Differentiating Organically Farmed Rice from Conventional and Green

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Differentiating Organically Farmed Rice from Conventional and Green Rice Harvested from an Experimental Field Trial using Stable Isotopes and Multi-Element Chemometrics Yuwei Yuan, Weixing Zhang, Yongzhi Zhang, Zhi Liu, Shengzhi Shao, Li Zhou, and Karyne M. Rogers J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.7b05422 • Publication Date (Web): 08 Feb 2018 Downloaded from http://pubs.acs.org on February 9, 2018

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Journal of Agricultural and Food Chemistry

Differentiating Organically Farmed Rice from Conventional and Green Rice Harvested from an Experimental Field Trial using Stable Isotopes and Multi-Element Chemometrics YuweiYuan1,3+, Weixing Zhang2, Yongzhi Zhang1,3, Zhi Liu1,3, Shengzhi Shao1,3, Li Zhou1,3, Karyne M. Rogers4* 1

Institute of Quality and Standards for Agricultural Products, Zhejiang Academy of Agricultural Sci-

ences, Hangzhou 310021, P.R. China 2

China National Rice Research Institute, Hangzhou 310006, P.R. China

3

Key Laboratory of Information Traceability for Agricultural Products, Ministry of Agriculture,

Hangzhou 310021, P.R. China 4

National Isotope Centre, GNS Science, 30 Gracefield Road, Lower Hutt 5040, New Zealand

+

Corresponding Author 1: [email protected]

*Corresponding Author 2: [email protected]

ACS Paragon Plus Environment


1

ABSTRACT

2

Chemometric methods using stable isotopes and elemental fingerprinting were used to character-

3

ize organically grown rice from green or conventionally grown rice in experimental field trials in Chi-

4

na. Carbon, nitrogen, hydrogen and oxygen stable isotopes as well as 26 elements were determined.

5

Organic rice was found to be more depleted in 13C than green and conventionally grown rice due to

6

uptake of enriched 13C from carbon dioxide and methane respiring bacteria, and more enriched in 15N

7

due to volatilization of nitrogen from urea and ammonium of animal manures used to manufacture the

8

organic composts. Chemometrics (PCA and LDA) were used to separate the three farming methods

9

and provide a promising scientific tool to authenticate the farming methods of different rice cultivars

10

fertilized with animal manures, composts and synthetic fertilizers in China or elsewhere.

11 12

KEYWORDS: Rice; Organic; Stable isotope; Multi-element; Linear discriminant analysis (LDA);

13

Chemometrics


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INTRODUCTION

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Rice is the most widely consumed staple food in the world. The highest global producer of rice is

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China, with a total output of above 166.20 million tons in 2003 which accounts for around 36.9% of

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the world’s rice output1. Around 65% of Chinese people rely on rice as their daily staple food, so cer-

18

tification and testing undertaken by government authorities and regulatory agencies to assess rice

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safety and quality in China is increasingly important to consumers to assure food safety2.

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Over the last 10 years, a rapidly growing Chinese economy has led to a consumer focal change

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away from food supply to food safety3, in particular heavy metals and mycotoxin contaminations,

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which have significant health hazards when found at higher concentrations in foods. Recent reports

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suggest that up to 10% of rice samples collected from six provinces across China were contaminated

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with heavy metals, 70% of the rice samples tested exceeded the maximum residue limits (MRL) of

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cadmium in southern China, and 16% of rice samples exceeded the safety levels for lead in one

26

coastal region4-6.

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Consumers are now rapidly turning to organically labeled foods in China, with China being the

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fourth largest consumer of organic foods after USA, Germany and France7. However, as organic

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products command much higher prices than conventionally grown products, there is now a demand

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for scientific tests which can differentiate between organic and other production methods to assure

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consumers about food safety and prevent fraud in labeling8.

