	marang	Autocarpus odoratissimus Blanco			USA
	monkeyfruit	Artocarpus spp			USA
	monstera	Monstera deliciosa Liebm.	Mexican breadfruit		USA
	pandanus	Pandanus sp.			USA
	pitaya	Hylocereus spp. Hylocereus undatus			Australia
	poshte	Annona scleroderma			USA
	pulasan	Nephylium ramboutan-ake (labill.) Leenh.			USA
	satinleaf	Chrysophyllum oliviforme L.	damson plum, wild star apple, caimitillo		USA
	screwpine	Pandamu utilis			USA
	sun sapote	Licania platypus			USA
	white star apple	Chrysophyllum albudum G. Don			USA

VEGETABLES
VA Bulb vegetables

VB Brassica (cole or cabbage) vegetables, Head cabbages, flowerhead brassicas

VC Fruiting vegetables, Cucurbits
	Chilacayote	Cucurbita ficifolia Bouché	Black-seed squash, fig-leaf gourd		Australia
	Kiwano	Cucumis metuliferus	African horned melon. Horned cucumber		EU
VO Fruiting vegetables, other than Cucurbits
	Horseradish tree	Moringa oleifera Lam.	Drumstick tree Ben moringa seed	Oilseed, not fruiting vegetable	Australia

VL Leafy vegetables (including Brassica leafy vegetables)
	Buffalo spinach	Enydra flucutrans			Australia
	Jew mallow; meloukhia; jute	Corchorus olitorius L.	Nalta Jute		Australia
	Foo Yip	Glinus oppositifolius, Glinus lotoides			Australia
	Perilla; beefsteak plant	Perilla frustescens(L.)Britton			Australia
VP Legume vegetables

VD Pulses

VR Root and tuber vegetables
	Chinese keys	Boesenbergia rotunda (L.) Mansf.			Australia
	Ginseng	Panax quinquefoluim L.			USA
	Japanese ginger, Myoga ginger	Zingiber mioga (Thunb.) Roscoe		Also dried\Spring shoots and flower buds	Australia
	Lotus root; east Indian lotus	Nelumbo nucifera Gaertn.			Australia
	Rettich	Raphanus L. sp.		White variety of black radish	EU
	Wasabi; Japanese horse radish	Wasabia japonica (Miq.)Matsum.			Australia
	(chinese) water chestnut	Eleocharis dulchis (Burm.f.)Trin. Ex Hensch.			Australia
VS Stalk and stem vegetables
	Lemongrass	Cymbopogon citratus(DC.)Stapf		Herbs, not stalk and stem.	Australia
GC Cereal grains

TN Nuts and seeds

CO Oilseed
	Evening primrose	Oenothera biennis L.			EU
	Pumpkin seed	Cucurbita pepo var. oleifera Pietsch			EU
HH Herbs
	Cuphea	Cuphea spp		Oilseed???	USA
	Garden dahlia	Dahlia pinnata Cav. X D. coccinea			USA
	Cilantro, leaf	Coriandrum sativum	Coriander leaf		Australia, EU
	Daylily	Hemerocallis fulva (L) L.		Bulb vegetable??	USA
	Dokudami	Houttoynia cordata Thumb.			USA
	Epazote	Chenopodium ambrosioides L			USA
	Euphorbia	Euphorbia lathyris L.			USA
	Evening primrose	Oenothera biennis L.	See also Oilseed		USA
	Flameflower	Talinum triangulare (Jacq.) Willd.			USA
	Zenmai fern	Osmunda japonica thunb.			USA
	Edible flowers				USA
	Geranium (scented, lemon, rose)	Pelargonium spp.			USA
	Globe mallow	Sphaeralcea spp.			USA
	Kaffir lime leaves Mauritius papeda	Citrus hystrix DC.			Australia
	Melilot, field	Melilotes Officinalis (L.) PALLAS			EU
HH/HS	Lemon myrtle; lemon ironwood	Backhousia citriodora F. Muell.			Australia
	Vietnamese mint; hot mint; Vietnamese coriander;	Polygonum odoratum Lour.			Australia
	White ginger	Hedychium coronarium J Konig			USA
	Ginkgo	Ginkgo biloba L.			USA
HS Spices
	Japanese ginger, Myoga ginger	Zingiber mioga (Thunb.) Roscoe		Also dried\Spring shoots and flower buds	Australia
	Lemongrass	Cymbopogon citratus(DC.)Stapf		Herb???	Australia
	Green pepper, fresh	Piper nigrum L.		Immature form of black or white pepper	EU
	Native mountain pepper	Kunzea pomifera F. Muell.			Australia
	Riberry	Syzygium leuhmannii			Australia
	Wattle seed; acacia seed	Acacia spp.			Australia
DT Teas
	Red tea bush; rooibos	Aspalathus linearis (Burm.f.) R.Dahlgren			Australia

