Ruminal Methanogen Community in Dairy Cows Fed Agricultural

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Ruminal methanogen community in dairy cows fed agricultural residues of corn stover, rapeseed, and cottonseed meals Pengpeng Wang, Shengguo Zhao, Xingwen Wang, Yangdong Zhang, Nan Zheng, and Jiaqi Wang J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.6b00708 • Publication Date (Web): 20 Jun 2016 Downloaded from http://pubs.acs.org on June 27, 2016

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Journal of Agricultural and Food Chemistry

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Ruminal methanogen community in dairy cows fed agricultural residues of

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corn stover, rapeseed, and cottonseed meals

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Pengpeng Wang†, ‡, §, ǁ, Shengguo Zhao†, ‡, §, ǁ, Xingwen Wang†, ‡, §, Yangdong Zhang†, ‡, §

, Nan Zheng†, ‡, §, and Jiaqi Wang*, †, ‡, §

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†

State Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese

Academy of Agricultural Sciences, Beijing 100193, People’s Republic of China ‡

Laboratory of Quality & Safety Risk Assessment for Dairy Products of Ministry of

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Agriculture (Beijing), Institute of Animal Science, Chinese Academy of Agricultural

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Sciences, Beijing 100193, People’s Republic of China

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§

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Beijing, 100193, People’s Republic of China

Milk and Dairy Production Inspection Center of Ministry of Agriculture (Beijing),

14 15

ǁ

Pengpeng Wang and Shengguo Zhao contributed equally to this paper.

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*Corresponding author: Jiaqi Wang. Tel: 86-10-62816069, Fax: 86-10-62897587.

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E-mail: [email protected]

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Pengpeng Wang and Shengguo Zhao contributed to experimental design and process,

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data analysis, and manuscript drafting. Xingwen Wang and Yangdong Zhang were

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mainly involved in conducting the experiments. Nan Zheng and Jiaqi Wang mainly

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contributed to experimental design.

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ACS Paragon Plus Environment


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ABSTRACT

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The purpose was to reveal changes in the methanogen community in the rumen of

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dairy cows fed agricultural residues of corn stover, rapeseed, and cottonseed meals,

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compared with alfalfa hay or soybean meal. Analysis was based on cloning and

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sequencing the methyl coenzyme M reductase α-subunit gene of ruminal

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methanogens. Results revealed that predicted methane production was increased

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while populations of ruminal methanogens was not significantly affected when cows

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were fed diets containing various amounts of agricultural residues. Richness and

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diversity of methanogen community were markedly increased by agricultural

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residues addition. The dominant ruminal methanogens shared by all experimental

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groups belonged to rumen cluster C, accounting for 71% of total, followed by order

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Methanobacteriales (29%). Alterations of ruminal methanogen community and

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prevalence of particular species occurred in response to fed agricultural residue

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rations, suggesting the possibility of regulating target methanogens to control

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methane production by dairy cows fed agricultural residues.

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KEYWORDS: rumen, forages, meals, methanogen, diversity

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INTRODUCTION

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Methane (CH4) produced by enteric fermentation in livestock accounts for

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approximately 30% of the total anthropogenic CH4 emissions and for up to 12% of

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dietary energy losses in ruminants1. Mitigation of CH4 emissions from domestic

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animals is of importance as it can enable environmentally and economically

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sustainable stock husbandry. In ruminants, CH4 is an end product of rumen

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fermentation by methanogens, which typically comprise around 3% of prokaryotic

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microbiota in the rumen2. The community structure of rumen methanogens is

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associated with feed efficiency and CH4 production3. Recent studies report that the

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manipulation of methanogen community composition can mitigate enteric CH4

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emissions of ruminants. For example, condensed tannin fractions with higher

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molecular weight in the diet influenced CH4 production levels by inducing a shift in

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ruminal methanogen diversity4. Feeding beef cattle 250 mg/d monensin reduced

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enteric CH4 production by decreasing the numbers of Methanomicroium genus

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members and concurrently increasing the numbers of Methanobrevibacter genus

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members5. Consequently, improved understanding of the methanogen community

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may facilitate mitigation of the production of enteric CH4 in ruminants.

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In some developing countries (e.g., China), alfalfa hay and soybean meals are a

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limited resource because of reduced grassland or cultivated land per capita.