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Currently organic authentication is achieved through certification rather than through any partic-

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ular analytical test9. However more frequently multi-isotope and elemental chemometric techniques

34

are used to identify methods of agricultural production. Specifically, nitrogen isotopes (δ15N) have

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been shown to effectively discriminate organic and conventional farming systems, as organic fertiliz-

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ers are generally enriched in

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occurs with the storage or processing of organic fertilizers from NH3 volatilization10-11. Sulphur (δ34S)

38

and oxygen (δ18O)can be useful for discriminating fertilizer origins while other light isotopes such as

39

carbon (δ13C) and hydrogen (δD) are more useful for country of origin studies or water availability12-

40

13

15

N compared to synthetic fertilizers due to isotopic fractionation that

. Multi-elemental fingerprints have also been shown to be useful to compare products grown in or-



41

ganic soils from those grown in conventional soils14, or geographical origin of wheat15 and onions

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from farms in Japan16.

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Organic rice production in China has also rapidly grown to account for about 35% of total organ-

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ic grain production (92 million tons in 2016)17, however there are only a few studies which use iso-

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topes and/or trace elements to discriminate production methods of organic rice from conventional

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rice18. Stable isotope ratios reflect various climatic and human induced factors, while trace elements

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provide a fingerprint of the soil (both geological and anthropogenic inputs). δ13C values depend on the

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CO2 photosynthetic fixing pathways such as C3 and C4 cycles in plants19-20, although other factors

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such as drought, solar radiation, temperature, atmospheric pressure and stress can also change the iso-

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topic values21. Multi-isotope compositions of Japanese, USA and Australian rice were used to investi-

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gate country of origin but not organic production methods, in which the study found that the Japanese

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rice samples could easily be distinguished from Australian and USA rice based on climate, nutrients

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and irrigation water differences between each country22.

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However other external influences may affect the δ13C values of rice, particularly the CO2 re-

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spired by heterotrophic and methanogenic bacteria (methanotrophs) which can affect carbon dynamics

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in rice fields23-24, 48. Nitrogen is shown to stimulate the growth and activity of methane-oxidizing bac-

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teria, particularly where ammonium and urea based fertilizers are used, but especially with organic

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animal manures25-29.These comparative studies demonstrate the different levels of CO2/CH4 produced

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from rice fields where rice is grown in adjacent fields under the same climatic conditions but using

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different fertilizer conditions (chemical or organic fertilizer). Lin et al.30 showed the high availability

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of methanogenic substrate present in organic fertilizers (straw, animal manures etc.) as a prime reason

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for high CH4 emissions in organic fields. The use of pesticides and their inhibiting side effects on CH4

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producing microbes were proposed as the reason for lower methane emissions from conventional

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farms.

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Nitrogen isotopes traditionally indicate the use of synthetic versus organic manures which differ-

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entiate organic from conventional farming systems, although when combinations of both types of ma-

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nures are used in variable quantities, this can be confounding31-32. In the case where nitrogen from N-


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fixing plants such as legumes (e.g. hairy vetch) is incorporated into soils as fertilizers, it can also be

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difficult to see isotopically distinct differences33. In a recent rice study31, organic and synthetic N-

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fertilizer inputs became less isotopically distinct over time, and green manures incorrectly suggested a

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synthetic source due to their N-fixing ability. However, when multi-element chemometrics are com-

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bined with stable isotopes, it is possible to tease apart mixed organic and conventional fertilizer appli-

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cations31.

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Hydrogen and oxygen isotopes of rice reflect the irrigation water and/or precipitation in the area

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of cultivation34, but also depends on rainfall amount, water use efficiency and evaporative effects in

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the region which may fractionate the isotopes22. Until this study, hydrogen isotopes have not been

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used to investigate the incorporation of hydrogen in rice from methane production in rice paddy

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fields.

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Although recent elemental studies have found some key trace element differences that exist between

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organic and conventional rice samples14, 35, we propose that the addition of stable isotopes (δ13C, δ15N,

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δ2H and δ18O) to multi-element analyses will strengthen the discrimination between organic and con-

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ventionally grown rice for different cultivars, and for the first time investigate green farmed rice

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which is becoming more popular as an alternative to organic rice. Multi-isotopic and elemental

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chemometrics have already shown promise for other types of crops31-32, 36-38.