ANNEX 2: PROPOSAL FOR REGROUPING COMMODITY GROUPS

FC Group 1 Citrus fruits
• Small citrus fruits (e.g. lemons, limes, mandarins)
• Big citrus fruits (e.g. oranges, shaddocks, pomelos)
(A problem could be the division of the commodities among the two groups, as there exists a lot of varieties from one crop being on the one hand small and on the other hand big.)
FB Group 4 Berries and small fruits
• 4-1 Cane berries (e.g. blackberries, raspberries, dewberries)
• 4-2 Bush berries (e.g. blueberries, currants and gooseberries)
• 4-3 Other small fruited berries (e.g. grapes, strawberries)
VA group 9 Bulb vegetables
• 9-1 Bulbs (e.g. onions, shallots)
• 9-2 Whole bulb vegetables (e.g. spring onions) (whole plants without roots)
VB group 10 Brassica vegetables
• 10-1 Flowerhead cabbages (e.g. cauliflower, broccoli)
• 10-2 Head cabbages (e.g. cabbage, white, red)
• 10-3 Leafy Brassicas (codes from Leafy vegetables e.g. Chinese cabbage, mustard greens)
kohlrabi?
VC group 11 Fruiting vegetables, Cucurbits
• 11-2 Edible peel (e.g. cucumber, courgette)
• 11-2 Inedible peel (e.g. melon, pumpkins)
VO group 12 Fruiting vegetables, other than Cucurbits
• 12-1 Solanaceae (e.g. tomatoes, peppers)
• 12-2 Mushrooms
VL group 13 Leafy vegetables (including Brassica leafy vegetables) change in Leafy vegetables, except Brassica leafy vegetables
VR group 16 Root and tuber vegetables
A new group is proposed for the foliage of root and tuber vegetables or the tops or leaves should be added to the leafy vegetable group and to the animal feeds (sugar beet tops).
GC group 20 Cereal grains
• 20-1 Small grains (e.g. millet, teff)
• 20-2 Grains (e.g. wheat, barley, rice)
• 20-3 Immature grains (e.g. sweet corn)

ANNEX 3: OTHER AMENDMENTS (SYNONYMS, SCIENTIFIC NAMES, EXPANSION OF CODES, REGROUPING)

Proposed Code	Commodity	Latin name	Synonyms	Remarks	Proposed by
Proposals for crossreferences
HH 4 HH 0727	Garlic chives	Alium tuberosum		Cross reference to VA	Australia
HH 4 HH 0727	Garlic chive flowers	Alium tuberosum		Cross reference to VA	Australia
HS 0784	Ginger, root	Zingiber officinale		Cross reference to VR	Australia
HS 0794	Turmeric, root	Cucurma longa		Cross reference to VR	Australia
Proposals to extent codes
VO 4 VO 0440	Thai eggplant	Solanum undatum		Expand Eggplant code	Australia
VO 4 VO 0440	Pea aubergine	Solanum torvum		Expand Eggplant code	Australia
VL 0473	Watercress	Roripa nasturtium aquaticumSynomym of N. officinalis		Inclusion of Roripa under code VL 0473	Australia
VD 0531	Hyacinth bean	Lablab purpureus(L.)Sweet subsp purpureus		Inclusion of purpureus variety	Australia
VR 0576	Canna, edible, Old arrowroot	Canna indica		Inclusion of indica variety	Australia
	La lot	Piper longum, P. sarmentosum		Ammendment for VL 0489 Pepper leaves	Australia
Proposals to regroup individual commodities
FT 4123, FT 312	Tamarillo			Regrouping to FI (inedible peel)	New zealand
VO 447 VO 1275	Sweet corn			Regroup to Cereal grains GC	USA
FI 339	Jambolan			Regrouping to FT (edible peel)
VA 380	Fennel bulb			Regroup to VS	NL
Proposals to update scientific names
VB 0401	Chinese broccoli; Gai lan	Brassica oleracea var. alboglabra	kailan	Current scientific name incorrect	Australia
VS 627	Rhubarb	Rheum x hybridum		Current scientific name incorrect	USA
Adition of synonyms
VL 486	Warrigal greens; New zealand spinach	Tetragonia tetragonoides (Pall.) Kuntze		Add synonym	Australia
	Taro, Japanese	Colocasia antiquorum		Synonym of Taro VR 0505	Australia