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Therefore, agricultural residues (e.g., corn stover, rapeseed meal, and cottonseed

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meal) are widely used to fully or partially replace the forage or meals with good

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qualities, to decrease the feeding cost of dairy production in these countries. Studies 3



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showed that replacing alfalfa with corn silage reduced CH4 production and yield in

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lactating dairy cows, though the effects were linear or curvilinear6, 7. A diet

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containing corn stover significantly altered the ruminal microbial metabolome, as

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compared with a diet of alfalfa and corn silage8. Furthermore, replacement of

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soybean meal with canola meal reduced ruminal ammonia and branched-chain

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volatile fatty acid production, while improving milk fat and protein yields and

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animal nitrogen utilization, when lactating cows were fed both low and high crude

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protein diets9. Replacing partial soybean meal protein with cottonseed material

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protein generally increased milk fat and protein content while reducing

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branched-chain volatile fatty acid concentrations10.

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However, information about the effects of agricultural residue rations on the

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ruminal methanogen community in dairy cows is limited. Therefore, the current

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study aimed to compare the community structure of ruminal methanogens using

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clone libraries of methyl coenzyme M reductase α-subunit (mcrA) gene derived from

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the rumen of dairy cows fed rations of agricultural residues in China.

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MATERIALS AND METHODS

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Experimental procedures involving the care and management of animals, and the

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collection of rumen fluid, were approved by the Animal Care and Use Committee for

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Livestock issued by the Institute of Animal Science, Chinese Academy of

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Agricultural Sciences (Beijing, China).

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Animals, treatments, and ruminal fluid sampling. Healthy Chinese Holstein

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dairy cows (n = 48), with an average initial body weight of 550 ± 11 kg (55 ± 15 d of 4


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day in milking and milk yield of 31 ± 4 kg), were randomly assigned to one of three

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dietary treatments (n = 16 per treatment) according to a completely randomized

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block design. The three (typical) diets were as follows: (1) a mixture of alfalfa hay

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and corn silage as dietary fiber source and a mixture of soybean, rapeseed, and

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cottonseed meals as dietary protein source (MF diet); (2) corn stover as dietary fiber

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source and a mixture of soybean, rapeseed, and cottonseed meals as dietary protein

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source (CSA diet); and (3) corn stover as dietary fiber source and a mixture of

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rapeseed and cottonseed meals as dietary protein source (CSB diet). The ingredients

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and chemical compositions of the three diets are listed in Table 1 and are the same as

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in a previous study11. The feed was offered ad libitum at 0700, 1400, and 2100 h, and

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animals were milked daily at 0600, 1300, and 2000 h. After 91 days, rumen fluid

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samples were orally collected from each animal before morning feeding (0 h) and 2

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h after the morning feeding. All samples were immediately frozen in liquid nitrogen,

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and subsequently stored at –80 °C until further analyses. The concentrations of

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acetate and propionate in rumen fluid samples were determined by gas

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chromatography as described previously12.

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Calculation of methane production. Methane production (MJ/d) was

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calculated using an equation based on the results of Ellis, et al. 13. Models developed

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in their study and cited in other studies were evaluated using mean squared

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prediction error (MSPE). Comparisons of the square root of MSPE (RMESP) values

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between equations with different predicted means could thus be made to evaluate

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deviation from the observed values. According to the lowest RMESP values, an 5



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equation with three variables of dry matter intake (DMI), acid detergent fiber (ADF),

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and neutral detergent fiber (NDF) for dairy cows was used in the current study: CH4 (MJ/d) = 2.16 (± 1.62) + 0.493 (± 0.192) × DMI (kg/d) – 1.36 (± 0.631) ×

108 109

ADF (kg/d) + 1.97 (± 0.561) × NDF (kg/d)

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DNA extraction. Genomic DNA was extracted from thawed rumen fluid

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samples using a modified cetyltrimethylammonium bromide (CTAB) and bead

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beating method14. Briefly, cells were disrupted by bead beating in CTAB extraction

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buffer (10% CTAB in 0.7 M NaCl solution, mixed with an equal volume of 240 mM

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potassium phosphate, pH 8.0) and phenol:chloroform:isoamyl alcohol (25:24:1).

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Total DNA was precipitated by incubating the samples with ammonium acetate (3 M,

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pH 5.2) and isopropanol at room temperature, followed by centrifugation. Finally,

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the DNA samples were suspended in TE buffer and stored at –20 °C until analysis.