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Agricultural practices such as fertilization, irrigation, insect and disease control and routine man-

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agement to cultivate the rice crops are dependent on specific agricultural regulations; where organic

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systems do not allow the use of pesticides or synthetic fertilizers, and must be chemical free for more

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than three years, green systems use green manures, synthetic fertilizers and reduced pesticide levels

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(compared to conventional farming practices), and conventional systems also allow pesticides and

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synthetic fertilizer treatments39. Given the more frequent occurrence of incorrectly applied fertilizer

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treatments where it is not possible to verify that a product is completely organic (small amounts of

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pesticides and fertilizers may be used) or in instances where synthetic fertilizers may contaminate or-

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ganic produce, it is now important to be able to clearly distinguish genuine organic rice from green or

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conventionally produced rice. Therefore, the objective of this work is to undertake experimental field

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trials using multi-isotopic and elemental fingerprinting with chemometric approaches to find a reliable



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and feasible strategy that can differentiate organic, green and conventional rice. Our goal is to develop

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discrimination technique which can be applied to test in-market products, assuring food safety, im-

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proving consumer confidence and combating fraud in high-value organic rice.

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MATERIALS AND METHODS

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Fertilizer Treatments and Growing Systems

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Rice was grown under experimental field trials of Jiaxian Rice Product Company in 2014, locat-

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ed at Danyang City, Jiangsu Province, China. Three cultivars of Japonica rice were used in the trials:

104

Xiaoyangjing (XYJ, OryzaStiva, L.japonica), Jiayin 2 (JY2, OryzaStiva, L.japonica) and Jiayin 3 (JY3,

105

OryzaStiva, L.japonica). Rice seedlings were sown into trays on 14th May, transplanted into fields on

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20th June with row spacing’s of 30 cm×20 cm, and harvested on 25th November (a total growing time

107

of around 6 months). Environmental variables (e.g. rainfall, climate, irrigation water ) were eliminated

108

by planting rice in three adjacent experimental fields and irrigating using the same water source to

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ensure the investigation focused specifically on the different fertilizer effects, and each variety un-

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derwent three fertilizer treatments (i.e. organic, green and conventional) to exclude any effects from

111

the different rice varieties.

112

The organic rice cultivation area was prepared by applying flowering Chinese milk vetch

113

(Astragalus membranaceus) as a base mulch, then rape cake or expeller (pressed rapeseed after the oil

114

is expressed). Free-ranging ducks provided further manure, and were used to control weeds and in-

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sects, along with the use of light traps to attract and kill insects. Green rice cultivation was undertaken

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on soil that was fallowed over winter, then a base fertilizer of 15 kg NPK compound fertilizer (nitro-

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gen-phosphorus-potassium with 15-15-15), with additional rape cake and 10 kg urea per 667 m2 ap-

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plied. Pesticide sprays were applied four times during the growing season to control rice sheath blight,

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plant hoppers and leaf rollers, while herbicides were applied twice to kill grass, broad leaf and sedge

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weeds. Ducks were also used to provide additional fertilizer, insect and weed control. For convention-

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al rice cultivation, the soil was fallowed over winter, a basal fertilizer of 20 kg compound fertilizer

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(N-P-K with 15-15-15) and 15 kg urea per 667 m2 was applied. Pesticide sprays were applied six

123

times during their growth period to control rice sheath blight, plant hoppers and leaf rollers, while


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herbicides were applied twice to kill grass and broad leaf and sedge weeds. Ducks were not used due

125

to the higher levels of pesticides and herbicides applied to conventional rice crops.

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Sample Collection and Preparation

127

At maturation, 5 rows of rice (where each row consists of 10 plants) were collected from each

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different rice variety and the three different growing sites in triplicate. Around 150 ears of rice were

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put into large nylon mesh bags to air-dry in direct sunlight before threshing. Air-dried samples were

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milled to a fine powder, then further dried in oven at 65°C for 48 h before stable isotope analysis .In

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total 27 samples were collected; 9 samples for each farming practice of each three rice cultivars.