APPENDIX X

PROPOSED REVISED CRITERIA FOR PRIORITIZATION PROCESS

PROCEDURE FOR PROPOSING PESTICIDES FOR CODEX PRIORITY LISTS

Member countries are required to nominate chemicals for the Priority List using the following procedure:

1. GENERAL CRITERIA

1.1 Criteria for Inclusion of Compounds on the Priority List

Before a pesticide can be considered for the Priority List it:
(a) must be available for use as a commercial product; and
(b) must not have been already accepted for consideration.
To meet the criteria for inclusion in the priority list the use of the pesticide must: give rise to residues in or on a food or feed commodity moving in international trade, the presence of which is (or may be) a matter of public health concern and thus create (or have the potential to create) problems in international trade.

1.2 Criteria for Selecting Food Commodities for which Codex MRLs or EMRLs should be Established

The commodity for which the establishment of a Codex MRL or EMRL is sought should be such that it may contain pesticide residues and form a component of international trade. A higher priority will be given to commodities that represent a significant proportion of the diet.

2. CATEGORISING THE TYPE OF EVALUATION PROPOSED

Governments are recommended to check if the pesticide is already in the Codex system.
NOTE: Pesticide/commodity combinations which are already included in the Codex system or under consideration are found in a working document prepared for and used as a basis of discussion at each Session of the Codex Committee on Pesticide Residues. Consult the document of the latest session to see whether or not a given pesticide has already been considered.
If the pesticide is not in the Codex system, governments should prepare a proposal for evaluation by completing the Appendix “Pesticide Information for CCPR” below.
In this process:
(i) consult with the manufacturer(s) about the existence of sufficient toxicological and residue data and confirm that the manufacturer(s) would be willing to submit data to the JMPR, and in what year, and;
(ii) submit the information to the Ad hoc Working Group on Priorities with a copy to the Secretary, Codex Alimentarius Commission using the format in the Appendix “Pesticide Information for CCPR”.

2.1 New Chemicals

For new chemicals the information to satisfy the criterion of whether the propose new chemical is a “safer” or “reduced risk” chemical should be provided using Item 6 “Justification for use” of Section on Pesticide Information for CCPR below.
The nominating country is required to provide:
• The names of the chemical(s) the proposed chemical is likely to replace;
• A summary of acute and chronic dietary exposure calculations encompassing the range of diets considered by the CCPR; and

• Other relevant information to support the proposed new chemicals as a replacement chemical.
2.2 Periodic Re-evaluation

2.2.1 Chemicals that have not been reviewed toxicologically for more than 15 years and/or not having a significant review of maximum residue limits for 15 years taking into account the heavy workload of JMPR will be nominated as the Ad hoc Working Group on Priorities for consideration for review.
2.2.2 Governments may wish to propose a pesticide for re-evaluation and to do so according to Section Pesticide Information for CCPR below.