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Cloning and sequencing of mcrA genes. Clone libraries of mcrA genes were

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constructed from ruminal fluid DNA samples. Separate libraries were constructed for

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each dietary treatment before or after the morning feeding (n = 6 libraries: three

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dietary treatments × two sampling time points). Partial sequences of the mcrA genes

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were

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(5′-GGTGGTGTMGGATTCACACARTAYGCWACAGC-3′) and mcrA reverse

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primer (5′-TTCATTGCRTAGTTWGGRTAGTT-3′)15. Each 40 µL PCR reaction

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mixture contained 20 µL of Ex Premix (TaKaRa Bio, Otsu, Japan), 1.0 µL of each

126

primer (10 mM), 17 µL of ddH2O, and 1.0 µL of genomic DNA template. Cycling

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conditions included initial denaturation at 94 °C for 5 min, followed by 35 cycles of

PCR-amplified

using

mcrA

6


forward

primer

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denaturation at 94 °C for 30 s, annealing at 55 °C for 30 s, and elongation at 72 °C

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for 1 min, and a final elongation at 72 °C for 10 min. Amplification products were

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purified using a commercial kit, PureLink® PCR Purification (Invitrogen, CA, USA),

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and were then cloned into pMD™19-T vector (TaKaRa Bio), and used to transform

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Escherichia coli JM109 competent cells, according to the manufacturer’s protocol.

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Approximately equal numbers of positive transformants were randomly picked from

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each library to ensure representative sampling of clones. Clone DNA fragments were

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sequenced using the M13 forward and T7 reverse primers, as described by Matsui, et

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al. 16.

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Phylogenetic and statistical analysis of McrA sequences. All sequences were

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compared with entries in the GenBank nr (non-redundant) database, which excluded

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sequences from environmental and uncultured clones, using BLASTN. Deduced

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amino acid sequences were aligned with CLUSTAL W17, and evolutionary distance

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matrices were calculated based on the Kimura two-parameter algorithm using

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MEGA18. Sequences were assigned to operational taxonomic units (OTUs) on the

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basis of ≥ 94% sequence identity19, according to the furthest-neighbor algorithm,

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using Mothur20. Phylogenetic trees were constructed using one representative

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sequence from each OTU and reference strain sequences from GenBank, as well as

146

the abundance of each OTU. Phylogenetic trees were constructed in MEGA using

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the neighbor-joining method, and the stability of the branches was analyzed with

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1000 bootstrap replications21. Species richness and diversity were estimated using

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Chao 1, Ace, Shannon, and Simpson indices, as implemented in Mothur. Statistical 7



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significance of the differences between libraries was determined by ∫-LIBSHUFF

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analysis, which calculated the integral of the Cramer-von Mises statistic22. The P

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values and ∫-LIBSHUFF were corrected using Bonferroni’s correction, and

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significance was defined at P < 0.05. The heat map and principal component analysis

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(PCA) were constructed and implemented using R version 3.1.1 software (R

155

Foundation for Statistical Computing, Vienna, Austria).

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Real-time quantitative PCR (qPCR). The methanogen population in the

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rumen was quantified using SYBR Green-based real-time quantitative PCR (qPCR)

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assays and ABI 7500HT Fast Real Time PCR System (Applied Biosystems, Foster

159

City,

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(5′-CCGGAGATGGAACCTGAGAC-3′)

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(5′-CGGTCTTGCCCAGCTCTTATT-3′)3.

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uniMet1-R, and mixed genomic DNAs obtained by pooling equal amounts of all

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genomic DNA samples, were used to prepare the qPCR standard. The standard curve

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relating threshold cycles (Ct) to plasmid copy number was obtained by serial

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dilutions of standard plasmid DNA23. Methanogen copy number could thus be

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determined by relating Ct values to the standard curve.

CA,

USA).

The

primers

used

were

and The

primer

uniMet1-F uniMet1-R

pair

uniMet1-F

and

167

The qPCR reaction mixtures (10 µL) contained 5.0 µL of SYBR® Premix Ex

168

Tag® (2×) (TaKaRa Bio), 0.2 µL of ROX Reference Dye II (50×) (TaKaRa Bio), 0.4

169

µL of each primer (10 µM), 1 µL of DNA template (10 ng/µL), and 3 µL of ddH2O.