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Stable Isotope Analytical Procedure

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Approximately 4.5 mg (for δ13C and δ15N) and 1.5 mg (for δ2H and δ18O, equilibrated for 3 days

134

in a desiccator) of powdered rice was weighed into 4×11 mm tin capsules for stable isotope analysis.

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All samples were analyzed according to Yuan et al.31 The temperature for the elemental analyzer oxi-

136

dation and reduction furnace for δ13C and δ15N isotopes was set at 920 and 600 °C, respectively with

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the carrier gas (He) flow rate of 230 mL min−1. Pyrolysis (δ2H and δ18O) was undertaken at 1450°C,

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with the carrier gas (He) flow rate of 120 mL min−1.

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Isotope ratios were determined using the following Eq 1:

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δsample (‰)=[Rsample/Rstandard -1]×1000.............................................................(1)

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Where sample represents either δ13C, δ15N, δ2H or δ18O, and R value denotes the isotope ratio of

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13

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sion and reproducibility were better than 0.15, 0.2, 1.5 and 0.3‰ for δ13C, δ15N, δ2H andδ18O, respec-

144

tively.

C/12C, 15N/14N, 2H/1H or 18O/16O in the analytical sample and IAEA standards. The analytical preci-

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Primary reference materials (IAEA, International atomic energy agency, Vienna) were used for

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multi-point calibration of isotope ratio, i.e. IAEA-N1 (NH4SO4, δ15N=0.4±0.2‰), USGS24 (Graphite,

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δ13C=16±0.1‰), VSMOW (Ocean water, δ2H=0‰), SLAP (δ2H=-428.0‰), IAEA601 (δ18Ovsmow=

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23.3±0.3‰), and IAEA602 (δ18Ovsmow=71.4±0.5‰). High purity (>99.99%) CO2 (δ13C=-27.92±

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0.15‰), N2 (δ15N=-1.3 ±0.2‰), H2 (δ2H=-222.6±1.5‰) and CO (δ18O=14.6±0.3‰) served as refer-

150

ence gas.



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Pb Isotope Ratio and Multi-elemental analysis by ICP-MS

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Powdered rice (approximately 200.00 mg) was digested in duplicate in acid-washed 60 mL mi-

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crowave oven vessels containing 5.0 mL HNO3, then heated in a microwave digestion system (Mile-

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stone Ethos one, ITA) under temperature control mode. After cooling, 1.0 mL of H2O2 was added to

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the vessels, then they were placed on a graphite heater at 160°C to evaporate the acid until the diges-

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tion liquid volume was reduced to around 1.0 mL. The cooled digested liquids were subsequently di-

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luted to 25.0 mL with deionized water and analyzed using ICP-MS (Thermo Fisher iCA Qc, Thermo

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Co. Ltd., USA). The Pb isotope ratio (206Pb/207Pb and 208Pb/206Pb) was measured with the ratio mode,

159

and a kinetic energy discrimination (KED) mode was used to determine elemental concentrations. An

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internal standard solution (10 ng/mL) containing a mixture of Y (GSB04-1788-2004), Sc (GSB04-

161

1757-2004), Ge (GSB 04-1728-2004), Rh (GSB 04-1746-2004) and Re (GSB 04-1745-2004) was

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prepared using standards purchased from National Centre of Analysis and Testing for Nonferrous

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Metals & Electronic Materials (Beijing, China) to monitor and check instrument drift. A standard so-

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lution containing all 24 elements was also obtained from Sigma-Aldrich and diluted into five different

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concentrations with milliQ water for calibration. Certified powdered rice reference materials; Hunan

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rice (GBW10043) and Liaoning rice (GBW10043) were obtained from National Research Center for

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Certified Reference Materials (Beijing, China) and used as interlaboratory quality control samples

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(QA/QC) to evaluate the accuracy of measurement. Multi-elemental analysis resulted in the detection

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of 24 elements in rice, which could be divided into three groups based on their relative concentrations.