2.3 Evaluation

Where the pesticide has already been evaluated by the JMPR and MRLs, EMRLs or GLs have been established the following situations may arise:
2.3.1 The JMPR may note a data deficiency in a Periodic Re-evaluation or New Chemical evaluation.
In response, industry or other interested parties may pledge to supply the information to the appropriate Joint Secretary of the JMPR with a copy to the Chair of the Working Group on Priorities. Following scheduling in the JMPR tentative schedule, the data from industry or other interested parties should be submitted subsequently to the appropriate Joint Secretary of the JMPR.
2.3.2 The CCPR may place a chemical under the four-year rule, in which case the government or industry should indicate support for the specific CXLs to the FAO Joint Secretary of the JMPR, with a copy to the Chair of the Working Group on Priorities. Following scheduling in the JMPR tentative schedule, any data in support of maintenance of the CXL(s) would be submitted to the FAO Joint Secretary of the JMPR.
2.3.3 Where a government member or industry seeks to expand the use of an existing Codex chemical; that is, obtain MRLs for one or more new commodities where some CXLs already exist for other commodities. The request for consideration would be directed to the FAO Joint Secretary of the JMPR and copied to the Chair of the Working Group on Priorities. Following scheduling in the JMPR tentative schedule, the data would be submitted to the FAO Joint Secretary of the JMPR.
2.3.4 A government member or an industry may seek to expand the use of an existing CXL. For example a new GAP may necessitate a larger MRL. In this case the request should be made to the FAO Joint Secretary with a copy to the Chair of the Working Group on Priorities. Following scheduling in the JMPR tentative schedule, the data would be submitted to the FAO Joint Secretary of the JMPR.
2.3.5 Where the CCPR requests a clarification or reconsideration of a recommendation from the JMPR, the relevant Joint Secretary will schedule the request for the next JMPR.
2.3.6 Where a serious public health concern exists in relation to a particular pesticide, government members should notify the WHO Joint Secretary of the JMPR promptly and provide appropriate data to the WHO Joint Secretary.

3. CRITERIA FOR PRIORITIZATION

3.1 New Chemicals

When prioritising new chemicals for evaluation by the JMPR, the Committee will consider the following criteria:
1. If the chemical has a reduced acute and/or chronic toxicity risk to humans compared with other chemicals in its classification (insecticide, fungicide, herbicide);
2. The date nominated;
3. The date that data will be submitted (availability of data);

4. The availability of international/national reviews and coordination with other national/international lists; and
5. Allocating new chemicals to be evaluated on a 50:50 basis with periodic re-evaluation chemicals to be evaluated.
3.2 Periodic Re-evaluation

When prioritising chemicals for periodic re-evaluation by the JMPR: the Committee will consider the following criteria:
1. Chemicals that have not been reviewed toxicologically for more than 15 years and/or not having a significant review of maximum residue limits for 15 years taking into account the heavy workload of JMPR;
2. The year the chemical is listed in the list for Candidate Chemicals for Periodic Re-evaluation –Not Yet Scheduled;
3. The date that data will be submitted;
4. If the intake and/or toxicity profile indicate a high level of public health concern.
5. Whether the CCPR has been advised by a national government that the chemical has been responsible for trade disruption;
6. If there is a closely related chemical that is a candidate for periodic re-evaluation that can be evaluated concurrently;

7. Allocating periodic re-evaluation chemicals to be evaluated on a 50:50 basis with new chemicals to be evaluated.
3.3 Evaluations

When prioritising proposed residue evaluations by the JMPR for food commodities, the Working Group on Priorities will consider the following criteria:
1. The date the request was received;
2. The date the data can be submitted;
3. Whether the data is submitted under the 4-year rule for evaluations of extra data; and
4. The nature of the data to be submitted.

PESTICIDE INFORMATION FOR CCPR

for evaluation
for reevaluation
1. NAME:
2. STRUCTURAL FORMULA:
3. CHEMICAL NAME:
4. TRADE NAME:
5. NAMES AND ADDRESSES OF BASIC PRODUCERS:
6. JUSTIFICATION FOR USE:
7. USES: MAJOR
MINOR
8. COMMODITIES MOVING IN INTERNATIONAL TRADE AND LEVELS OF RESIDUES:
9. COUNTRIES WHERE PESTICIDE IS REGISTERED¹³:

10. NATIONAL MAXIMUM RESIDUE LIMITS:

11. COMMODITIES FOR WHICH THE NEED FOR ESTABLISHING CODEX MRLS IS RECOGNIZED:
12. MAJOR INTERNATIONAL USE PATTERN:
13. LIST OF DATA (TOXICOLOGY, METABOLISM, RESIDUE) AVAILABLE:
14. DATE DATA COULD BE SUBMITTED TO THE JMPR:
15. PROPOSAL FOR INCLUSION SUBMITTED BY (COUNTRY):

APPENDIX XI

PRIORITY LIST OF CHEMICALS SCHEDULED FOR EVALUATION AND RE-EVALUATION BY JMPR

The following are the tentative schedules to be evaluated by the FAO/WHO Joint Meeting on Pesticides Residues (JMPR) from 2004 to 2013

2004 JMPR

Toxicological evaluations	Residue evaluations
New compounds	New compounds
Fludioxinil	fludioxinil
trifloxystrobin	trifloxystrobin
	pyraclostrobin