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The qPCR program consisted of the following three segments: (1) initial

171

denaturation at 95 °C for 30 s; (2) 40 cycles of denaturation at 95 °C for 3 s, and 8


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annealing and elongation at 60 °C for 34 s (with fluorescence detection); and (3)

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melting curve analysis: 95 °C for 15 s, 60 °C for 1 min, and 95 °C for 15 s, with

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continuous fluorescence detection. To minimize variability, both standard and

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genomic DNA samples were routinely run in triplicate using the same master mix in

176

the same PCR plate. A negative sample (blank, without DNA template) was also run,

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using the same primer pair. The qPCR efficiencies were calculated from slopes in

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StepOne™ software, and only samples with efficiencies between 90% and 105%

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were used for analysis24. The total methanogen populations were expressed as

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copies/mL culture samples. Data were logarithmically transformed before statistical

181

analysis. SAS 9.2 Proc GLM procedure (2002) was performed, and the only effect

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set as fixed was treatment.

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RESULTS AND DISCUSSION

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Prediction of CH4 production by dairy cows using mathematical models does not

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involve extensive and costly experiments, although the uncertainty associated with

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each modeled coefficient can be magnified upon combination, resulting in inaccurate

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predictions. In the current study, the predicted CH4 production by dairy cows fed

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CSA and CSB diets was 22.37 and 22.24 MJ/d, respectively, which was significantly

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(P < 0.05) higher than that of dairy cows fed an MF diet (20.47 MJ/d). Corn stover

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in the CSA and CSB diets generally contains relatively low amounts of

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rumen-degradable proteins compared with alfalfa hay and corn silage in the MF diet,

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and mixed meals of rapeseed and cottonseed usually have relatively low starch

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content compared with soybean meal in the MF diet (Table 1). Previous studies 9



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reported that high-quality forage and a high proportion of concentrate in dairy cow

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rations resulted in low amounts of produced enteric CH425. Protein fermentation

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produces almost 30–50% less CH4 than the fermentation of carbohydrates26. These

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observations are in agreement with our results, although our CH4 production values

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were predicted. In addition, there were no significant differences between treatments

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on the total methanogen population, based on qPCR data (Table 2). Some studies

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also observed the phenomenon of increased CH4 production accompanied by

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unchanged total methanogen population, which suggests that little correlation exists

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between CH4 emission and methanogen abundance27. Thus, we hypothesize that the

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increased CH4 production might be caused by changes within the methanogen

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community in the rumen of dairy cows fed agricultural residue diets.

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Culture-independent molecular approaches are currently widely applied to

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characterize the genetic diversity of complex microbial communities and detect

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community changes resulting from different treatments28. Methanogens can be

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distinguished from non-methanogens based on the sequence of mcrA gene, which

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encodes a key enzyme of methanogenesis. Crucially, the mcrA gene can serve as the

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basis for differentiating different methanogenic species29. By cloning this functional

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gene, many studies successfully assessed rumen methanogen diversity in such

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ruminants as cattle, dairy cow, and buffalo30, 31. In the present study, a total of 763

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clone sequences were obtained from six mcrA libraries, which were then assigned to

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25 species-level OTUs using minimum sequence identity of 94%19. Phylogenetic

215

analysis

indicated

that

eight

OTUs

shared

the

10


highest

identity

with

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Methanobacteriales species and 17 OTUs shared the highest identity with rumen

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cluster C (RCC) strains (Figure 1). In addition, methanogens related to the genus

218

Methanobrevibacter

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Methanobacteriales. OTU1 was close to RCCk (AEV77033) and was the most

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abundant in all libraries. RCCk was first reported, in the rumen of cattle, by

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Tymensen, et al.

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methanogens. Previous studies confirmed the overall dominance of the RCC clade in

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the archaeal consortium in the rumen32-34. Other studies reported that

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Methanobrevibacter spp. are the primary methanogen taxon in ruminants fed

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different diets, as assessed using clone libraries or the TTGE/DGGE technique2, 35,

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and always associated with protozoa36,

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methanogens in the rumen varies significantly in different studies because of

228

differences in sample processing methods, primers used in PCR-amplifications,

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ruminant species, and dietary treatments38.