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Group 1 included 7Li, 9Be,

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Group 2 included

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where the concentrations ranged from 0.1 to 10 mg/kg, 10 to 500 mg/kg and 1.0 to 50.0 g/kg, respec-

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tively. The limits of detection (LODs, µg/kg) for trace elements in Group 1 were 0.33, 0.04, 0.08, 0.12,

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0.03, 0.04, 0.08, 0.02, 0.29, 0.04, 0.15, 0.02, 0.09, 0.07, respectively, which was far lower than the

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concentrations in rice.

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Statistical Analysis

27

Al,

55

51

Mn,

V,52Cr, 56

Fe,

65

59

Co,

Zn,

85

60

Ni,

Rb,

64

138

Cu,

69

Ga,

95

Mo,107Ag,

Ba; Group 3 included

111

23

Cd,

Na,

24

133

Cs,

Mg,

39

205

Tl,

K and

208

44

Pb;

Ca,

177

One-way analysis of variance (ANOVA) was performed on SPSS software (ver.19.0) using the

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general linear model procedure to test the difference between various farming practices and means of


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variables were directly separated by Tukey’s comparison test. The programs for PCA and follow-up

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LDA modeling were performed on MATLAB (ver. 2015b) and were previously scripted in our la-

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boratory.

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Unsupervised Chemometric Analysis

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Principal component analysis (PCA) was used to discriminate rice samples from three different

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growing methods into homogeneous groups according to multi-elements and multi-isotopes data. A

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Data matrix of 27×26 (samples×varibles) was first normalized column-wise to unit vectors and then

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mean-centered according to Eq.2-3. The three PC’s with the largest variances were used to cluster rice

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samples.

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=

189

=

........................................................................................(2)

∑

............................................................................(3)

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Where, yij is the new data after applying unit vector and mean-centered, the Si is the standard devia-

191

tion of xi.

192

Supervised Chemometric Analysis

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Supervised pattern recognition methods (Linear Discriminant Analysis; LDA) were used to im-

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prove classification patterns found using PCA. LDA was undertaken on PCs (with accumulative vari-

195

ance >90%) to establish two orthogonal linear discriminant variable functions to classify different

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farming methods by simultaneously maximizing the variances of between-group and within-group

197

measured variables. A test set validation procedure was applied to assess the performance of the es-

198

tablished LDA model. Each individual case was sequentially used to estimate the model constants,

199

and then group membership was determined from the resulting model and compared to its original

200

group to calculate the classification success rate. PCA and LDA were performed using MATLAB

201

2015a (The MathWorks, Inc., USA) with in-house laboratory-built scripts.

202 203

RESULTS AND DISCUSSION

204

Rice Yield



205

Rice yields for each cultivar and cultivation method were determined (in kg/667 m2). XYJ rice

206

cultivar had the lowest yields of the three cultivars, and JY3 rice cultivar had the highest overall yield

207

(Table 1). However, it was found that JY3 rice cultivars had lower yields under organic cultivation

208

than when grown using conventional and green methods. Conversely, XYJ rice cultivars had higher

209

yields under organic methods than under green or conventional methods, and JY2 rice cultivars had

210

similar yields for all three farming methods.

211 212

Insert Table 1 here Stable Isotopes

213

Carbon isotopes range between -27.0 and -28.1 ‰, with JY3 rice having more positive δ13C val-

214

ues, and JY2 rice having more negative δ13C values (Figure 1, Table 2). Rice cultivation has been

215

identified as a significant source of greenhouse gas (GHG), specifically releasing carbon dioxide, me-

216

thane, nitrous oxide from heterotrophic bacterial decompostion of organic matter and methanogenic

217

bacterial respiration associated with the rice rhizosphere region29, 40-42. Moreover, different rice culti-

218

vars have different GHG emission levels depending on their physiology43-44, with high yielding culti-

219

vars suggested to have lower GHGs emissions than lower yielding traditional cultivars45. Hetero-

220

trophic decomposition of the organic matter releases 13C-depleted CO2, while methanogenic bacteria

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consume isotopically light methane which is also released during the fermentation of organic material

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and in return respire CO2. However, this the CO2 released from both processes is isotopically lighter

223

(c. -40 ‰) than atmospheric CO2 (c. -8 ‰) due to fractionation. Where higher GHG emissions occur,

224

rice δ13C values may display slightly more negative δ13C values than rice with lower GHG emissions

225

from photosynthesis of the released 13C-depleted CO2.