Periodic re-evaluations	Periodic re-evaluations
glyphosate (158)	ethoprophos (149)
phorate (112)	metalaxyl-M
pirimicarb (101)	paraquat (057)
propiconazole (160)	prochloraz (142)
triadimefon (133) {should be evaluated	propineb
triadimenol (168) {together

Evaluations	Evaluations
bentazone (172) - acute toxicity	chlorpyrifos (017)
captan (007) – acute toxicity
dimethipin (151) – acute toxicity	folpet (041)
fenpropimorph (188) – acute toxicity	fenitrothion (037)
fenpyroximate (193) – acute toxicity	malathion (047)

folpet (041) – acute toxicity	methomyl (094)
	oxydemeton-methyl (166)
	pirimiphos-methyl (086)
	spinosad (203)

2005 JMPR

Toxicological evaluations	Residue evaluations
New compounds	New compounds
dimethenamid-P	dimethenamid-P
fenhexamid	fenhexamid
indoxacarb	indoxacarb
novaluron	novaluron
sulfuryl fluoride	sulfuryl fluoride

Periodic re-evaluations	Periodic re-evaluations
benalaxyl (155)	alpha and zeta cypermethrin
clofentezine (156)	cypermethrin (118)
cyhexatin (067)/azocyclotin (129)	cyhexatin (067)/ azocyclotin (129)
propamocarb (148)	endosulfan (032)
	glyphosate (158)
	methoprene (147)
	phorate (112)
	terbufos (167)

Evaluations	Evaluations
carbendazim (072) –acute toxicity	ethoxyquin (035)
chlorpropham (201)	guazatine (114)
ethoxyquin (035	methiocarb (132)
guazatine (114)
haloxyfop (194)
imazalil (110) – acute toxicity
thiabendazole (065)

2006 JMPR

Toxicological evaluations	Residue evaluations
New Compounds	New Compounds
bifenazate	bifenazate
dimethomorph	dimethomorph
pyrimethanil	pyrimethanil
quinoxyfen	quinoxyfen

Periodic re-evaluations	Periodic re-evaluations
cyromazine ( 169)	pirimicarb (101)
alfa and zeta cypermethrin (118)	propiconazole (160)
flusilazole (165)	triazophos (143)
procymidone (136)	triadimefon (133) {should be evaluated
profenofos (171)	triadimenol (168) {together

Evaluations	Evaluations
pirimiphos-methyl (086) –acute toxicity	propargite (113)
thiophanate-methyl (077) – acute toxicity

2007 JMPR

Toxicological evaluations	Residue evaluations
New Compounds	*New Compounds*

zoxamide	zoxamide

Periodic re-evaluations	Periodic re-evaluations
azinphos-methyl (002)	clofentezine (156)
cyfluthrin/beta cyfluthrin (157)	permethrin (120)
fentin (040)	propamocarb (148)
vinclozolin (159)	triforine (116)
lamda-cyhalothrin
Evaluations	Evaluations

2008 JMPR

Toxicological evaluations	Residue evaluations
New Compounds	New Compounds
Periodic re-evaluations	Periodic re-evaluations
bioresmethrin (93)	benelaxyl (155)
buprofezin (173)	cyromazine (169)
chlorpyrifos-methyl (090)	lamba-cyhalothrin replacement of cyhalothrin
hexythiazox (176)	flusilazole (165)
	procymidone (136)
	profenofos (171)

Evaluations	Evaluations

2009 JMPR

Toxicological evaluations	Residue evaluations
New Compounds	New Compounds
Periodic re-evaluations	Periodic re-evaluations
bifenthrin (178)	azinphos-methyl (002)
cadusafos (174)	cyfluthrin/beta cyfluthrin (157)
chorothalanil (081)	fentin (040)
cycloxydim (179)	vinclozolin (159)

Evaluations	Evaluations

2010 JMPR

Toxicological evaluations	Residue evaluations
New Compounds	New Compounds
Periodic re-evaluations	Periodic re-evaluations
aldicarb (117)	bioresmethrin (93)
dicofol (026)	buprofezin (173)
dithianon (028)	chlorpyrifos-methyl (090)
fenbutatin oxide (109)	hexythiazox (176)