32

were

the

predominant

phylotype

from

the

order

and is more abundant in the community of protozoa-associated

37

. The proportion of those dominant

230

Analysis of the mcrA libraries using ∫-LIBSHUFF and PCA indicated that

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community structure of methanogen libraries differed between treatments (Table 3

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and Figure 2). The Chao1 and Ace indices reflect OTU richness, and the Shannon

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and Simpson indices reflect OTU diversity (Table 4). According to those indices,

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both CSA and CSB libraries harbored a potentially more diverse methanogen

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community than the MF library. Diversity of the microbial community in the rumen

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is influenced by many factors, such as the ruminal environment, dietary composition,

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additives, and genetic background of the animal species39. In the current study, 11



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inclusion of agricultural residues in the diets might be a major factor affecting the

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diversity of ruminal methanogens. Compared with alfalfa hay and corn silage of the

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MF diet, corn stover in the CSA diet may have provided more structural

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carbohydrates, which was supported by higher NDF and ADF in the CSA diet

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compared with the MF diet. Complex carbohydrates are fermented to volatile fatty

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acids by ruminal microbes in multi-step pathways, which is accompanied by the

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production and utilization of hydrogen40. Different dietary carbohydrates in the CSA

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and MF diets resulted in alterations of volatile fatty acid production patterns (acetate:

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propionate, CSA vs. MF: 3.75 vs. 2.65; P < 0.01) and hydrogen levels, and

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potentially affected the hydrogenotrophic methanogen community. In addition,

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soybean meal may contain more total digestible nutrients than equal amounts of

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rapeseed and cottonseed meals41, which was supported by a higher dietary crude

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protein content in the MF diet compared with the CSB diet. Because high grain

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content can result in lower ruminal pH, adversely affecting some methanogen

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species42, it is reasonable to anticipate that feeding animals the MF diet would result

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in decreased richness and diversity of the methanogen community compared with the

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CSB diet.

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Knowledge of the specific composition of the ruminal methanogen community

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enables a more targeted manipulation of CH4 emissions43. Heat map data revealed

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treatment-dependent OTU distributions (Figure 3). Wide-spread distribution and

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high abundance of some OTUs suggest that they may comprise the core species of

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the ruminal methanogen community in animals fed different diets. Among these, the 12


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abundances of RCCk- and RCCd-like species were highest in all treatments. These

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species exist in both free-living and protozoa-associated methanogen communities32

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and are distantly related to the order Thermoplasmatales (Figure 1). Recently,

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archaea from the order Thermoplasmatales were found to be highly abundant in the

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rumen, as determined by both 16S rRNA and mcrA gene analyses. These microbes

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prefer to utilize methyl groups during methanogenesis44. OTU4, OTU5, OTU6,

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OTU9, OTU16, and OTU18 were identified as Methanobrevibacter smithii,

267

Methanobrevibacter

268

Methanobrevibacter

269

Methanosphaera stadtmanae DSM 3091, respectively, with the amino acid sequence

270

similarity ranging from 96% to 99% (Figure 1). M. ruminantium, M. smithii, and

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Methanobrevibacter thaueri were identified as the dominant methanogens in the

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rumen of feedlot cattle fed diets of predominantly corn or potato byproducts45. M.

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ruminantium was also reported as the largest methanogen group in lactating dairy

274

cows fed total mixed rations, followed by M. stadtmanae46. Furthermore, in the

275

ovine rumen, the majority of clones were also identified as belonging to the genus

276

Methanobrevibacter, although M. ruminantium and Methanomicrobium mobile were

277

confirmed as the major methanogens using 16S rRNA-targeted fluorescent in situ

278

hybridization by Yanagita, et al.

279

largest group of clones in the sheep rumen library by Wright, et al.

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methanogen species mentioned above are all hydrogen utilizers49,

281

abundance and wide distribution of methanogenic species indicates that both

millcrae, gottschalkii,

Methanobrevibacter Methanobrevibacter

ruminantium, and

millerae,

47

, while M. gottschalkii was reported to be the

13


48

. The

50

. Such high


282

methylotrophic and hydrogenotrophic methanogenesis may play important roles in

283

methane production in the rumen of dairy cows. However, some OTUs were only

284

occasionally identified in specific libraries. For example, OTU10, OTU12, and

285

OTU19 only emerged in the CSA library, and OTU20 was only found in the MF

286

library. Most of those OTUs were distantly related to Methanomassiliicoccus

287

luminyensis, with similarity ranging from 75% to 83%, which means that these

288

methanogens should be classified as new species. Considering that methanogens use

289

different pathways to produce CH4, e.g., hydrogenotrophic and methylotrophic

290

methanogenesis pathways, it is possible to modulate bacterial fermentation or animal

291

diet to control the production of methanogenesis type-specific substrates.