226

Although organic rice had slightly more negative δ13C values than its corresponding convention-

227

al and green farmed rice (Figure 1) with ∆13Cconv-org values of 0.4 ‰ for XYJ, 0.2 ‰ for JY2 and 0.1 ‰

228

for JY3, the difference was not significant. This small δ13C shift in organic rice is most likely caused

229

depleted CO2 from the bacterial fermentation and decomposition of organic manures in the paddy

230

field which can be absorbed by the rice plant. Slightly more positive δ13C values found in convention-

231

al and green manured rice may conversely be due to a reduction in bacterial fermenta-


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tion/decomposition of manure with the absence of organic composts. Ammonium fertilization stimu-

233

lates methane production in organic farming systems, increasing methanotrophic (oxidizing) bacterial

234

growth and activity25-26, 46 stimulating 12CO2 production and consequently more negative 13C rice val-

235

ues from the extra 12CO2 photosynthetic uptake. Ammonium is mostly derived from animal excretion

236

which has undergone denitrification, and in this study, both organic and green farming methods used

237

duck manure. While synthetic ammonium fertilizers were added to green and conventionally grown

238

rice, there was either insufficient ammonium to stimulate methane production, or pesticide application

239

could have reduced or removed the methanotrophic bacteria from the soil, as the δ13C values were not

240

as depleted as the organically grown rice. It has also been reported that the use of pesticides (in green

241

or conventional farming) can potentially kill or severely reduce the methanotrophs associated with

242

paddy fields, removing the available source of

243

notrophic respiration30. Regardless, δ13C of rice is a result from a range of complicated C processes

244

and can be highly variable over space and time.

13

C isotopically depleted CO2 derived from metha-

245

Nitrogen (δ15N) isotopes of organic and green farmed rice typically displayed a 2-3‰ enrich-

246

ment in 15N from conventionally farmed rice, typical of the denitrification of organic material and loss

247

of lighter

248

green/organic rice. Optimized fertilizer applications will ensure efficient utilization of nutrient by the

249

rice, leaving little residue for nitrification/denitrification. Rice JY3 had slightly lower δ15N values for

250

organic and green rice than XYJ and JY2, which may be due to the cultivar using the nutrients more

251

quickly before they are denitrified than the other cultivars or that the soil conditions were more anaer-

252

obic, and 14N loss was reduced.

14

N (Figure 1, Table 1). JY3 rice had the lowest ∆15N shift between conventional and

253

Hydrogen isotopes (δ2H) are noticeably different for the three cultivars, even though the same ir-

254

rigation water was applied to all crops. JY3 rice has more positive δ2H values for each growing meth-

255

od by up to 8‰ than the other two cultivars, suggesting that there was less water fractionation by the

256

JY3 rice cultivar. For each cultivar, the conventional and green farming methods have similar δ2H

257

values, but the organic farmed rice from each cultivar have more depleted δ2H values. Apart from cul-

258

tivar water use differences, the most likely reason for more negative δ2H values in organic rice is the



259

additional mulch from the milk vetch (added as a base fertilizer to the organic samples), which reduc-

260

es evapotranspiration, and hence controls the loss of 1H from the rice paddy34. For green and conven-

261

tional growing methods, milk vetch mulch was not applied, so loss of the lighter water isotope in-

262

creased the δ2H values towards more positive values. There was no significant difference between rice

263

species and cultivation methods for oxygen isotopes (δ18O, Table 1).

264

Multi Element Analyses

265

Some elemental concentrations of organic, green and conventional rice were significantly differ208

Pb/206Pb ratios and Li, Na, Ca, Cr, Fe, Ga, Sr, Cs, Ba and Tl

266

ent (p

Differentiating Organically Farmed Rice from Conventional and Green

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