Evaluations	Evaluations

2011 JMPR

Toxicological evaluations	Residue evaluations
New Compounds	New Compounds

Periodic re-evaluations	Periodic re-evaluations
dichlorvos (025)
diquat (031)	amitraz (122)
etofenprox (184)	bifenthrin (178)
fenpropathrin (185)	cadusafos (174)
	chorothalanil (081)

Evaluations	Evaluations

2012 JMPR

Toxicological evaluations	Residue evaluations
New Compounds	New Compounds

Periodic re-evaluations	Periodic re-evaluations
	aldicarb (117)
	cycloxydim (179)
	dithianon (028)
	fenbutatin oxide (109)

Evaluations	*Evaluations*

2013 JMPR

	Toxicological evaluations	Residue evaluations
New Compounds	New Compounds

Periodic re-evaluations	Periodic re-evaluations
	dichlorvos (025)
	dicofol (026)
	diquat (031)
	etofenprox (184)
	fenpropathrin (185)

Evaluations	Evaluations

ANNEX I
CHEMICALS PROPOSED FOR PRIORITY LISTING BUT FOR WHICH FURTHER CONSIDERATION IS REQUIRED BEFORE A DECISION CAN BE MADE.

DDT (EMRLs)
Gentamicin, oxytetracycline hydrochoride.
MRLs for various pesticides on spices based on monitoring data.

APPENDIX XII

PROPOSED DRAFT AND REVISED DRAFT MAXIMUM RESIDUE LIMITS FOR PESTICIDES
(Retained at Step 7 and 4)

				MRL (mg/kg)		Step	Note

194 HALOXYFOP

AL	1021	Alfalfa forage (green)	5	fresh wt	4
MO	1280	Cattle kidney	1		4
MO	1281	Cattle liver	0.5		4
MM	812	Cattle meat	0.05		4
ML	812	Cattle milk	0.3		4
PE	0840	Chicken eggs	0.01	(*)	7
PM	0840	Chicken meat	0.01	(*)	7
PO	0840	Chicken, Edible offal of	0.05		7
SO	0691	Cotton seed	0.2		7
OC	0691	Cotton seed oil, Crude	0.5		7
AM	1051	Fodder beet	0.3		7
AV	1051	Fodder beet leaves or tops	0.3	fresh wt	4
SO	0697	Peanut	0.05		7
VP	0063	Peas (pods and succulent=immature seeds)	0.2		7
VR	0589	Potato	0.1		7
VD	0070	Pulses	0.2		7
SO	0495	Rape seed	2		7
OC	0495	Rape seed oil, Crude	5		7
OR	0495	Rapeseed oil, Edible	5		7
CM	1206	Rice bran, Unprocessed	0.02	(*)	7
CM	0649	Rice, Husked	0.02	(*)	7
CM	1205	Rice, Polished	0.02	(*)	7
OC	0541	Soya bean oil, Crude	0.2		7
OR	0541	Soya bean oil, Refined	0.2		7
VR	0596	Sugar beet	0.3		7
AV	596	Sugar beet leaves or tops	0.3	fresh wt	4
SO	0702	Sunflower seed	0.2		7

201 CHLORPROPHAM

MM	0812	Cattle meat	0.1	(fat)	7
ML	0812	Cattle milk	0.0005	(*)	7
MO	0812	Cattle, Edible offal of	0.01	(*)	7
VR	0589	Potato	30	Po	7

¹ Soboleva E. Ambrus A., Application of system suitability test for quality assurance and performance optimization of a gas chromatographic system for pesticide residue analysis, J. Chromatogr. A. 1027. 2004. 55-65.

² Lantos J., Kadenczki L., Zakar F., Ambrus A. Validation of gas chromatographic Databases for qualitative identification of active ingredients of pesticide residues in Fajgelj A. Ambrus A. (eds) Principles of Method Validation, Royal Society of Chemistry, Cambridge, 2000, pp 128-137.

³ Soboleva E. Ahad K. Ambrus A. Applicability of some MS criteria for the confirmation of pesticide residues, http://www.iaea.org/trc

⁴ Ambrus¹* Á.,. Füzesi²I.; Susán² M.; Dobi³ D., Lantos⁴ J., Zakar⁵ F., Korsós⁴ I., Oláh³ J., Beke³ B.B., and L. Katavics⁵ A cost effective screening methods for pesticide residue analysis in fruits, vegetables and cereal grains, J. Environ Sci. Health B39 2004 accepted for publication.