292

Furthermore, specific vaccines or antibodies and bacteriocins against targeted

293

methanogens can be designed or used to control the methanogenic community and

294

subsequent methane production35.

295

In conclusion, agricultural residues in feed rations affected the ruminal

296

methanogen community. Methanobrevibacter sp. and RCC (especially RCCd and

297

RCCk) methanogen clusters might comprise targets to reduce CH4 production by

298

dairy cows fed rationed agricultural residues.

299

FUNDING

300

This study was funded by the National Natural Science Foundation of China (grant

301

nos. 31261140365 and 31501981), Agricultural Science and Technology Innovation

302

Program (ASTIP-IAS12), and Modern Agro-Industry Technology Research System

303

of the PR China (nycytx-04-01). 14


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NOTES

305

The authors declare no competing financial interest.

306 307

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451 452

18


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453

Figure captions

454

Figure 1. Phylogenetic analysis of partial McrA amino acid sequences from ruminal

455

methanogen libraries and the abundances of each OTU. Representative OTUs were

456

defined at ≥94% sequence identity. Reference sequences were retrieved from the

457

GenBank database, and their accession numbers are presented in parentheses. Bar,

458

0.05 nucleotide substitutions per base. Numbers by the nodes indicate confidence

459

levels from 1000 bootstrap resampling.

460

Figure 2. Principal component analysis (PCA) showing the differences among

461

ruminal methanogens of dairy cows fed MF, CSA, and CSB diets before (0 h) and

462

after (2 h) morning feeding on day 91.

463

Figure 3. Heat map showing OTU distribution in ruminal methanogen libraries of

464

dairy cows fed MF, CSA, and CSB diets before (0 h) and after (2 h) morning feeding

465

on day 91.

466

19



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Tables Table 1. Ingredients and chemical composition of the tested diets Item Ingredients Alfalfa Corn silage Corn stover Soybean meal Rapeseed meal Cottonseed meal Extruded soybean Beet pulp Whole cotton Corn Wheat bran EB100 XP Limestone Salt Premixa NaHCO3 Chemical composition DM, % CP, %DM EE, %DM Starch, %DM Insoluble CP, %CP NDF, %DM ADF, %DM ADL, %DM NFC, %DM GE, Mcal/kg a

MF

Diet CSA

CSB

17.3 18.8 11.3 4.2 2.1 2.1 4.2 10.4 25.6 1.14 0.33 0.75 0.45 0.5 0.92

36.1 11.3 4.2 2.1 2.1 4.2 10.4 25.6 1.14 0.33 0.75 0.45 0.5 0.92

36.1 9.6 6.7 7.5 10.4 23.5 4.5 0.75 0.45 0.5 -

93.1 18.1 5.6 33.2 81.8 35.9 25.2 12.0 33.4 4.2

93.2 16.1 4.7 31.1 85.6 47.6 29.3 10.8 23.8 4.1

93.1 15.1 3.4 30.1 84.5 49.1 32.8 13.2 24.6 4.0

Premix (per kg): VA, 250000 IU; VD, 65000 IU; VE, 2100 IU; Fe, 400 mg; Cu,

540 mg; Zn, 2100 mg; Mn, 560 mg; I, 35 mg; Se, 15 mg; Co, 68 mg.

20


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Table 2. Total copy numbers of ruminal methanogens of dairy cows fed MF, CSA, and CSB diets before (0 h) and after (2 h) morning feeding on day 91 Treatment Time (h)

P value MF

CSA

CSB

0

7.83 ± 0.09

8.02 ± 0.09

7.72 ± 0.11

0.09

2

7.81 ± 0.06

7.89 ± 0.08

7.50 ± 0.13

0.56

21



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Table 3. LIBSHUFF comparison of mcrA gene clone libraries derived from ruminal methanogens of dairy cows fed MF, CSA, and CSB diets before (0 h) and after (2 h) morning feeding on day 91 Comparison CSA-0 vs. MF-0 CSA-2 vs. MF-2 CSB-0 vs. MF-0 CSB-2 vs. MF-2 CSA-0 vs. CSB-0 CSA-2 vs. CSB-2

dCXY score 0.00011 0.00158 0.00011 0.00046 0.00014 0.00007

22


P value

Ruminal Methanogen Community in Dairy Cows Fed Agricultural

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