⁵ Ambrus Á.; Füzesi I.; Lantos J.; Korsos I.; Hatfaludi T. Repeatability and Reproducibility of Rf and MDQ Values with Different TLC Elution and Detection Systems. J. Environ Sci. Health B39 2004 accepted for publication.

⁶ IUPAC Report on Pesticides (13) (Bátora, V., Vitorovic, S.Y., Thier, H.-P. and Klisenko, M.A.; Pure & Appl. Chem., 53, 1981, 1039-1049

⁷ Packing, shipping, storage, and laboratory preparation of samples may have significant influence on the residues detected, but their contribution to the uncertainty can often not be quantified based on the current information. Examples of such errors are eg selection of sampling position, time of sampling, Incorrect labelling decomposition of analytes or contamination of the sample

⁸ EURACHEM Guide to Quantifying Uncertainty in Analytical Measurements, 2^nd ed. 1999, http://www.measurementuncertainty.org

⁹ Ambrus A. Reliability of residue data, Accred. Qual. Assur. 9, pp. xx. 2004

¹⁰ ISO, Guide to the Expression of Uncertainty in Measurement, ISO. Geneva, 1993

¹¹ Ambrus A and Soboleva E. Contribution of sampling to the variability of residue data; www.iaea.org/trc

¹² Soboleva E., Ambrus A., Jarju O., Estimation of uncertainty of analytical results based on multiple peaks, J. Chromatogr. A. 1029. 2004, 161-166

¹³ Countries should provide detailed information on the registration status at the time of proposing a compound for inclusion in priority lists and again when the compound is scheduled for JMPR review.

008 CARBARYL

113 PROPARGITE

126 OXAMYL

130 DIFLUBENZURON

135 DELTAMETRIN

162 TOLYLFUANID

203 SPINOSAD

100 METHAMIDOPHOS

145 CARBOSULFAN

162 TOLYLFUANID

008 CARBARYL

74 DISULFOTON

100 METHAMIDOPHOS

113 PROPARGITE

126 OXAMYL

130 DIFLUBENZURON

135 DELTAMETRIN

137 BENDIOCARB

162 TOLYLFUANID

007 CAPTAN

008 CARBARYL

74 DISULFOTON

90 CHLORPYRIFOS-METHYL

117 ALDICARB

126 OXAMYL

135 DELTAMETRIN

145 CARBOSULFAN

166 OXYDEMETON-METHYL

203 SPINOSAD

Confirmatory Tests

1. INTRODUCTION

2. IDENTIFICATION OF UNCERTAINTY SOURCES

3. PROCEDURES FOR ESTIMATING MEASUREMENT UNCERTAINTY

4. GUIDANCE VALUES FOR ACCEPTABLE UNCERTAINTIES

5. USE OF UNCERTAINTY INFORMATION

Commodity

FRUITS

FP Pome fruits

FS Stone fruits

FB Berries and other small fruits

FT Assorted tropical and sub-tropical fruits – edible peel

FI Assorted tropical and sub-tropical fruits – inedible peel

VEGETABLES

VA Bulb vegetables

VB Brassica (cole or cabbage) vegetables, Head cabbages, flowerhead brassicas

VC Fruiting vegetables, Cucurbits

VO Fruiting vegetables, other than Cucurbits

VP Legume vegetables

VD Pulses

VR Root and tuber vegetables

VS Stalk and stem vegetables

GC Cereal grains

TN Nuts and seeds

CO Oilseed

HH Herbs

HS Spices

DT Teas

Commodity

Proposals for crossreferences

Proposals to extent codes

Proposals to regroup individual commodities

Proposals to update scientific names

Adition of synonyms

PROPOSED REVISED CRITERIA FOR PRIORITIZATION PROCESS

PROCEDURE FOR PROPOSING PESTICIDES FOR CODEX PRIORITY LISTS

1. GENERAL CRITERIA

2. CATEGORISING THE TYPE OF EVALUATION PROPOSED

3. CRITERIA FOR PRIORITIZATION

PESTICIDE INFORMATION FOR CCPR

APPENDIX XI

PRIORITY LIST OF CHEMICALS SCHEDULED FOR EVALUATION AND RE-EVALUATION BY JMPR

New compounds

New compounds

Periodic re-evaluations

Periodic re-evaluations

Evaluations

Evaluations

dimethipin (151) – acute toxicity

fenpropimorph (188) – acute toxicity

New compounds